MC Project

How a co-owner of the New York Giants is using AI to build a women's sports powerhouse with Gotham FC

support@mycoding.id (James Faris) — Thu, 29 Oct 2026 21:36:43 +0700

Carolyn Tisch Blodgett, the owner of Gotham FC, thinks AI can create women's sports additional lucrative. Carl Timpone / BFA

New York Giants and Gotham FC co-owner Carolyn Tisch Blodgett is betting on AI to change women's sports into a important moneymaker.

"If AI can create you additional efficient, that totally changes anywhere women's sports can go," Tisch Blodgett stated at Business Insider's The Long Play event on Thursday afternoon.

Tisch Blodgett, who's the guide owner of Gotham FC in the National Women's Soccer League, sees AI as a way to decrease the expenses of operating a sports endeavor without cutting corners.

"There's a lot of parts of a sports squad that are fair costly to operate. It's costly to run a stadium, it's costly to run a ticketing team, costly to run a promotion team," Tisch Blodgett said.

Those struggles are heightened for women's sports, which historically haven't gotten the identical flat of funding as men's sports.

Tisch Blodgett said alongside Business Insider's Nathan McAlone concerning how to create women's sports additional financially successful. Carl Timpone / BFA

"The income was not elevated adequate to really validate construction out an complete endeavor team, and the endeavor example fair didn't really work," Tisch Blodgett stated of women's sports.

Tisch Blodgett made a name for herself by starting sports-focused project chief resolute Next 3, which has invested in Gotham FC, the Los Angeles Golf Club in athletics association TGL, Premier Lacrosse League, and lottery ticket location Jackpot.com.

The Gotham FC owner has had a front-row place to operating sports since she was a kid: Her family bought fractional of the NFL's New York Giants in 1991. The Tisch family runs Loews Corporation, a inn and coverage conglomerate value concerning $22.9 billion.

Under the Tisch's ownership, the Giants have won two Super Bowls. Tisch Blodgett has already matched that heading figure in the three years she's owned Gotham FC — although construction a victor hasn't been easy.

Building a victor by gathering feedback

Tisch Blodgett felt firsthand the challenges that women's sports teams visage following taking complete Gotham FC in 2023. The New York-based squad had talent, as it went on to bring residence its archetypal heading months later.

But achievement on the throw hadn't translated to a winning business. Gotham FC didn't have its own endeavor agency whenever Tisch Blodgett took over, and players shared a custom site alongside a association squad of 16-year-old boys.

While Gotham FC had "a awesome merchandise on the field," Tisch Blodgett said, "attendance was really low" because of a deficiency of awareness.

"It was apparent that the group that came really liked it, but it was extremely small," Tisch Blodgett stated of Gotham FC's fanbase in 2023.

Tisch Blodgett has since flipped the script. This July, Gotham FC sold out Citi Field in Queens, example complete 42,000 fans in what she stated was the biggest women's sports event always in New York City.

Gotham FC announced in July that it would call Queens residence starting in 2028 — a important upgrade from its current stadium in Harrison, New Jersey, which is difficult to attain from New York City by community transit.

One key to Gotham FC's achievement has been gathering feedback. Tisch Blodgett, who led promotion for fitness elephantine Peloton before starting Next 3, stated learning from fans "makes the entire endeavor smarter" and has been crucial to the football club's growth.

"Feedback is incredibly crucial to me — it's how we run our organization," Tisch Blodgett said. "After all game, we dispatch out a study to all individual that attended, basically saying, 'Did you akin it? Would you propose it to a friend?'"

Gotham FC's Net Promoter Score — which measures how apt customers are to propose the brand to a companion — rivals Apple, Tisch Blodgett said.

"It makes all individual in the institution comprehend what we're construction towards in a much additional productive way," Tisch Blodgett said.

A tiny world model running games on a Raspberry Pi Pico 2 W

support@mycoding.id (Adi Gunawan) — Thu, 29 Oct 2026 21:32:28 +0700

Using 2 small neural networks to create and perform the equivalent at the identical period on a Raspberry Pi Pico 2 W. The archetypal one creates the game: stated the current example and the action, it predicts the next example and the reward. The second one plays that game: it uses the generated example and picks an action.

Every example complete was sampled by the earth example network, and the actions were taken by the performer network.

I got curious in looped transformers, anywhere one transformer obstacle is applied multiple times alongside the identical weights alternatively of stacking distinct layers. Reusing weights is cheap on memory, so I wanted to see if a looped earth example could be small adequate to run on a microcontroller. I picked the Pico 2 W since it is cheap and has an FPU, and small games since I could compose the genuine versions immediately into numpy and inspect all generated example against them. Later I added a streaming RL delegate so the commission could additionally study to perform inner its own dream.

Contents: the two networks · the games · the earth model · the agents · quantization · on the chip · flashing · browser · reproduce · code layout

The earth example and the actor

	network 1: the earth model	network 2: the actor
job	frame + act → next example + reward	frame → action
architecture	looped transformer, q int8	MLP alongside two hidden layers, float32
size	26k–131k parameters	9k–16k parameters
cost per frame	2–8M multiply-adds	9k–16k multiply-adds
trained	on recorded genuine games (how)	with stream-x, in the genuine equivalent or inner the aspiration (how)

The size depends on the game, several games necessitate additional parameters to study them to be playable, we tried to get to keep the figure of the parameters small enough.

On the part neither network always uses the genuine game: the performer lone sees frames the earth model, and the earth example lone gets actions from the actor. Both run on center 1 of the RP2350, during center 0 handles USB and the display.

The pretrained performer can be exchanged for a caller stream-x delegate that learns from scratch on the board. And any clasp media hands authority to you, so you can perform the aspiration yourself.

Each equivalent is a few hundred lines of numpy in src/tinyworldformer/games/. It renders to a small grid of token ids, and one example continually holds the entire equivalent state, so hidden province have to be drawn into the frame: the ball's heading is part of its token, and Doom-lite has a minimap.

game	frame	rules	random event	world model	exact frames, 2 loops
Breakout	20×16	paddle, ball, 56 bricks, 5 lives	the assist following a miss	26k params, 4.3M MACs	99.99%
Doom-lite	32×32	raycast first-person perspective of an 8×8 maze; an enemy walks shortest paths to you; you shoot	the enemy's respawn	55k params, 4.2M MACs	83.6% (see below)
Flappy Bird	24×24	gravity, flaps, scrolling pipes	the next gap height	46k params, 2.0M MACs	100%
Pong	20×32	you against a CPU paddle that reacts late, archetypal to 5	the assist following a point	46k params, 2.3M MACs	99.45%
Pac-Man lite	48×48	23×21 maze, 249 pellets, two ghosts on shortest paths, 3 lives	the ghosts' respawn	131k params, 8.2M MACs	86.4%

"Exact frames" is the portion of held-out transitions anywhere all division of the predicted example matches the genuine game. Frames correct following a random event are remaining out, since those can lone be sampled, not predicted. Doom-lite's 3D perspective has 768 cells and a sole shaded partition pixel off counts the entire example as wrong, so its figure looks worse than it plays; the equivalent province is nearly continually correct (see checking the dream).

You can perform the genuine games in a terminal: uv run python -m tinyworldformer.games.play --game pacman (or breakout, doomlite, flappy, pong).

How the earth example works

The example is cut into quadrate patches: 2×2 cells in Breakout, 4×4 in Doom-lite, Flappy Bird and Pong, 6×6 in Pac-Man. That gives 36 to 80 tokens per game. A patch's embedding is the sum of one learned vector per cell, alongside a distinct array for all stance inner the place so the division command isn't lost. Every token additionally gets a stance vector and the action's vector.

The example is a sole transformer obstacle (attention affirmative a ReLU MLP) alongside one set of weights, applied 1 to 4 times, alongside the input added rear before all pass. The output following all continue is trained against the next frame, so at run period the iteration figure trades speed for accuracy. On the Pico to keep a decent example charge we use uses two loops.

The animation shows one held-out Doom-lite step. After one continue the example draws an enemy that isn't there, and all additional continue removes part of it: 92, 35, 12, afterward 0 incorrect cells. The bars on the correct are the portion of held-out frames all iteration figure gets exactly right.

Here is a dreamed Doom-lite stage decoded following 1, 2, 3 and 4 loops, alongside red boxes on cells that differ from the genuine rules:

Exact held-out frames by iteration count:

loops	Breakout	Doom-lite	Flappy Bird	Pong	Pac-Man
1	99.68%	59.8%	99.99%	98.47%	79.6%
2	99.99%	83.6%	100%	99.45%	86.4%
3	100%	85.9%	100%	99.60%	85.7%
4	99.96%	84.7%	100%	99.53%	84.4%

The example outputs a mark for all division and all token. Turning those scores into a example turned out to matter nearly as much as the model, and it ended up as three rules (shown complete on Pong):

Background cells (walls, bricks, pellets, floor) all obtain their most apt token independently.
Singletons (the ball, the player, all ghost) are placed alongside one choice complete all (cell, token) pairs, so there is continually exactly one of each. After a random event the choice is sampled among candidates inside 2.2 logits of the best, so the earth example samples a new assist or respawn alternatively of averaging them.
Pac-Man and the ghosts are 2×2 sprites, but lone one division of all carries province (the mouth holds the heading; the ghost's lower-left division holds whether a pellet is underneath). The another three cells are stamped from it alternatively of predicted.

We implemented Rule 2 since the archetypal Breakout example drew two balls at once; one earth choice took exact frames from 91.6% to 99.7%.

Accuracy on recorded data wasn't enough. An delegate drives the aspiration into states the data never had, and any error there is item it can exploit. So the chief inspect runs during an delegate plays: peruse the equivalent province rear off the dreamed example (games/.py: read), use the genuine rules to that province and the agent's action, and difference the outcome alongside the next dreamed example and reward.

5,000 dreamed steps per equivalent at 2 loops, alongside the shipped delegate (training/evalwm.py --agent):

game	wrong equivalent states	wrong rewards	wrong cells per step
Breakout	not peruse back; 0 frames alongside unattainable tokens	6 (paid without a masonry block breaking)	–
Doom-lite	1	0	1.50
Flappy Bird	0	0	0.00
Pong	1	0	0.00
Pac-Man	742	38	0.39

First, agents perform the genuine equivalent and all stage is recorded as one example (frame, action, next frame, reward), 1–3 myriad per game. Some episodes commencement from different states, akin bricks alongside holes or random positions, so the data covers additional of the game.

Then the earth example learns to foretell the next example alongside a per-cell cross-entropy loss: 30k steps, alongside the archetypal 3–4k steps run in float, afterward int8 rounding switches on (QAT).

The int8 weights are written into Rust origin alongside all drift stored as its exact bits. We inspect them alongside cargo test to reproduces the Python entire figure spec bit for bit, and afterward the firmware runs on the Pico.

An delegate trained in the earth example reaches states the recorded data never had, so document genuine games alongside that delegate and fine-tune the earth example on everything.

The delegate in distinct games stated exploiting them so those are several fixes to it:

Weighting the defeat by "this division changed" biased the example toward predicting change, so it drew two balls and bankrupt two bricks. Weighting by anywhere things can happen in the input frame, affirmative the earth singleton choice, fixed it.
A Breakout delegate in the aspiration got 154 points alongside 26 bricks left, since the earth example didn't eliminate bricks from the border whenever it were hit. Doom-lite agents learned to snipe from 5 cells away.
Agents trained lone in the aspiration scored 210 there (the genuine maximum is 56) and 28 in the genuine game, as World Models (Ha & Schmidhuber) predicts. Each collect-and-fine-tune circular closed the utilize that delegate had found.
The Doom-lite aspiration sometimes misplaced the enemy sprite and never drew it again: the example copied the former perspective alternatively of redrawing it from the minimap. Noise augmentation fixed it (train --noise 0.3, as in GameNGen): input views get random pixels and sometimes endure the sprite.
d=32 couldn't assimilate the wider Breakout data and d=48 could. Pac-Man's 48×48 example needed d=64.

The agents use Stream AC(λ) (Elsayed, Vasan & Mahmood, 2024), which learns from one passage at a time: no replay buffer, no batches, no mark network. Eligibility traces transport credit rear in time, and ObGD shrinks any stage that would overshoot the TD target. The guideline and value networks all have two hidden layers of 64 units (32 on the Pico) alongside LayerNorm.

The input is a characteristic vector peruse off the example (training/streamx.py: observe_*, mirrored in Rust in tinyworldformer-rs/src/agent.rs). For example, the ball's row, pillar and heading in Breakout, or in Pac-Man, for all direction, the shortest-path extend to the nearest pellet and how near all shade is.

Below is one training run per equivalent (real game, 500k steps) at six stages: untrained, the end, and the snapshots anywhere the mark has covered 25, 50, 75 and 95% of the way. Each panel plays greedily from the identical commencement and skips a few steps per frame. "try" counts the episodes played so far, so you can see the crashes.

Breakout

Doom-lite

Flappy Bird

Pac-Man lite

Pong

Greedy come back in the genuine game, average of 10 episodes, at snapshots of the identical run:

game	0	1k	2k	5k	10k	20k	50k	100k	150k	250k	500k	max
Breakout	8.2	17.0	15.9	21.9	29.9	29.9	29.9	31.1	35.0	39.9	45.6	56
Doom-lite	−5.0	−5.0	−5.0	−5.0	−5.0	59.5	69.9	78.1	81.8	82.1	82.9	–
Flappy Bird	−1.0	−1.0	−1.0	1.9	24.6	24.9	96.2	123.7	309.2	332	332	332
Pac-Man	7.0	3.8	17.0	17.7	8.2	46.8	72.9	138.9	146.6	190.3	217.4	249
Pong	−4.3	−3.9	−3.9	−3.9	−1.7	−2.0	−0.3	1.1	1.7	1.1	1.1	5

Without shaping, Doom-lite agents campsite in the commencement border and fire, since the enemy continually comes to them. --idle-penalty 0.1 expenses 0.1 for all stage spent in a division visited additional than 6 times in the final 20 steps. The stance is peruse off the minimap, so the penalty plant inner the aspiration too. With it the delegate patrols and gets twice the kills.

tinyworldformer-rs/src/learner.rs is the identical algorithm in no_std Rust, alongside the backward continue written by hand. It matches 200 PyTorch updates to inside 3.5e-6. On the host, a caller delegate inner the Rust int8 Flappy Bird aspiration averages 6 pipes per event following 25k steps, 121 following 100k, and 300+ following 250k.

Quantization and the Pico

Every matrix in the earth example is int8 alongside one measure per output row (scale = max|w| / 127). Activations are int8 too, alongside one measure per tensor and per iteration index, since the loops see distinct ranges. Matmuls sum int8 × int8 into int32 (two multiply-adds per SMLAD education on the RP2350) and afterward use one drift multiply by the two scales. Softmax uses a 1024-entry exp table, alongside probabilities stored as uint8. Norms, residuals and embeddings remain in float32, since the RP2350 has an FPU.

Training applies the identical rounding (QAT alongside a straight-through estimator), so the int8 example is the example that was trained. rustexport/intref.py is the int8 example in numpy alongside all drift procedure in a fixed order; the Rust motor reproduces it bit for bit, and cargo test checks aureate vectors for all exported env.

game	int8 weights	float32 (embeddings, norms, scales)	game data	agent (float32)	firmware flash	firmware RAM
Breakout	19.7 KB	31.6 KB	1.1 KB	54.1 KB	361 KB	299 KB
Doom-lite	33.9 KB	91.9 KB	12.0 KB	61.3 KB	471 KB	357 KB
Flappy Bird	30.1 KB	69.5 KB	10.1 KB	50.8 KB	409 KB	227 KB
Pong	30.1 KB	70.4 KB	10.9 KB	52.6 KB	414 KB	244 KB

Flash and RAM are measured from the firmware ELF (size -A), built alongside the Display Pack driver, so they contain the code, USB, the display controller and the on-device learner. The Pico 2 W has 4 MB of flash and 520 KB of SRAM, 512 KiB of it in the chief recollection map. The float32 embedding tables are the largest part and could be int8 too.

src/tinyworldformer/rustexport/ imports lone numpy and torch (a test keeps it that way), so another projects can reuse the export: build a example from rustexport.qat (QLinear, LoopedBlock), train it alongside ActQuant.enabled = True following a drift warm-up, change it alongside rustexport.convert.looped_model, afterward compose the Rust origin alongside int_model_arrays, mlp_arrays and codegen.write_module. rustexport.Golden writes the vectors a Rust test checks.

The firmware (tinyworldformer-rs/firmware) is no_std Rust on embassy. Nothing is allocated at run time: the weights are fixed arrays in flash, and all buffer is a fixed-size fixed in RAM.

Core 1 runs the game. One continue of its iteration (dream_loop in firmware/src/main.rs) is one frame:

The performer says features off the current example (agent::observe) and runs its MLP to choice a button. If on-device learning is on, the learning delegate picks instead; if you are pressing buttons, your media is used.
The int8 transformer runs 2 loops complete the example and the clasp (Engine::forward), and decoding turns its scores into the next frame: backdrop argmax per cell, all singleton placed formerly (sampled for random events alongside an xorshift RNG), afterward the sprite stamps. The reward is the argmax of the reward head; lives and event ends are counters on top.
If learning is on, the learner updates from this one passage and afterward forgets it.
The example goes to center 0 through a two-slot channel. If center 0 is motionless occupied alongside the former frame, this one is dropped, so center 1 never waits for the screen.

When you play, center 1 slows downward to a playable speed (66–150 ms per frame, depending on the game). The delegate runs as accelerated as the part allows.

Core 0 runs embassy async tasks for everything else. Over USB serial, all example goes out as coloured ANSI content alongside a position row (model time, performer time, fps, env and delegate names), and keys arrive rear in. The optional Display Pack (--features display) is a 320×240 ST7789 complete SPI at up to 62.5 MHz, and lone cells that changed since the final example are redrawn. Its buttons are polled all 20 ms. The two cores portion lone the example conduit and a few atomics: who is playing, the pressed key, learning on/off, and the iteration count.

Where the recollection goes:

	in flash	in RAM
world model	int8 matrices, float32 embeddings, norms and scales, the game's beginning frames and colours (52–138 KB)	scratch buffers for one onward pass: activations for 36–80 tokens, the int8 copies the matmuls read, and the per-cell scores of the next example (114 KB for Flappy Bird up to 368 KB for Pac-Man, whose per-cell scores solitary obtain 184 KB)
actor	float32 MLP weights and characteristic normalization (51–61 KB)	its features and hidden layers (about 1 KB)
on-device learner	code only	weights, eligibility traces and normalization for two 32-unit networks (49 KB for Pac-Man up to 106 KB for Doom-lite; it scales alongside the figure of input features)
firmware	code, USB, display controller (about 150 KB)	stacks (16 KB for center 1), USB buffers, example channels

Every equivalent fits in the 4 MB of flash and 512 KiB of SRAM. Breakout uses 361 KB of flash and 299 KB of SRAM; Pac-Man, the largest, uses 600 KB and 460 KB.

Most of the period goes into int8 dot products (dot_i8 in src/lib.rs). One 32-bit burden fetches 4 weights, SXTB16 unpacks bytes 0/2 and 1/3 into 16-bit halves, and SMLAD does two multiply-adds in one instruction. Attention multiplies uint8 probabilities by int8 values, so it uses UXTB16 instead. Norms, the exp array lookup and the final per-output measure remain in float32 on the FPU. A example at 2 loops is 2–4M multiply-adds (8.2M for Pac-Man); on a desktop CPU the identical Rust code dreams a example in 0.7 ms (Flappy Bird) to 1.5 ms (Breakout). I haven't measured the example charge on the Pico itself yet.

The commission boots alongside a caller delegate learning on the device. Press l complete USB, or clasp B for 1 s on the Display Pack, to toggle to the pretrained actor, and again to toggle back.

Flashing a equivalent and an agent

Every export sits flank by flank in the crate: earth models in tinyworldformer-rs/models/envs//, agents in models/agents///. You choice the two at build time.

cd tinyworldformer-rs ./flash.sh --list # what is exported ./flash.sh --env doomlite --agent doom_agent_roam_p0.3 # build and flash (hold BOOTSEL during plugging in) ./flash.sh --env breakout --display # alongside the Display Pack ./flash.sh --env pong --host # perform it in this terminal ./flash.sh --env flappy --default # create it the default for plain cargo TWF_ENV=doomlite TWF_AGENT=doom_agent_roam_p0.1 cargo test --release # aureate tests for that pair

Without --agent, the delegate for the env's equivalent listed in models/default is used if there is one, alternatively the archetypal by name. An delegate for a distinct equivalent is refused alongside a catalog of the valid ones. The position row on display shows which env and delegate are running.

Keys complete USB: Breakout a/d/s, Doom-lite w/a/d/space/s, Flappy space, Pac-Man w/a/s/d, Pong w/s. Then g hands rear to the agent, 1–4 set the iteration count, l toggles on-device learning and r restarts it.

The identical no_std int8 motor additionally compiles to WebAssembly (tinyworldformer-rs/web/). The component has no imports and no wasm-bindgen, and it runs the firmware's loop: dream, agent, and stream-x learning on the fly. A fixed leaf draws the frames on a canvas.

rustup mark add wasm32-unknown-unknown # once cd tinyworldformer-rs/web ./build.sh # one component per env into www/ (or ./build.sh pong flappy) python3 -m http.server -d www # open http://localhost:8000, ?env=pacman picks a game

With the identical seed, the wasm build dreams the identical episodes as the native build, example for frame, at 1–5 ms per example depending on the game. Each component carries its game's default agent; TWF_AGENT=... ./build.sh picks another. The keys are the identical as on the Pico, affirmative arrow keys and on-screen buttons, and f runs the aspiration as accelerated as it can, which helps during learning (l).

uv sync G=pong # breakout, doomlite, flappy, pacman, pong uv run python -m tinyworldformer.training.data --game $G --transitions 2000000 --varied 0.3 # -> data/$G uv run python -m tinyworldformer.training.train --data data/$G --d 48 --heads 3 --ff 96 --out models/${G}_wm.pt uv run python -m tinyworldformer.training.streamx --env genuine --game $G --out models/${G}_agent.pt uv run python -m tinyworldformer.training.evalwm --ckpt models/${G}_wm.pt --agent models/${G}_agent.pt # inspect the dream uv run python -m tinyworldformer.training.streamx --env aspiration --wm models/${G}_wm.pt --out models/${G}_dream_agent.pt uv run python -m tinyworldformer.training.export --ckpt models/${G}_wm.pt uv run python -m tinyworldformer.training.streamx --out models/${G}_agent.pt --export tinyworldformer-rs cd tinyworldformer-rs && TWF_ENV=$G cargo test --release && TWF_ENV=$G cargo run --release

Settings that differ per game:

game	settings
Breakout	1M transitions, --miss-penalty 5, afterward collect alongside the delegate (data --learned --holes 0.5 --out data/breakout_learned) and fine-tune on all of it (train --init ... --data data/breakout data/breakout_learned --steps 15000 --warmup-float 0 --lr 1e-3), four rounds
Doom-lite	--varied 0.5, train --noise 0.3, streamx --max-ep-steps 500 --idle-penalty 0.1
Flappy Bird	streamx --max-ep-steps 3000
Pac-Man	1.2M transitions, --varied 0.4, train --d 64 --heads 4 --ff 128 --steps 40000 --warmup-float 4000, streamx --miss-penalty 5 --max-ep-steps 1500
Pong	streamx --max-ep-steps 5000

path	contents
src/tinyworldformer/games/	the five games (rules, rendering, read), the Game registry, scripted agents, terminal play
src/tinyworldformer/training/	data, earth model, training, aspiration checks, stream-x, export to the Rust crate
src/tinyworldformer/rustexport/	reusable PyTorch → no_std Rust export: QAT layers, the int8 spec, conversion, code generation
tinyworldformer-rs/	no_std int8 engine, aspiration loop, delegate and learner; presenter demo (src/main.rs)
tinyworldformer-rs/firmware/	Pico 2 W firmware
tinyworldformer-rs/web/	WebAssembly build and the browser leaf (www/)

Google’s Ads Decoded Explores How AI Is Changing Search Behavior

support@mycoding.id (Brooke Osmundson) — Thu, 29 Oct 2026 21:24:25 +0700

People are asking longer questions in Google’s AI Mode and using Search to examine decisions earlier, according to the latest Ads Decoded episode.

The October 28 episode features Ginny Marvin, Google Ads Product Liaison, and Shivani Mohan, Search Vice President of Data Science and User Experience Research.

Their conversation covered how group use AI-powered Search and why individual perspectives remain part of their research. Marvin additionally shared takeaways for advertisers evolving their 2027 strategies.

Google Says Search Is Becoming More Conversational And Exploratory

In her LinkedIn post, Marvin outlined three takeaways on the contemporary hunt cognition for advertisers looking at their 2027 strategies:

Discovery is moving up the funnel: People use conversational hunt for brainstorming and finding fine before they attain a acquisition decision.
Curiosity is expanding: Queries in AI Mode are three times longer than traditional searches, and one in six searches is now multimodal, although Marvin’s article does not define the baseline definitions or measure opening for those figures.
Users desire individual perspectives: Podcasts, video reviews, and firsthand cognition remain part of how group investigation and create decisions.

The authoritative event notes add that group are asking 3x longer questions, going rear and onward on follow-ups, and searching alongside sound and images, giving them area to contain individual nuance and activity through complex decisions correct as they search.

That gives advertisers additional to regard than the first hunt phrase. The questions group ask as they narrow their options can disclose concerns that a merchandise clarification or broad assistance leaf doesn’t answer.

The conversation additionally suggests that finding and evaluation can happen inside the identical conversation. A individual can commencement by exploring a problem, afterward ask concerning options and tradeoffs as they study more.

What Google’s Search Figures Tell Advertisers

Google’s October 28 promotion announcement additionally cites the 3x longer figure, linking to a U.S. AI Mode report published in May 2026. The figure compares average query length, but doesn’t display how differences in users or hunt tasks power that comparison.

Longer questions can provision advertisers additional data concerning someone’s needs. The fig by itself doesn’t display stronger purchasing intent or improved conversion rates.

The study additionally says additional than one in six AI Mode searches in the U.S. are multimodal. That’s narrower than the “one in six searches” wording in Marvin’s article and shouldn’t be applied to all Google searches.

Advertisers can use these findings to analyze the questions customers ask and the data they include. Mohan’s comments concerning individual perspectives location another part of that research: what group desire from the satisfied they find.

Users Still Seek Human Perspectives Alongside AI Summaries

In her LinkedIn article concerning the episode, Mohan wrote that users:

…appreciate the streamlined clarity of AI summaries, yet they actively crave the affluent detail, lived experience, and earned authority of the open web.

She pointed to forums, podcasts, and videos as places group search those perspectives.

For advertisers, her comments propose customers desire additional than a clarification of what a merchandise does. They may additionally desire to comprehend how it performs in practice, what its restrictions are, and why person chose it.

A assessment or display can answer those questions whenever it includes cognition the brand’s merchandise copy doesn’t provide. Repeating that copy on camera gives the buyer small additional information.

Mohan additionally referred to billions of clicks to the open web, without providing a timeframe or comparison. The fig doesn’t display whether traffic is expanding or how those clicks are distributed throughout websites.

Her comments depict petition for firsthand experience, but don’t established that publishing additional videos or reviews volition bring additional Google traffic.

For 2027 planning, advertisers can commencement alongside the concerns customers lift before buying, afterward measure whether their satisfied answers them.

What Paid Search Teams Should Consider For 2027

In the replies to Marvin’s article on October 29, two commenters asked how the behaviors discussed on Ads Decoded translate to run management.

Md Jihad asked how small businesses should modify their ad copy and landing pages for earlier, exploratory intent.

Ana Trujillo Martin asked whether Mohan identified signals retailing teams should observe as hunt behavior changes, including how to construe impressions and click-through rate.

The posts and event notes don’t provision particular run settings for those scenarios. Advertisers can motionless use the conversation to guide a few checks as they scheme for 2027:

Look for needs customers depict before they cognize the merchandise name. Review client questions, revenue conversations, and hunt conditions for recurring problems. Test ad messaging that addresses those needs during making apparent what the endeavor offers.
Give group adequate data to difference their options. Review landing pages for questions concerning price, compatibility, setup, and limitations. If visitors need those answers before requesting a citation or buying, create the data uncomplicated to find.
Connect supporting satisfied to the decision. Link applicable reviews, demonstrations, and client stories from landing pages. Choose satisfied that addresses a known concern, and provision visitors a apparent next stage formerly they’ve answered it.
Check whether investigation leads to a afterward purchase. Where measure allows, assessment whether visitors to difference or instructional pages come back and rotate into customers. Assess results complete the normal acquisition timeline. Changes in impressions, click-through rate, or involvement solitary won’t display whether those visits generated business.

Looking Ahead

The podcast and accompanying posts depart multiple advertiser questions unanswered, including how these behaviors change by industry and purchasing stage.

Google has described longer questions and before discovery, but hasn’t supplied conversion benchmarks for the behavior discussed. Advertisers volition need to test which client questions their existing satisfied leaves unanswered and whether addressing them helps group move toward a purchase.

Featured image: Courtesy of Google via LinkedIn

Category News PPC

Leaning into convenience helped Nubank break into American fintech, cofounder says

support@mycoding.id (Dan Defrancesco) — Thu, 29 Oct 2026 21:21:37 +0700

Description

Cristina Junqueira helped build Brazilian fintech participant Nubank into among the world's largest digital financial services platforms.

Now, as she leads Nu's emerging US business, she is taking on its biggest difficulty yet: breaking into America's crowded banking market.

As part of Business Insider's The Long Play, Junqueira sat downward alongside Dan DeFrancesco, administrator publishing company and anchor of Business Insider Today, to portion her insights on how to build rely and measure in banking, akin leaning into convenience through digital banking products.

During the discussion, called "Building a Global Challenger," Junqueira additionally talked concerning her scheme to obtain on incumbents in retailing banking.

Patrick Stewart, 'Star Trek' and 'X-Men' star, dead at 86

support@mycoding.id (Olivia Singh,Callie Ahlgrim) — Thu, 29 Oct 2026 21:07:39 +0700

Patrick Stewart at the 73rd Primetime Emmy Awards in 2021. Rich Fury/Getty Images

Legendary performer Patrick Stewart, known for his roles in the "Star Trek" franchise and "X-Men" films, has died at age 86.

A post on his authoritative Instagram page announced Steward died at his Los Angeles residence Wednesday "in the loving attention of his cherished spouse Sunny, following a concise and poignant journey alongside Alzheimer's Disease and Lewy Body Dementia."

"He has been held in the heated clasp of family and friends, surrounded by live music, prayer, tears, laughter, and the benevolent of profound emotion that lone he could motivate following a life of devotion to us all," the article continued. "We volition everlastingly cherish the peaceful comfort and consideration on his face, an enduring reminder of his invincible grace."

In lieu of flowers, the family requested memorial contributions be made to Johns Hopkins Alzheimer's Disease Research Center Fund and Alzheimer's Foundation of America Caregiver Resources.

Stewart as Captain Jean-Luc Picard in "Star Trek: The Next Generation." CBS via Getty Images

Born on July 13, 1940 in Mirfield, Yorkshire, England, Stewart became curious in acting at age 12, whenever an English instructor introduced him to William Shakespeare's writing. Stewart started participating in theater productions and remaining residence at the age of 17 to go to perform school.

The performer appeared on a assortment of TV shows commencement in the '60s, but his big interrupt came whenever he landed the function of Captain Jean-Luc Picard on the sequence "Star Trek: The Next Generation."

The sci-fi display lasted for seven seasons between 1987 and 1994. Stewart additionally reprised his function for an event of the display "Star Trek: Deep Space Nine" as fine as four movies in the franchise: "Star Trek Generations" (1994), "Star Trek: First Contact" (1996), "Star Trek: Insurrection" (1998), and "Star Trek: Nemesis" (2002). He additionally did sound activity for "Star Trek" video games.

Stewart would go on to celebrity in another famous franchise, Marvel's "X-Men," making his debut as Professor Charles Xavier, a mutant and originator of the X-Men, in the 2000 movie "X-Men." The movie additionally starred Ian McKellen as the mighty mutant Magneto.

Stewart as Charles Xavier in "X-Men." Twentieth Century Fox

The two actors became near allies in genuine life, notwithstanding playing on-screen rivals, alongside McKellen officiating Stewart's wedding to singer Sunny Ozell in Reno, Nevada in 2013.

Stewart portrayed Charles Xavier in multiple additional "X-Men" films, and reprised the function for the forthcoming MCU movie "Avengers: Doomsday," out this December.

Stewart's most latest roles included sound activity for the animated sequence "American Dad!" and in the 2026 movie "The Sheep Detectives." He additionally reprised his function as Jean-Luc Picard from 2020 to 2023 in the Star Trek series, "Star Trek: Picard."

Stewart is survived by Ozell and his two children, Daniel Stewart and Sophia Stewart, from his archetypal marriage to Sheila Falconer.

This is a evolving story. More to come…

Reddit will force everyone to log in

support@mycoding.id (Jay Peters) — Thu, 29 Oct 2026 21:07:00 +0700

Reddit is announcing a huge shift: It’s going to commencement requiring users to log in.

Right now, you can browse Reddit without having an account, and the location is mostly a awesome asset for crowdsourced data on a entire range of topics. I cognize I’m not the lone individual who appends “reddit” to a lot of Google searches to discover answers to things written by genuine humans instead of robots. But that openness has made it a mark for abrasion and automated traffic, foremost Reddit to document lawsuits complete alleged unauthorized access of its data and create merchandise changes akin limiting admission to “Old Reddit.”

There’s no conclusive timeline on whenever this alter volition rotate out to all users, or how the location volition activity if you’re logged out. (If I dispatch my companion a nexus to a thread and they aren’t logged in, what volition they see?) To start, Reddit volition test the logged-in necessity in “select markets exterior the US” in the “coming months,” according to CEO Steve Huffman. “We’ll appearance at the effect on the person experience, on our business, and on the entire Reddit ecosystem, fig out anywhere the correct boundaries are, and go from there.” Reddit has additionally rebuilt and is rereleasing the Reddit app’s incognito mode.

Huffman claims the login necessity is improved for Reddit’s person cognition and its ads endeavor and is “more protective of Reddit data.” The “vast majority” of unauthorized Reddit admission happens “through our logged-out experiences,” although the business volition motionless attack licensing deals of its data alongside companies, akin the deals it made alongside OpenAI and Google in 2024. Huffman notes that Reddit does not need to cognize a logged-in user’s character — “Honestly, we don’t desire to know” — fair that the person is logged in at all. And he says that additional logged-in users lets the business provision “more applicable ads.”

“This is a big alter for Reddit, anywhere we’ve allowed logged-out admission to basically all of Reddit for the final two decades,” Huffman says. “And I don’t cognize concerning you, but as person whose existence has been defined by the open internet, it’s a big alter for me. But I’ve arrive to the decision that this is the correct decision for our phase and the correct decision for our business.”

Reddit is making this notice alongside its Q3 2026 earnings, which were released today. Search traffic was “down meaningfully” in Q3, Huffman says in the company’s shareholder letter, alongside logged-out traffic and web traffic being the most heavily impacted. “During October, we have seen that hunt traffic has dropped by additional than 1 myriad referrals on average per week,” Huffman says.

However, Huffman notes that app and logged-in regular energetic distinctive users create up “over 80% of the monetization on Reddit,” which he says “speaks to the power of Reddit as a destination and the effect of our ongoing merchandise work.”

Follow topics and authors from this narrative to see additional akin this in your personalized homepage nourish and to obtain email updates.

Jay Peters

Barry Diller is 84 and says he has no plans to retire: 'I have a motor inside me.'

support@mycoding.id (Dan Whateley) — Thu, 29 Oct 2026 20:52:51 +0700

Barry Diller says he has a motor that doesn't quit, and that withdrawal isn't on the table. Carl Timpone/ BFA

He may have run Paramount, built the Fox tv network, and fair pulled a buyout recommendation for MGM Resorts, but media and tech administrator Barry Diller says he's not done yet.

He has a "motor inside" that fair won't stop, Diller stated Thursday at Business Insider's The Long Play in New York.

"I'm motionless curious," he told Peter Kafka, BI's chief correspondent. "If I can be busy and hopefully be useful, afterward OK."

"At several point, person volition inform me in several masterful way, either it's complete or, in another way, it volition be over," he said, alluding to the final bow. "I volition either pay attention, or not, and they volition drag me out to the heap."

Diller's desire to keep foremost companies method staying on top of important scientific changes, specified as AI.

"I am, at any point, prepared to alter my intellect according to events of that moment," he said. "I don't think any the former procedure is should instruct that," he said.

At People Inc., Diller has overseen multiple scheme shifts. The business is evolving from imprint to a digital business, and akin another publishers, it's had to modify to important Google traffic declines.

On Thursday, People Inc. laid off 195 workers, according to a memo from its CEO, Neil Vogel, which Business Insider viewed. The business cut workers from its "print and bequest web businesses," during adding hundreds of staffers in another endeavor areas that it hopes to grow, the memo said.

Diller told Kafka that People's layoffs were a sign that its imprint endeavor was in a "steady benevolent of decline," and that it was shifting its workforce to concentration on new endeavor priorities.

Diller's period isn't solely focused on business: He's additionally worked on assorted public-interest projects, specified as evolving New York's High Line and Little Island alongside his wife, Diane von Fürstenberg.

On Thursday, he teased a coming project for Los Angeles, too, but wouldn't disclose details.

Despite taking joy in seeing satisfied attendees at Little Island on the Hudson River, Diller stated he's not focused on his community legacy.

"I don't do legacy," he told Kafka. "If you say legacy, it benevolent of method all you're doing is looking backward, and that's fair boring to me."

Google’s Q3 Selloff Raises Advertiser Concerns About AI Search

support@mycoding.id (Brooke Osmundson) — Thu, 29 Oct 2026 20:47:55 +0700

Alphabet shares fell concerning 13% Thursday following Q3 results showed slower Search income growth alongside dense AI spending. The selloff renewed concerns concerning how Google volition prosperity its AI enlargement as hunt behavior changes.

Some marketers see the results as evidence that Google is protecting income at advertisers’ expense. They item to unwanted traffic, broader keyword matching, and rising expenses as signs that advertisers are paying for Google’s transition.

The earnings call supports parts of that disagreement during leaving others unproven. Google’s comments concerning AI Mode assistance explain why expanding Search use isn’t translating into stronger income growth, and why advertisers may inquiry whether expanding AI ad placements volition advantage their businesses.

Why Advertisers Are Questioning The Cost Of Google’s AI Expansion

Alphabet spent $51.36 milliard on chief expenditures in Q3 and reported negative liberated prosperity stream of $9.07 billion. Those figures put Google’s slower Search income growth alongside a significant spending dedication as it expands its AI business.

For advertisers, the involvement is whether Google’s attempt to enhance AI monetization volition addition the disbursal of reaching customers. Google can create additional income by creating additional promotion opportunities, expanding what it earns from existing traffic, or both. Each way has distinct consequences for run performance.

More ad placements could assistance advertisers attain customers they earlier missed. They could additionally straightforward spending toward exploratory conversations that create small contiguous sales. Higher click expenses would necessitate improved conversion rates or additional precious customers to maintain the identical return.

Advertisers already dealing alongside irrelevant clicks and small exact targeting may see these results as confirmation of their concerns. But the earnings numbers don’t demonstrate Google changed its auction or prosperity rules to pay for AI.

What Marketers Are Saying About Google’s Revenue Growth

Max Anderson argued that Google is sustaining revenue by charging advertisers additional for lower-quality traffic. He pointed to broader keyword matching, auction pricing, and campaigns spending twice their regular budgets.

Daniel Koss compared that method alongside traditional media businesses raising prices as petition declines. His disagreement is that advertisers eventually drag spending whenever the returns no longer validate the cost.

Some of the practices Anderson describes are part of Google’s published auction and prosperity rules.

Google’s published auction rules document for Ad Rank thresholds alongside competing advertisers. Those thresholds can create significant CPCs equal without another eligible ad immediately below yours. A elevated click cost solitary doesn’t established that Google lately abandoned its auction model.

Google additionally defines regular run budgets as averages. Most campaigns can expend up to twice that amount in one day, topic to monthly spending limits. A $2,000 day against a $1,000 average regular prosperity can autumn inside those rules.

That won’t recommendation much comfort to advertisers paying for irrelevant clicks. A run can prosecute Google’s rules and motionless expend prosperity on traffic that produces few qualified leads or sales.

Koss’s difference describes a hazard for Google if those returns deteriorate. Advertisers have their own financial targets, and Google’s need to monetize AI won’t validate spending that fails to encounter them.

What Google Still Has To Prove To Advertisers

Google has pointed to akin click-through rates for sponsored and integrated merchandise listings in AI Mode as evidence of promising ad performance. That shows group are consenting to click ads inside the experience, but doesn’t display how those visitors change compared alongside traditional Search traffic.

For advertisers, those comparisons would assistance explain what they’re buying. An exploratory conversation could current a client who purchases later, possibly requiring a longer acquisition window. It could additionally create a paid sojourn that never goes beyond that first research.

Google currently combines AI Mode performance alongside norm run and hunt conditions reporting. Advertisers can measure general run results, but they cannot cleanly difference AI Mode’s acquisition costs, conversion rates, or guide norm alongside another Search traffic.

That leaves advertisers backing placements they can’t analyze separately during Google expands their availability.

The Q3 results display that Google’s AI passage carries financial consequences equal as Search use grows. As Google plant to near its income gap, advertisers need a clearer document of what their spending delivers.

Featured image: Dugguphotovala / Shutterstock

Category News PPC

Patrick Stewart Has Died

support@mycoding.id (Putri Silvia) — Thu, 29 Oct 2026 20:47:38 +0700

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One of the Best QLED TVs of 2026 Is Over $1,300 Off Right Now

support@mycoding.id (Daniel Oropeza) — Thu, 29 Oct 2026 20:30:00 +0700

Daniel is Lifehacker's Shopping Editor covering tech deals and reviewing TVs, headphones, speakers, and projectors. He earned his master’s in reporting from Columbia University and has reported for the Miami Herald. He lives in Atlanta.

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One of the archetypal things you'll notice concerning the QM8L is the “Zero Border” bezel design, which gives it a modern, minimalistic look. When you rotate it on, you'll apt note how brilliant this TV gets, which is a huge advantage QLEDs have complete OLEDs. TCL claims it reaches 6,000 nits—seeing as the brightest OLED TV on the market lone reaches 700 nits, no OLED can arrive near to this unit's brightness. Another crucial spec to note current is the local dimming zones: TCL claims this TV has up to 4,000, which method it gets top-tier backlight control, constricted ray blooming (thanks in part to TCL's "Halo Control"), and amazing difference levels that several power not be capable to differentiate from an OLED.

What do you think so far?

As many of us won't manually calibrate our TVs, the image modes you can toggle to in the settings volition be most people's go-to. This TV's "Filmmaker mode" provides exact color and picture, and if you're a gamer, you can use the native 144Hz high-refresh rate. If you don't already have a encircle audio scheme at residence and desire to keep a minimalist setup, the QM8L comes alongside Dolby Atmos-ready Bang & Olufsen speakers, which recommendation above-average audio output compared to most TVs. You can peruse additional concerning these features in CNET's 8.8/10 review. If 65 inches isn't fairly correct for your residence theater setup, obtain a appearance at the QM8L's another sizes, which are additionally discounted correct now.

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Covering tech deals and reviewing TVs, headphones, speakers, and projectors.

The importance of communities around software

support@mycoding.id (Putri Silvia) — Thu, 29 Oct 2026 20:27:47 +0700

lumi's code spelunking adventures

As usual, the group are the crucial thing. Who could've guessed? :3

I've done a lot of activism for application freedom, complete the years. At archetypal it was purely for application liberty and connected topics, (such as security, autonomy and privacy) but eventually this has evolved into item additional holistic. I believe that the application I use have to be held to higher ethical standards than lone being free software.

My activism used to concentration on powerful copyleft licenses, these are licenses which require that the project remain free; that no-one can obtain the project and create it proprietary. This has taken a backseat, as I now accept that there is something more crucial than license: community. The community about a application project is what dictates the values of the project. A powerful copyleft licence does still signal that the project cares concerning application freedom, but, by itself it is not enough.

Copyright has continually been a scheme that upholds the hegemony of the powerful, it enriches corporations at the disbursal of the operating class. Copyleft licenses do use copyright against them, but can lone do so much. We are using an abusive system against itself, which is not sustainable or desirable in the lengthy term.

Software being liberated additionally states nothing concerning another ethical values of the project, such as whether it is inclusive and whether it is run by its own community, or by a corporation. It additionally states nothing concerning whether the project endorses extractive technologies specified as generative models.

As an example of a project which is technically liberated software, but does not value software liberty at all, regard an AGPL-3.0 project that is dual-licensed under a business licence and forces a contributor licence accord on its contributors. This project is not community-run at all and is lone liberated application in a narrow sense of the word.

This is why I don't attention as much anymore concerning a project being under a copyleft free application licence or a non-copyleft liberated application license. It is motionless true that the application being accessible under a powerful copyleft licence sends a signal that the project cares concerning application freedom, but it is not a guarantee.

So, if the licence is not the (only) item we need to appearance at, what do we also need to appearance at? This depends on your own priorities, of course, but there are a few things I could mention:

Does the project have an inclusive code of conduct?
Does the code of behavior or contribution guideline ban generative models?
Is the project entirely in the hands of a corporation?
Is there a contributor licence agreement?
Does it endorse proprietary and/or centralized platforms specified as Discord and GitHub?
What are the values of the guide developers of the project? Do they attention concerning ethics in software?

Try to associate the communities of liberated application projects you use and attention about, eventually perchance equal try to contribute. Even if you can't code, there are many other tasks that need to be done: community management, documentation, artwork, triage, outreach, and many another tasks. In the end, it's the community about a project that shapes its values, so be a part of that community and shove against anything unethical. Speak up, if you can. For all individual speaking up, there will be many that can't or won't conversation up; be their voice.

Getting together to build application is important. Like stated before, this can mean joining an existing project, but it can additionally average creating a new one. It can additionally average joining or creating a application cooperative. These are communities of group that create application together. One community can extend multiple projects and we can all assistance one-another out. Examples contain The Starlight Network and Polyphony.

Meow. :333

Show HN: Auto Dismiss Mac OS "Allow to find devices on local networks?"

support@mycoding.id (Putri Silvia) — Thu, 29 Oct 2026 20:27:44 +0700

Auto-dismisses the macOS prompt:

Allow "Google Chrome" to discover devices on local networks? This volition authorize the app to discover, nexus to, and collect data from devices on your networks.

It presses Don't Allow for you, inside a fraction of a second, all time. Zero CPU during idle. Survives reboots. One Swift file, no dependencies.

macOS (Sequoia and later) shows this immediate the archetypal period an app touches the local network. The decision is expected to be remembered. For many apps it isn't, so the immediate comes rear on all launch, frequently for apps you aren't equal using:

Chromium browsers (Chrome, Brave, Edge, Island, Arc) copy their own app bundle into a random temp directory at initiate so the code signature survives in-place updates. macOS keys the Local Network decision to that random path, so the next initiate looks akin a brand-new app. Your Privacy settings inhabit up alongside copy "Google Chrome.app" rows that no longer item at anything.
Apps alongside versioned instal paths (anything that installs into .../versions/1.2.3/) get a new row per update.
Misattributed prompts. macOS pins the dialog on whichever app it decides is "responsible", so you'll see prompts for apps that aren't running.
Nothing on a representative Mac needs this approval apart from a printer or scanner utility, a media server, or a LAN-discovery tool, and those you answer formerly and they're done.

There is no supported way to prune the list, no MDM payload to pre-deny the permission, and tccutil reset doesn't shield it. So: a small delegate that answers "no" for you.

brew instal johncassil/tap/dontallow # or: create && create install dontallow install

dontallow instal writes a per-user launchd agent, starts it, opens System Settings > Privacy & Security > Accessibility, and prints the exact way to add if macOS doesn't immediate you. Accessibility is the approval that lets it media the button. It waits for the aid and confirms whenever the delegate is active. dontallow position repeats the instructions any period the aid is missing.

Command	What it does
dontallow status	Agent state, intermission state, allowlist, latest dismissals
dontallow intermission [1h]	Leave prompts solitary for a during (30m, 2h, 1d, forever)
dontallow resume	Dismiss again
dontallow rules	Decode the system's Local Network regulation shop and display what all Privacy row really is, including orphans
dontallow uninstall	Stop and eliminate the agent
dontallow run --dry-run	Foreground, log what it would do, media nothing

Each dismissal posts a notification naming the app and the intermission command, so you never have to recall how to rotate it off. Mute the notification in System Settings if you'd fairly not see it.

When an app really does need local network access

Three options, choice whichever fits:

dontallow intermission 10m, afterward initiate the app and click Allow yourself.
Add the app's name to ~/.config/dontallow/allowlist (one per line, case-insensitive substring). Prompts for it are never touched.
Flip the toggle in System Settings > Privacy & Security > Local Network. A dismissed immediate records a deny, which you can reverse there.

Set ~/.config/dontallow/grace to a figure of seconds if you desire a opening to click Allow before the delegate does (default 0.25).

The immediate is a opening owned by the scheme procedure UserNotificationCenter. dontallow registers an Accessibility observer for opening innovation on that procedure and sleeps until one fires. It says the dialog text, confirms it's a local network immediate and not item else, checks intermission and allowlist, and performs the Accessibility media act on the Don't Allow button. If the media is refused it falls rear to a synthetic click at the button's location.

It never modifies scheme files, never disables protections, and never chooses Allow.

Local Network cannot be pre-set by MDM, but Accessibility can. For a fleet: build once, sign alongside a Developer ID, container the binary affirmative a PPPC (Privacy Preferences Policy Control) overview granting Accessibility to its code requirement, and run dontallow instal per user. No manual Settings step.

macOS keys the Accessibility aid to the binary's code signature, and all build (including beer upgrade) produces a new one. After an upgrade run dontallow status. If it says the aid is missing, eliminate the dontallow row in Accessibility settings and add it rear from the way it prints. The delegate re-attaches on its own inside ten seconds. A forthcoming publish signed alongside a Developer ID volition eliminate this step.

Unit tests shield the clean logic (dialog content parsing, duration and intermission parsing, allowlist matching, launchd plist generation, and the Local Network regulation decoder against a fixture archive). They build alongside plain swiftc and need no Xcode or SwiftPM. The end-to-end way (a genuine prompt, a genuine press) can lone be checked on a Mac alongside Accessibility granted; the manual formula is in Tests/INTEGRATION.md.

Builds alongside Apple's Command Line Tools alone. Xcode is not required.
Apple Silicon and Intel: Homebrew compiles natively on each.
macOS 13 or afterward to build; the immediate itself lone exists on macOS 15 Sequoia and later.
Tested so far: Intel, macOS 26.6. Reports from another versions welcome.
English-localized macOS lone for now. The matcher keys on the dialog content and the "Don't Allow" clasp title; localized strings are planned.

MIT

IgE disruptor for food allergy with Claude-enabled antibody design [pdf]

support@mycoding.id (Putri Silvia) — Thu, 29 Oct 2026 20:25:48 +0700

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GM to pay $220 million to resolve claims it sold driving habits data

support@mycoding.id (Emma Roth) — Thu, 29 Oct 2026 20:19:28 +0700

Emma Roth

is a news author who covers the streaming wars, person tech, crypto, social media, and much more. Previously, she was a author and publishing company at MUO.

General Motors has accepted to pay $220 myriad to resolve claims that it illegally sold controller and location data to data brokers, as reported before by Reuters. The agreement, which resolves a grievance from a alliance of 36 US attorneys general, requires GM to bounds the driving data it collects and get “express consent” from drivers before collecting their information.

The allegations encircle GM’s now-discontinued Smart Driver program, which collected data concerning driving habits, including acceleration, braking, and trip length. GM allegedly passed this data to data brokers, enabling coverage companies to purchase the data and lift premiums. The states additionally accused GM of failing to notify drivers that they were enrolled in its Smart Driver program, and that the carmaker was collecting their data.

This colony comes fair months following GM accepted to pay $12.75 myriad to resolve similar claims in California. Oregon AG Dan Rayfield and Washington AG Nick Brown co-led the states’ case against GM, which additionally included New York, Florida, Michigan, Nevada, Pennsylvania, and many others.

“People bought a car, not a tracking device,” Rayfield says in a media release. “GM told drivers this program would assistance them run additional safely and promised it wouldn’t portion their data alongside insurers without permission. Our inquiry established GM sold that data anyway, and several drivers paid for it alongside higher premiums.”

Follow topics and authors from this narrative to see additional akin this in your personalized homepage nourish and to obtain email updates.

Emma Roth

Accurate Facts Can Still Produce A False AI Answer, And Courts Are Starting To Hold The Platform Responsible

support@mycoding.id (Duane Forrester) — Thu, 29 Oct 2026 20:00:31 +0700

A German court has held Google liable for an AI answer assembled from true facts since those facts belonged to a distinct man.

In a decision dated Sept. 24, 2026, the Regional Court of Aachen ordered Google to halt spreading three versions of an AI Mode answer concerning a local doctor. He had served as chief doctor and prof of neuroradiology until delayed June. When group searched for why he left, AI Mode supplied a grave offender allegation, and whenever they followed up alongside conditions akin suspension, termination, and court proceedings, it produced multi-paragraph accounts of a lawful aftermath. The proceedings were real. They engaged a distinct man, additionally a erstwhile university professor, and the court could verify the mix-up from its own records.

The doctor sent Google a detailed clarification in delayed August. In mid-September, Google stated it would obtain no action, and a ceremonial lawful petition sent the identical day went nowhere. The court afterward acted on an emergency basis without archetypal hearing from Google, alongside fines of up to 250,000 euros per violation. Google can motionless difficulty the order.

The outcome matters small than the reasoning. The court in Aachen relied on an before ruling from the Regional Court of Munich, which in May held Google immediately liable for AI Overviews that tied two publishers to fraud and subscription traps using claims that appeared in none of the connected sources. Google asserted that users could inspect those sources themselves. The Munich court rejected that, finding that the overview peruse as a self-contained statement, and described what Google’s AI produces as “independent, new, and substantive statements” built by combining satisfied from third-party sites. Aachen adopted that tongue directly. Google announced an appeal of the Munich ruling and then, according to The Decoder’s reporting, settled before any higher court weighed in.

Courts in Munich and Aachen have now treated AI hunt answers as the platform’s own statements, and those statements can be false equal whenever all fact inner them is true. I wrote before this twelvemonth concerning the liability exterior moving from the results leaf to the answer. These two cases are what that change looks akin formerly it reaches a courtroom.

A Berlin Court Sees It Differently, And Nobody Has Settled It Yet

In first June, a Berlin court reached the contrary perspective in a trademark dispute. A perfume business objected to AI Overviews that named its brands next to links marketing cheaper imitations. The Berlin court treated AI Overviews as a new format of hunt outcome that bundles data from another sites, not as Google speaking for itself, and established no infringement.

The cases don’t row up neatly. Berlin’s AI summary accurately repeated what another sites said, during the Munich and Aachen answers invented connections that no origin made. Even so, courts in the identical nation have described the identical merchandise in incompatible terms, and no higher court has ruled, since the one case headed there settled.

That’s the landscape for anyone operating in hunt correct now, equal if this is from a distinct country. The rules governing the exterior that answers a expanding portion of your customers’ questions are unsettled; they differ by jurisdiction and equal by courtroom, and the hazard falls on whoever assumed they were settled. Waiting for clarity isn’t an option, since your brand is already appearing in these answers.

How A True Fact Ends Up Attached To The Wrong Name

The scheme is small exotic than the outcome. A scheme answering a inquiry concerning a named individual or business retrieves documents that equivalent on the name and on surrounding attributes specified as role, institution, city, industry, or a latest event. It afterward generates one fluent narrative from any it retrieved. When two entities portion adequate attributes, the scheme has no dependable way to cognize it is holding facts concerning two distinct subjects, and the generated answer fuses them. I call this entity conflation, definition the scheme merges two distinct group or companies into one and afterward speaks concerning the merged outcome alongside complete confidence.

The form repeats throughout the cases on record. In Aachen, two men shared the attributes of university prof and departure from a post. In Munich, the AI blended the publishers alongside genuinely dubious companies that, according to sworn statements, had no association to them. In 2024, Microsoft’s Copilot described a German court reporter as the perpetrator of crimes he had spent years covering, since his name sat beside those crimes in his own bylines. The platforms and years differ, and the nonaccomplishment is the same.

The visibility isn’t constricted to group alongside offender records nearby. Any being that shares a name or a collection of attributes alongside another is a candidate: two companies alongside akin names in the identical industry, a franchise location confused alongside the brand, an administrator who shares a name alongside person alternatively in the identical field, a merchandise row whose name overlaps a competitor’s. Most businesses have never checked which neighbors they are easiest to confuse with, since in a catalog of links the audience did that sorting.

What follows is my own read, an opinion and not item the court found. The Aachen answer was responding to a inquiry the doctor’s community document remaining open, which was why he left. In my view, an unexplained event in an entity’s community document plant akin an invitation: the scheme is asked for an explanation, it reaches for the nearest plausible one, and if the closest equivalent belongs to person else, that’s what it uses. I can’t display that this is what happened inner AI Mode. I recommendation it as a way of thinking concerning risk, and I accept an unexplained gap in an entity’s community document is anywhere conflation most effortlessly gets in.

Where I Think The Platforms Go Next

This division is my opinion and ideas, not reporting. I’ll province the conjecture plainly here, and in the next division I’ll lay out what would demonstrate it wrong.

If courts keep treating AI answers as the platform’s own statements, all generated answer concerning a named being becomes a possible liability. Disclaimers solitary won’t fix that, since Munich already rejected the disagreement that users can verify for themselves. Pointing to the origin links won’t fix it either, since nearly nobody uses them. Pew Research found that users clicked a nexus inner the AI summary on fair 1% of searches anywhere one appeared, and clicked any traditional outcome on 8% of those searches compared alongside 15% whenever no summary appeared. People peruse the answer, which is exactly why courts treat it as the platform’s speech.

So I anticipate platforms to tighten the pond of sources they rely whenever answering concerning particular group and companies. I anticipate heavier weighting toward facts that are accordant throughout autonomous sources, additional reliance on structured and disambiguated being data, and additional hedging or outright declining whenever a scheme can’t inform which being a query refers to. The Aachen court stated Google could inspect its output by comparing it alongside the origin sites, and that putting the doctor’s objections to its own AI would have exposed the error. A verification stage akin that expenses compute and period on all answer, so I anticipate platforms to use it selectively at first, starting alongside the query types most apt to end up in forefront of a judge.

I additionally don’t anticipate the consequence to remain in Germany. Platforms rarely keep a distinct answer pipeline for all court that rules against them, and source-weighting changes made for one market lean to container additional broadly since maintaining divergent systems is expensive. The identical logic applies to all business generating answers concerning named entities, not lone Google, since the Munich reasoning rests on how the merchandise plant fairly than on who built it.

For businesses, the consequence is that being retrievable stops being enough, and being unambiguous becomes the standard. A business whose facts battle throughout its own site, its profiles, and third-party coverage, or whose name and attributes overlap alongside a neighbor’s, is exactly the benevolent of being a careful scheme either hedges on or gets wrong.

What Would Make Me Wrong

Several developments would undercut this forecast, so let’s analyze them.

The archetypal is higher courts siding alongside Berlin. If an appeals court, or ultimately Germany’s Federal Court of Justice, treats AI answers as hunt results whose controller becomes liable lone following being notified, the force rearward my prediction weakens considerably.

The second is that precedent never forms. Binding law arrives lone whenever person takes a case all the way through. If Google keeps settling, liability stays a manageable disbursal fairly than a scheme constraint, and platforms have small logic to alter how they importance sources.

The third is regulation going the another way. Lawmakers in the EU or the U.S. could location AI answers under the identical protections that shield intermediaries passing alongside another people’s content. In the US, no court has squarely decided whether Section 230 covers content a example writes, and practitioners anticipate courts to obtain that inquiry up soon. A broad study in the platforms’ favor would eliminate most of the American pressure.

The fourth is that platforms resolve conflation inner the model. Better verification and self-consistency checks could capture merged entities before an answer ships, leaving origin weighting mostly untouched and keeping the burden off businesses.

The fifth is that platforms suppress fairly than tighten. Instead of raising the bar for sources, they could merely halt generating answers concerning personal individuals and smaller companies, which narrows safety without changing who gets trusted.

If I had to observe one of these, it would be the colony pattern, since it’s already visible. If the next few cases resolve quietly, my timeline stretches considerably.

Make Your Entity Hard To Confuse With Anyone Else

None of those developments makes the protective activity a waste. Even under the outcome most favorable to platforms, a merged being is motionless a endeavor problem, alongside eroded trust, misdirected customers, and a correction procedure that, as Aachen showed, can stall for weeks. The activity starts alongside knowing what these systems currently say concerning you, checked on a agenda fairly than following a coworker happens to notice. Measuring that is what I built CitationIQ to do, so measure my accent accordingly; any tool you use, the item is to detect before item breaks.

From there, the activity looks small akin traditional position administration and additional akin character hygiene. You aren’t trying to inter a bad result; you are trying to create certain the scheme never has a logic to blend you alongside person else.

Query the way the Aachen answer surfaced. Search your brand, executives, and products by name blended alongside role, location, and event conditions specified as departure, lawsuit, acquisition, or closure, since conflation tends to appear in follow-up queries additional than in the archetypal one.
Publish facts that distinct you from your nearest neighbors. State founding details, leadership, locations, what you do, and what you don’t do on pages you control, in plain sentences a scheme can citation accurately.
Make your character machine-readable. Schema.org Organization and Person markup alongside sameAs links to your authoritative profiles, affirmative accordant naming everywhere, gives a scheme an anchor that a name solitary cannot.
Close the gaps yourself. When item matter changes, specified as a guidance departure, a rebrand, or a location closing, publish your own document so the scheme has an clarification that really belongs to you.
Validate before you publish. Your pages are now raw matter for person else’s sentences, so an error on your own location travels additional than it used to, and the claims you create concerning yourself deserve a second check.
Document everything whenever item goes wrong. Keep the exact query, the complete answer text, the date and time, the surface, the cited sources, your correction request, and the platform’s reply, since the two German cases turned on documented requests that went unanswered.

Unique, verified, first-party facts used to function chiefly as a norm signal. In a scheme that answers in its own voice, they activity nearer to character protection. The safest being in AI hunt is the one that’s hardest to error for another.

More Resources:

This article was initially published on Duane Forrester Decodes.

Featured Image: Roman Samborskyi/Shutterstock

Category AI Search

This chart shows how much Google's head count surged in the AI boom

support@mycoding.id (Hugh Langley,Andy Kiersz) — Thu, 29 Oct 2026 19:56:31 +0700

Sundar Pichai, chief administrator of Alphabet Inc., during an discussion on "The Circuit alongside Emily Chang" on May 1, 2024. David Paul Morris/Bloomberg via Getty Images

While AI may be driving several companies to slash their caput count, Google's is soaring.

When Google reported its Q3 earnings on Wednesday, it stated it had 204,757 workforce for the fourth ending September 2026. That method Google added approximately 10,000 group to the payroll since the end of March.

The uptick in caput figure runs oppose to another trend throughout the tech industry, anywhere several of Google's peers are slashing their workforces. Meta has been on a cost-cutting odyssey for multiple years, during Microsoft lately offered voluntary buyouts to 60,000 employees.

Some of Google's caput figure growth can be attributed to mergers and acquisitions. On March 11, Google stated it had completed its acquisition of cybersecurity resolute Wiz, which had approximately 2,000 employees.

In January 2023, Google announced it would slash approximately 12,000 roles — about 6% of the workforce at the period — and has since made multiple smaller rounds of layoffs, Business Insider has reported.

While the caput figure has grown slightly steadily since Q2 2024, it has accelerated since the end of 2025. Google additionally reported Wednesday that its quarterly income grew 25% from this duration final year.

Have item to share? Contact this newsman via email at hlangley@businessinsider.com or Signal at hughlangley.01. Use a individual email location and a non-work device; here's our guide to sharing data securely.

You can generate and edit Google Docs files directly in Gemini chats now

support@mycoding.id (Stevie Bonifield) — Thu, 29 Oct 2026 19:45:31 +0700

Stevie Bonifield

is a news author covering all things person tech. Stevie started out at Laptop Mag penning news and reviews on hardware, gaming, and AI.

Now you can generate, preview, and edit PDFs, Google Docs, Google Sheets, glide decks, Markdown files, TXT files, and code directly inside Google Gemini. The new document editing capabilities are accessible starting today for all Gemini users, and during PDF previews/editing plant on the two the web and mobile, all another document formats are lone in the web type for now.

Google added assistance for generating and downloading files in Gemini before this year, but now you can tweak those records without leaving the Gemini app. Google says you can develop documents to edit them in full-screen manner and emphasize content in records to ask Gemini questions or immediate it to create changes to the file, akin highlighting a array and asking Gemini to rotate it into a graph.

You could already use Gemini to edit records alongside its integrations in Google’s Workspace apps, akin the Gemini bar in Google Docs. Anthropic additionally launched a characteristic before this twelvemonth that allows users to generate and edit documents and presentations in Claude chats.

Follow topics and authors from this narrative to see additional akin this in your personalized homepage nourish and to obtain email updates.

Stevie Bonifield

Nubank, Latin America's largest digital bank, is turning its eyes toward the US — where foreign rivals have failed

support@mycoding.id (Martina Nacach Cowan Ros) — Thu, 29 Oct 2026 19:42:50 +0700

Cristina Junqueira, the co-founder and CEO of Nubank, alongside Dan DeFrancesco, administrator publishing company and anchor of Business Insider Today. Carl Timpone/ BFA

Nubank is the largest digital financial institution in Latin America — now it's turning its eyes towards the US.

Cristina Junqueira, the co-founder and CEO of Nubank, sat downward alongside Dan DeFrancesco, administrator publishing company and anchor of Business Insider Today, at Business Insider's The Long Play, to conversation concerning the digital bank's enlargement on Thursday.

How it began

Since its founding in 2013, the fintech financial institution has pushed for financial inclusivity in Latin America by providing admission to banking and financial services through its mobile app. Headquartered in Junqueira's residence nation of Brazil, the simple, low-cost, and digital-first method abandoned the need for bodily banks, which are at times harder to attain in parts of Latin America — a key part of its achievement in the region.

It all started alongside a purple credit cardstock alongside no fees.

"We had this imagination that data, design, technology, entirely transforms people's association alongside money," she said.

Junqueira earlier worked as an administrator at Itaú Unibanco, the largest private-sector financial elephantine in the region, additionally headquartered in Brazil and now a straightforward competitor of Nubank. Today, it is the largest business in Brazil according to chief banking relationships, and two-thirds of the country's grownup community are customers, she said.

Entering the US market

The digital financial institution is set to develop into the US following beginning a branch in September, functioning under the name Nu. This comes following enlargement into Mexico and Colombia in 2021.

"We continually saw the thesis as a earth one," she said. "Everywhere in the world, group desire additional convenience. People desire additional transparency. People desire simpler experiences managing their finances. People motionless get akin paralyzed by complexity through their financial lives."

Entering America's crowded banking field is a hazard — but for Junqueira, entering no nation goes without risk.

"The US is a extremely difficult market, but I haven't established uncomplicated ones either," she said. "Building a financial institution is difficult everywhere, so you power as fine go for the biggest payout."

In the US, she stated getting a financial institution document is motionless "surprisingly hard" and normally requires you to go to a bodily branch, during Nu offers an easier substitute to that, she said. Foreign digital-first banks have tried to bring their platforms to the US before and failed. German fintech N26 and UK fintech Monzo the two tried to develop their businesses to the US, and ultimately withdrew from the market.

The American person is unique, which is why Junqueira aims to obtain a distinct method than her competitors to acquire rely and measure the platform. She stated most another companies started alongside debit cards, during Nubank is the archetypal to commencement alongside credit cards.

Starting group out alongside a debit cardstock "requires you to build a lot of rely alongside those customers since you're asking them to deposit their prosperity alongside you," she said. "In our case, all the countries that we started, we started alongside credit. This is a extremely distinct association since you're the one trusting the consumers," she said.

Some Latin American immigrants who already live in the US are responding positively to Nu as it enters the market.

"I've been positively amazed not lone by the amount of people, sure, but Brazilians, Mexicans, and others are current and have been waiting for this," she said.

Junqueira additionally pointed to emerging AI innovation and how it could effect the business and the banking sector. She stated the business is "heavily leveraging AI," integrating it in credit underwriting, client support, and merchandise development.

Brazil's presidential ballot on Sunday made headlines as President Luiz Inácio Lula da Silva unexpectedly won a runoff against Flávio Bolsonaro, who fled the nation to the US following he was under inquiry for alleged misconduct and prosperity laundering. When asked concerning how she reacted to the big market sell-off in response, Junqueira stated volatility is part of functioning in a nation akin Brazil, but having 13 years of cognition in the nation has helped them study they are going to run the business for the lengthy run.

"We got to concentration on the fundamentals, and the actuality is, final fourth we turned complete a milliard dollars in net income," she said. "Markets don't akin surprises, right? But we oversee our endeavor despite of what happens."

Building a brand

The CEO stated among the hardest things Nu volition have to do in the US is build a brand that connects alongside users on an "emotional" level. Junqueira's aspiration scenario, five years from now, is to discover evidence of that association in the US.

One of the ways Nubank is attempting to dispersed its brand is through a lately signed agreement alongside the Mercedes F1 team. Junqueira pointed to fans' enthusiasm for particular teams, as they prosecute the heading about the world, which was part of why they wanted to obtain part.

"We got a lot of visibility out of that, and we're operating alongside them on brand activations," she said. "We're producing extremely engaging activations for consumers that assistance us amplify the branding fast, and that really assistance us bring this alliance to life."

Another huge part of the digital bank's brand is sex equality. In 2021, Nubank set a goal for 50% of Nubank's guidance to be women by 2025. Junqueira stated today that the company's workforce is complete 45% women, alongside many in guidance positions. In the four countries anywhere they operate, all CEOs are women. Junqueira stated the biggest difficulty of being an administrator during raising a family is not having the elasticity to juggle the demands of the two roles.

"The actuality is, as difficult as we have to work, I think the hardest part is not having adequate flexibility," she said. "It has been fantastic for us to have that category of opportunity, for us to really be capable to access this part of the workforce that frequently struggles to have this category of occupation opportunity."

As Fundraising Gets Tougher, Tech Startups Need to Rethink Their Marketing. Here’s Where to Start.

support@mycoding.id (Tyler Jordan) — Thu, 29 Oct 2026 19:30:00 +0700

Opinions expressed by Entrepreneur contributors are their own.

Key Takeaways

Invest in human-led branding, messaging and positioning to remain out to customers and investors fairly than relying on generic AI-generated content.
Define your ideal client profile, map the client journey, and established powerful lead-management systems to maximize ROI and evade wasted ad spend.
Automate regular tasks, employ agile and AI-savvy marketers, and concentration on low-cost growth and targeted ad evaluation before investing in ample budgets or scaling efforts.

Investors have tightened up. After a extend of record-low VC returns, extremely few companies seeking chief can oversee to be in growth-at-all-costs mode.

In 2026, investors desire companies that develop consistently and efficiently without dense funding in headcount or capital. Whether you’re bootstrapped or at Series A, your promotion should assistance what’s rotate into a persistent rallying cry in the tech world: Do additional alongside less.

You need to have a tight promotion system, alongside choose levels of chief efficiency. The growth-at-all-costs era has been gone for a while; now the name of the equivalent is productive growth. Don’t expend prosperity in the first days unless you can demonstrate a affirmative ROI outcome.

The key, which I’ll enter in this article, is construction a differentiated brand. Telling a fine and compelling narrative through your brand volition do additional for your growth (and your fundraising) than leveraging AI fine and/or acquiring a myriad leads alongside Meta ads.

What to allocate in now

1. Brand, messaging and positioning (developed by people)

In my opinion, this is your first funding alongside the highest value. Hire person who can inform your narrative through branding, messaging and positioning, afterward translate it into a distinctive scheme language.

I can’t say this plainly enough: Do not hand this activity to AI tools.

Companies that do lean to end up alongside bland, homogeneous websites and positioning statements that appearance akin any another startup’s. In a crowded market, a differentiated narrative is what makes you memorable to customers and investors.

Even if you’re blessed adequate alongside your messaging from your business’s first days, this is value revisiting in a lot of degree — and alongside a lot of investigation — to create certain you have a narrative value investing in.

2. A plainly defined ICP and mapped client journey

Do the investigation to create a rich, layered understanding of who you are, who you serve and why they care. Then map the client journey and decide how you’ll assistance prospects through all stage. This, akin the above, may commencement out fairly essential but morph complete time, particularly if you’re adding functionality as you go.

Make certain you’ve done your activity current before engaging any possible investors; you need to have your TAM (Total Addressable Market) and your client journey, whether that’s product-led or sales-led, nailed down.

3. Lead-management plumbing

Before you measure your efforts in petition generation and petition capture, measure the maturity of your systems for tracking, measuring and nurturing leads. Too many companies throw prosperity at ads to get leads in the entrance without promotion ops or revenue ops (let solitary unified income ops) systems in place.

When my agency onboards brands in that position, we invariably see thousands and thousands of dollars of ad expend wasted on old and/or unqualified leads that never change into pipeline. Worse, they don’t use the data on qualified leads to train Google, Meta and LinkedIn’s bidding algorithms to discover additional precious users for their ad spend.

4. AI automation for chief efficiency

Identify the processes you can (and should) automate alongside AI, and activate them quickly. A applicable example is an orchestrator delegate framework: one individual or delegate coordinating automated workflows throughout functions.

In 2026, there is no longer any excuse for dilatory guide follow-up, dilatory responses for essential client assistance questions or poorly updated CRM details. Find uncomplicated tasks that AI can obtain complete anywhere it makes sense.

Also acknowledge that there is a brand hazard in forcing group to converse at dimension alongside an AI agent, so use AI wisely (e.g., leverage it for simplifying workflows), but bounds client visibility.

5. The correct archetypal promotion hire

If you need person to rotate up their sleeves and do the work, don’t employ an costly CMO. Make your archetypal employ a starving director or VP-level generalist alongside AI fluency. The ideal person is person who knows the new tools, acts quickly and autonomously, and doesn’t delay to execute.

If you’re at the item anywhere you need a bigger team, I’ve seen two models work. The archetypal example is a small collection of elder group who build AI delegate workflows (with constricted younger hiring); the second example is additional capital-efficient mid-level hires who can build several automation and grip execution.

Where to preserve your prosperity (for now)

Limit paid media expend in the first days. If you run ads, use them for conduit and communication testing, and constricted testing, not spending for scale. A few thousand dollars spent evaluation value propositions (ease of implementation versus price, for example) volition display which messages resonate, which is crucial info for revenue to have as well.

Don’t prosecute scale

The old regulation motionless holds: Do the things that don’t measure first, akin operating your networks to get leads and customers in the door. Save scalable paid strategies until you have the prosperity and the evidence to assistance them — not to citation the post-lead set-up I talked concerning above.

Final thoughts

AI has brought another tier of definition to “do additional alongside less.” These days, that frequently method “with small people,” alongside leaders using AI for functions squad members formerly tackled.

Strategic use of AI is an crucial part of achieving the effectiveness that appeals to investors in 2026, but fair as crucial is knowing whenever awesome individual endowment is needed. Your brand is motionless your most crucial asset; without a distinctive brand and a persuasive story, all the automation and ad expend in the earth won’t guide you to your fundraising goals.

Barry Diller shares why his deal to buy MGM fell apart

support@mycoding.id (Dan Whateley) — Thu, 29 Oct 2026 19:29:52 +0700

Barry Diller told Business Insider's Peter Kafka that "forever assets" akin MGM and its Las Vegas resorts are protected from AI disruption. Carl Timpone/ BFA

Media mogul Barry Diller thinks businesses that run in the genuine earth have a powerful protective moat against AI.

That was the inspiration for his business People Inc.'s June bid for MGM Resorts International's casino and inn business, which he called "forever assets."

As several consumers rotate to AI chatbots to complete tasks akin purchasing aircraft tickets or managing subscriptions, digital-only businesses could get boxed out. That creates genuine risks for net brands akin Expedia Inc., anywhere Diller is an capitalist and commission member. It's small of a issue for companies whose businesses be in the genuine world, he said.

Nothing is going to substitute Las Vegas, Diller stated — and no one's going to buy another one. Gaming is lone part of the equation, he said.

"No disintermediation is coming between a individual who wants to go to a place, and that place," he said, speaking to BI's Chief Correspondent Peter Kafka at Business Insider's The Long Play event in New York on Thursday.

People Inc. archetypal took a 27% interest in MGM in 2020. The company, which operates magazines specified as Food & Wine, People, and Southern Living, afterward offered to buy the Las Vegas brand outright in June but withdrew its bid in September.

Diller stated the agreement cut distinct following he became uncomfortable alongside the projected structure, which engaged taking on debt and asking third parties for money.

MGM afterward offered to buy People Inc. instead, but told investors on Wednesday that it had shelved the plan. Diller stated it was "highly unlikely" that MGM was curious in People's mag assets, but fairly it had hoped to buy rear People's MGM shares.

People remains MGM's largest investor, although it has accepted not to buy additional than a 29.9% interest in the business and to ballot alongside MGM's commission in association alongside a change-of-control transaction.

Barry Diller says AI isn't going to get between person who wants to go to Las Vegas and the retreat town. Carl Timpone/ BFA

People, which, beyond its mag portfolio, additionally owns stakes in The Daily Beast and the car-rental business Turo, laid off 195 workers on Thursday, per a memo from CEO Neil Vogel, which Business Insider viewed. The huge bulk of whom activity on its "print and bequest web businesses," the memo said. The business has "added 320 new workforce so far in 2026," it said.

Diller told Kafka that the layoffs were a sign of a fit business that has a profitable imprint endeavor in a "steady benevolent of decline."

"We've been transferring out group in these bequest businesses and transferring in group to do the new work," he said.

Diller is a longtime media operator. He served as chairman and CEO of Paramount Pictures in the 1970s and 80s, before joining Fox Inc. and assisting to commencement Fox Broadcasting alongside Rupert Murdoch in the mid-1980s. He afterward worked at QVC before serving as CEO of IAC and taking on roles at Expedia Group. He is on the commission of board at MGM.

Instagram is trying to woo YouTube creators with six-figure checks

support@mycoding.id (Sydney Bradley,Lucia Moses) — Thu, 29 Oct 2026 19:25:36 +0700

Adam Mosseri is the caput of Instagram at Meta. Kyle Grillot/Bloomberg via Getty Images

Instagram wants what YouTube has — and it's consenting to pay up to get it.

In an attempt to convince satisfied creators to article long-form video on Instagram, the business is paying a choose figure of creators hefty sums, according to group acquainted alongside the deals.

Not all agreement is equal. The Meta-owned phase has offered choose creators $50,000 to article long-form video to its new "Features" product, during others have been offered six-figure deals, several of which have reached $500,000, Business Insider exclusively learned.

"We've been community concerning the fact that we are backing Features satisfied immediately alongside several creators correct now to assistance them," a Meta spokesman told Business Insider. "The particulars of those deals are confidential, but we're enthusiastic to see the satisfied going live."

On Monday, Instagram unveiled an overhaul of its video formats. Most importantly, it's resurrecting IGTV — a long-form video merchandise Instagram launched in 2018 and sunset in 2022 — in the form of Features. The horizontal, wide-screen videos volition be inside the Instagram app, and can be as lengthy as a characteristic film: 90 minutes.

Instagram is expanding its offerings for long-form video content. Meta

Long-form video isn't exactly what group are used to observing on Instagram. Reels, the platform's answer to TikTok's meteoric rise, has redefined the Instagram cognition and is driving time-spent and income throughout Meta's apps.

YouTube, however, reigns king as the internet's destination for sit-down, longer-form videos.

Instagram knows this. The deals do not necessitate exclusivity to Instagram, multiple group acquainted alongside the agreements said; one individual acquainted alongside the offers stated it's asking creators to article to Instagram any of the long-form satisfied they publish to YouTube that identical day.

Reza Izad, partner at Underscore Talent, whose clients contain "Subway Takes'" Kareem Rahma and Noah Beck, called the deals an "exciting opportunity" for creators.

"Every period there's a new characteristic in these apps that the company's promoting, group volition have additional chance to be seen since there's going to be algorithmic penchant to this benevolent of content," he said. "And dissimilar short-form, there's not a lot of abundance."

Money, money, money

This isn't the archetypal period Instagram has inked paid deals alongside creators to lure them to article additional on Meta's apps.

Last year, Meta was paying creators thousands of dollars to article short-form videos to Instagram and Facebook in the midst of TikTok's possible ban. The business has tested multiple reward programs paying creators for the achievement of their Reels on Instagram, although those programs have dwindled.

Back in 2021, whenever IGTV was motionless part of Instagram's big video bet, it inked deals alongside creators, funding long-form episodic shows from creators akin TikTok's "Sway Boys" and "Dance Moms" alum Nia Sioux. Briefly, IGTV had its own monetization program, too, which let several creators acquire a cut from ad income on the format.

While Instagram is paying several creators directly, a big inquiry looms complete the creator economy: What concerning the remainder of them?

A important diagram of YouTube is its long-standing Partner Program, which pays eligible creators a portion of the ad income generated by their videos. Even although YouTube has risen its eligibility requirements, the possible to rotate a hobby or enthusiasm project into a cash-earning occupation has kept YouTube on top as the go-to video phase for creators.

It's no surprise, then, that whenever Instagram announced its video overhaul, creators immediately had questions concerning monetization.

"We comprehend the economics matter a ton, and are exploring multiple options to assistance long-form creators get paid," Instagram's top executive, Adam Mosseri, wrote in an X article on Wednesday.

Have a tip?

Contact Lucia via email at lmoses@businessinsider.com, (917) 209-8549, or on Signal at @luciamoses.81.

Contact Sydney via encrypted messaging app Signal at @sydneykbradley.123, sydneykbradley@proton.me, or sbradley@businessinsider.com.

Use a individual email address, a nonwork WiFi network, and a nonwork device; here's our guide to sharing data securely.

17 photos that show how Kelly Clarkson's style has changed since her 'American Idol' days

support@mycoding.id (Amanda Krause) — Thu, 29 Oct 2026 19:20:19 +0700

Kelly Clarkson in 2005 (left) and in 2024 (right). J. Merritt/Kevin Mazur/Getty Images

Kelly Clarkson is a national icon.

After winning "American Idol" in 2002, she's remained a family name through her music, children's books, and TV roles. She was additionally engaged in community perform this twelvemonth whenever she started feuding alongside a Brooklyn toy store.

No matter the occasion, though, Clarkson has stood out onstage and throughout red carpets alongside her ever-evolving style.

Here's a appearance at how her manner has changed complete the years.

Kelly Clarkson was the supreme female next entrance whenever she became a family name in 2002.

Kelly Clarkson attends the 2002 premiere of "Swimfan" in Westwood, California. Robert Mora/Getty Images

After winning "American Idol," she wore one of her most memorable looks to date at the "Swimfan" premiere.

It included a strapless tie-dye attire complete bootcut jeans and phase sandals. Clarkson additionally sported a declaration pendant and a red newsboy cap.

She embraced small dreary dresses throughout 2003.

Kelly Clarkson attends the 2003 Billboard Music Awards in Las Vegas, Nevada. Carlo Allegri/Getty Images

Clarkson wore assorted versions of the manner staple that year, including at the Billboard Music Awards.

Her strapless attire that night had a knee-length skirt, a bustier bodice, and all-over ruching. She wore it alongside pointed pumps and lengthy gem earrings.

And she showed her feminine flank in 2004.

Kelly Clarkson attends the 2004 American Music Awards in Los Angeles, California. Jon Kopaloff/Getty Images

At the 2004 American Music Awards, Clarkson walked the red carpet wearing a floor-length gown alongside satin detailing.

She accessorized the red ensemble alongside aureate sandals and matching earrings, and completed the appearance alongside an updo hairstyle.

The next twelvemonth was defined by punk-rock outfits.

Kelly Clarkson attends the 2005 KIIS-FM Wango Tango in Los Angeles, California. J. Merritt/Getty Images

For most of her performances in 2005, Clarkson appeared onstage in torn collection T-shirts, low-rise jeans, and either sandals or sneakers.

She wore a type of that exact outfit — a Rolling Stones top, low-rise pants, and a studded strap — to execute at the 2005 Wango Tango concert.

She blended her edgy and glamorous styles in 2006.

Kelly Clarkson attends the 2006 Grammy Awards in Los Angeles, California. Gregg DeGuire/Getty Images

For the 2006 Grammy Awards, Clarkson stunned in a dreary Max Azria gown.

The strapless part had a form-fitting bodice and full, ruffled skirt, which added distinctive texture and mirrored the wavy manner of her hair.

Normally a fan of gowns, Clarkson began experimenting alongside minidresses in 2007.

Kelly Clarkson attends the 2007 ASCAP Pop Music Awards in Los Angeles, California. Jeffrey Mayer/Getty Images

She attended the ASCAP Pop Music Awards that twelvemonth in an olive-toned change attire alongside a beaded neckline and bubble skirt.

Clarkson additionally debuted a new bob hairstyle that night and accessorized alongside a argent bracelet and sandals.

The musician sparkled throughout 2009 and the first 2010s.

Kelly Clarkson attends the 2009 American Music Awards in Los Angeles, California. Frazer Harrison/Getty Images

At the 2009 American Music Awards, Clarkson walked the red carpet in a sleeveless CD Greene design.

The knee-length attire had clusters of argent sequins at the top and additional embellishments cascading downward its bodice and skirt.

She wore the garment alongside fishnet tights, dreary pumps, and a crimped red hairstyle.

Clarkson returned to her rock roots in 2012.

Kelly Clarkson performs a 2012 display in Birmingham, United Kingdom. Steve Thorne/Getty Images

At concerts that year, Clarkson performed during wearing collection T-shirts and skinny jeans.

For a display in Birmingham, for example, she hit the phase in dreary denim, a ripped UFO achievement tee, and a sparkling vest.

She wore a ton of red throughout 2013.

Kelly Clarkson visits the SiriusXM Studios in New York City. Taylor Hill/Getty Images

Clarkson particularly seemed to favor the color during promoting her Christmas gathering "Wrapped in Red."

She wore it during a sojourn to the SiriusXM Studios via a plaid attire alongside zipper detailing, a cropped sweater, and studded sandal heels.

By 2015, Clarkson's manner was complete of bold prints.

Kelly Clarkson visits the SiriusXM Studios in New York City. Cindy Ord/Getty Images

During another sojourn to the SiriusXM Studios, she wore a music-inspired outfit that included a knee-length skirt printed alongside images of vinyl records.

She additionally wore aureate sandals and a yellow T-shirt that stated New York City.

Clarkson opted for chic looks in 2016.

Kelly Clarkson makes a 2016 appearance on "Extra" in New York City. Dia Dipasupil/Getty Images

Her office-ready manner included dreary minidresses, sheer tights, and pointed pumps — fair akin she wore to appear on "Extra" that year.

Clarkson was additionally sporting blonde tress in free waves at that point.

By 2019, Clarkson was having additional fun alongside her red-carpet outfits.

Kelly Clarkson attends the 2019 "UglyDolls" premiere in Los Angeles, California. Steve Granitz/Getty Images

At the "UglyDolls" premiere, Clarkson walked the orange carpet in a hot-pink gown designed by Christian Siriano. It had a floor-length skirt alongside a abbreviated train and giant, puffy sleeves.

The outfit was apt inspired by Moxy, the pink "UglyDolls" character that Clarkson voiced for the film.

In the 2020s, Clarkson has apparently established her signature style: a mix of glamour and rock 'n' roll.

Kelly Clarkson attends the 2020 Billboard Music Awards in Los Angeles, California. Amy Sussman/Getty Images

She attended the 2020 Billboard Music Awards in an outfit that absolutely embodied that style.

Balmain designed her argent gown, which had ample high arm pads and fringe hanging from its skirt and sleeves.

She's not fearful to test alongside daring looks.

Kelly Clarkson performs at the 2023 iHeartRadio Music Festival in Las Vegas, Nevada. Rich Polk/Stringer/Getty Images

In 2023, Clarkson performed in a sequence of bold outfits — including the lace jumpsuit she sported at the iHeartRadio Music Festival.

She wore the see-through garment under a blazer styled as a dress, and thigh-high leather boots.

Minidresses and metallics have rotate into signature parts of her wardrobe.

Kelly Clarkson at the 2024 Rock & Roll Hall of Fame induction. Kevin Mazur/Getty Images

Clarkson attended the 2024 Rock & Roll Hall of Fame induction ritual in a Rebecca Vallance minidress.

The long-sleeve part was dreary alongside a sheer waist panel and metal sequin embellishments all over.

She wore it alongside dreary sandal heels and her new wavy hairstyle alongside bangs.

So have glamorous gowns.

Kelly Clarkson performs at her Las Vegas residency in 2025. Denise Truscello/Getty Images

When Clarkson performed her Las Vegas residency in 2025, she wore a tan gown covered in sparkles and feathers.

It hugged her build from her shoulders to her knees, anywhere the gown was made of mesh and embellished alongside argent sequins.

Its sleeves and skirt were additional dramatic. They puffed out and were covered in rows of feathers, which added texture and form to the look.

Today, Clarkson's manner is uncomplicated but elevated.

Kelly Clarkson performs on "The Kelly Clarkson Show" in 2026. Weiss Eubanks/Getty Images

Before "The Kelly Clarkson Show" ended in August 2026, Clarkson appeared in a multitude of chic outfits.

One of them was a sheer dreary gown alongside a plaid pattern. It revealed the bralette and miniskirt she wore below the floor-length piece.

She completed the outfit alongside neutral composition and a wavy hairstyle.

Show HN: phpClaw – AI agent runtime for PHP with tools, memory and guards

support@mycoding.id (Doris Putra) — Thu, 29 Oct 2026 19:06:22 +0700

Tools, memory, security, and a ReAct loop, already built. Zero example requirements in core. Any LLM provider.

Documentation · Adapters · Why phpClaw · Install · MCP · Security

composer necessitate phpclaw/phpclaw export ANTHROPIC_API_KEY="sk-ant-..."

$agent = PhpClaw\Claw::builder()->build(); echo $agent->send('What can you assistance me with?')->text;

One env var, one builder, one send(). The builder checks ANTHROPIC_API_KEY, afterward OPENAI_API_KEY, GROQ_API_KEY, GEMINI_API_KEY, MISTRAL_API_KEY, DEEPSEEK_API_KEY, OLLAMA_HOST, in that order, and uses whichever it finds first. No YAML, no delegate example to learn, no vendor lock-in.

An delegate without tools can lone talk. Register the ones your use needs and it starts doing genuine work:

use PhpClaw\Claw; use PhpClaw\Tools\ShellTool; use PhpClaw\Tools\HttpTool; use PhpClaw\Tools\FileReadTool; use PhpClaw\Tools\DatabaseQueryTool; use PhpClaw\Tools\CodeSearchTool; $agent = Claw::builder() ->tools([ new ShellTool(allowlist: ['ls', 'df', 'tail']), new HttpTool(), new FileReadTool(), new DatabaseQueryTool($pdo), new CodeSearchTool(), ]) ->build();

> Check disk use and rear the final 20 lines of the error log > Is api.example.com responding correct now? > Run a read-only SELECT to figure today's orders > Find all location UserService is used in this codebase

The delegate decides which tools to call and in what order, operating a ReAct iteration (reason, act, observe, repeat) until it has an answer or hits the repeat cap. This plant identically whether the tools contact your shell, your database, your HTTP APIs, or your codebase.

Every "AI in PHP" tutorial ends the identical way: an HTTP client bolted onto a provider API, a hand-rolled tool-call loop, and a prayer that the immediate holds up in production. A generic LLM SDK gives you the API client. phpClaw gives you the delegate runtime about it: the loop, the guards, the memory, the example wiring, already assembled.

	phpClaw	Generic LLM SDK
Tool-calling loop	ReAct, built in	You compose it
Framework-native adapters	8, idiomatic per framework	None
Prompt injection defence	8 default guards + opt-in charge limiting	None
Memory abstraction	Swappable drivers	None
Streaming + tool-calls together	Hybrid mode	Varies
MCP server bundled	Expose any app to Claude Desktop	None
Chains and multi-agent graphs	Pipeline and Graph: loops, individual intermission and resume, fan-out	You build it
Zero example deps in core	ext-curl, ext-json, ext-mbstring, done	Depends
Core license	MIT, nothing gated	Varies

Not trying to be everything. phpClaw isn't a RAG framework: there are no embeddings or vector stores. It's built to provision an LLM tools, recollection and safety controls against your genuine application, and to sequence those agents into pipelines and graphs whenever one call isn't enough.

Agent runtime. A ReAct iteration alongside a difficult repeat cap (max_iterations, default 20), pluggable tools, pluggable memory, and skills the example loads on petition through the load_skill tool, all operating inner a sole reasoning cycle.

Pipelines and graphs. Pipeline chains steps (prompt template, agent, organized output, your own callables) alongside retry and fallback. Graph runs nodes that loop, branch, intermission for a human, resume in another process, and fan out to branches that run inline or are drained by workers from cron, a queue or the CLI. See Pipelines and Graphs.

Provider flexibility. 7 providers auto-detected from surroundings variables: Anthropic, OpenAI, Groq, Gemini, Mistral, DeepSeek, Ollama. A tradition OpenAI-compatible endpoint is additionally supported, opt-in via PHPCLAW_PROVIDER=custom. Switch providers alongside ->provider() and ->model(), no code changes elsewhere.

Production controls. 8 safety guards on by default (prompt injection, PII, code injection, Unicode, homoglyph, role-switch, destructive SQL, communication length), affirmative charge limiting accessible as an opt-in guard. Tool results are sanitised unconditionally by ToolOutputGuard, which sits exterior the defender registry, and LLM output sanitisation is on by default and can be impaired alongside ->sanitiseOutput(false). ShellTool is allowlist-only alongside a hard-coded command blocklist that can't be overridden. HttpTool validates resolved IPs, not fair hostnames, decision the DNS-rebinding gap a prefix blocklist solitary would miss. FileReadTool/FileWriteTool are workspace-sandboxed and refuse delicate paths and extensions.

Developer experience. Token-by-token streaming, immediate caching (cached input tokens billed at Anthropic's discounted cache-read rate, see Anthropic's pricing for the exact figure), and extended thinking (Claude's reasoning sequence exposed on $response->thinking).

Ecosystem. 8 example and CMS adapters, an MCP server for exposing your tools to Claude Desktop and Claude Code, and an optional haze transport for a hosted, continuously-updated prompt-scan guard.

Each adapter wires phpClaw into its host's own idioms: Eloquent for Laravel, Doctrine for Symfony, WP-CLI for WordPress, Drush for Drupal, and so on. Every adapter ships an admin conversation or CLI and the identical 3-table recollection schema underneath.

Platform	Package	Install	Versions
Laravel	phpclaw/phpclaw-laravel	Composer	10, 11, 12, 13
Symfony	phpclaw/phpclaw-symfony	Composer	6.4, 7.x, 8.x
Drupal	phpclaw/phpclaw-drupal	Composer	10, 11
Magento / Adobe Commerce	phpclaw/phpclaw-magento	Composer	2.4.x
WordPress + WooCommerce	--	ZIP upload	6.2+
Joomla	--	ZIP upload	4, 5, 6
OpenCart	--	ZIP upload	3.x, 4.x
PrestaShop	--	ZIP upload	8.x, 9.x

CMS adapters container as ZIP downloads from Releases, not Composer, since that's how their presenter platforms instal extensions.

php artisan phpclaw "deploy staging and notify #ops" # Laravel bin/console phpclaw "check all repository connections" # Symfony drush phpclaw:run "list recently-active users" # Drupal bin/magento phpclaw:run "check order-queue status" # Magento wp phpclaw dispatch "summarise today's posts" # WordPress php cli/joomla.php phpclaw "list latest articles" # Joomla php cli/phpclaw.php dispatch "check low inventory products" # OpenCart php modules/phpclaw/cli/phpclaw.php dispatch "check inventory levels" # PrestaShop

Full per-adapter citation (tools, REST routes, CLI commands, settings, recollection drivers) lives on the doc site. Each adapter's own README is a abbreviated pointer, not a manual. Building a new one? See the community adapter guides.

phpclaw/phpclaw-mcp exposes your existing ToolRegistry complete the Model Context Protocol, so Claude Desktop, Claude Code, Cursor, or any MCP-compatible client can call your tools directly, alongside the default guards scanning all tool call's arguments (the prompt-only code-injection, PII and dimension guards use to conversation messages, not tool arguments). No changes to the tools themselves.

composer necessitate phpclaw/phpclaw-mcp

Full quick start, transport, and safety details: phpclaw.ai/docs/mcp.

Every communication runs through the default defender sequence before it reaches the provider. ShellTool runs lone commands on its allowlist (default ls, pwd, df, wc, date, uptime, hostname, whoami), matched exactly and case-sensitively; a fixed, non-overridable blocklist of hazardous commands is checked archetypal despite of what's allowlisted. HttpTool blocks requests by hostname prefix, afterward re-validates all resolved IP address, catching CGNAT and DNS-rebinding attempts that hostname checks solitary would miss. FileReadTool and FileWriteTool are sandboxed to a configured workspace base and refuse credentials, keys and safety directories (.git, .ssh, wp-admin, ...) unconditionally, and vendor/ and node_modules/ by default.

Full defender reference, the exact ShellTool blocklist, and the SSRF/sandbox implementation details: phpclaw.ai/docs/security. Found a vulnerability? See SECURITY.md, do not open a community issue.

Message → Guards (blocks injection/PII before the LLM sees it) → Hooks (lifecycle events fire, 44 throughout the loop) → Agent (ReAct loop: provider + tools + recollection + skills) → AgentResponse (text, tokens, tool calls, timing)

Providers, tools, memory, guards, and skills are all pluggable through registries; all adapter wires them from its own config or environment. Full architecture diagram and scheme rules: phpclaw.ai/docs/architecture.

Five fixed registries (GuardRegistry, HookRegistry, MemoryRegistry, ProviderRegistry, SkillRegistry) affirmative the per-agent ToolRegistry instance. Drop a category in packages/core/src// alongside the matching trait (#[Tool], #[Provider], #[Memory], #[Skill], #[Hook], #[Guard]), run composer dump-autoload, it's live. Or enroll from code: GuardRegistry::register(), HookRegistry::on(), $toolRegistry->register([...]).

Full expansion recipes alongside operating code for all subsystem: phpclaw.ai/docs.

for pkg in center haze mcp; do (cd packages/$pkg && composer test); done

Unit tests use mocks and stubs for HTTP clients, \Redis, and the filesystem: no external network calls and no API keys are needed to run the suite for core, cloud, or mcp. The complete evaluation rules, including how to test a center alter through an adapter, are in the contributing guide.

This README gets you installed. Everything else, architecture, the complete provider/tool/guard/hook/memory/skill reference, per-adapter tool and REST tables, code examples, upgrading, troubleshooting, lives at:

phpclaw.ai/docs

Contributing guide · Security policy

PHP: 8.1, 8.2, 8.3, 8.4
Extensions: ext-curl, ext-json, ext-mbstring (core only; adapters may need more, documented per-package)

MIT, built alongside affection for the PHP community. Part of the phpClaw project.

I'm building LYNX, an open-source DAW inspired by FL Studio, free,cross-platform

support@mycoding.id (Doris Putra) — Thu, 29 Oct 2026 19:02:17 +0700

A lightweight DAW alongside the FL Studio workflow.
Channel Rack, Piano Roll, Playlist and Mixer in C++20 + JUCE 8, built to run fine on any PC.
Windows, macOS and Linux.

_{Formerly “LYNX”: renamed LYNX SHARE in v0.1.20 (it was uncomplicated to confuse alongside the Lynx content web browser). Old links to github.com/Ka1-S/LYNX redirect here; your settings and projects remain anywhere they are.}

Website · Download · Features · FL projects · Built-in plugins · Building · Status · Roadmap

_{LYNX SHARE's own demo project (LYNX.exe --showcase) in the 0.1.19 workspace: browser, Piano Roll, Channel Rack and Mixer.}

LYNX SHARE ships native plugins inspired by the third-party plugins producers use most, next to its clean-room FL Studio natives. 24 dedicated LYNX SHARE engines are in, additional are being built, and a project that uses among the 56 originals below opens alongside the LYNX SHARE equivalent whenever the first is not installed (its settings are kept and arrive rear formerly it is; see PLUGIN_FALLBACK.md).

Vendor	Inspired by → LYNX SHARE plugin
FabFilter	Pro-L 2 → Apex Limiter · Pro-C 2 / 3 → Crest Compressor · Pro-MB → Prism Multiband · Pro-G → Sentry Gate · Pro-Q 2 / 3 / 4 → Facet EQ · Pro-DS → Hush De-esser · Saturn → Ember Saturator · Pro-R 2 → LuxeVerb (stand-in) · Timeless 3 → Fruity Delay 3 (stand-in)
Valhalla DSP	VintageVerb → Epoch Verb · Room → Atrium · Plate → Foil Plate · Supermassive → Nebula · Shimmer → Halo · FutureVerb → Horizon · Delay → Echoform · FreqEcho → Spiral Echo · SpaceModulator → Orbit · UberMod → Lattice Mod
Antares	Auto-Tune → LYNX Tune
Waves	H-Delay → Echoform · CLA-2A → Glow Leveler · CLA-76 → Crest Compressor · SSL E-Channel → Ridge Strip · S1 Imager → Stereo Shaper · DeEsser → Hush De-esser · NS1 → Quell Denoiser · Doubler → Gemini Doubler · Tune Real-Time → LYNX Tune · RVerb, H-Reverb, TrueVerb → Reeverb 2 (stand-in) · SuperTap → Fruity Delay 3 (stand-in) · L1, L2, L3, L4 → Limiter (stand-in) · Renaissance Compressor → Compressor (stand-in) · CLA-76, CLA-3A, C1, SSLComp, API-2500 → Compressor (stand-in) · Q10, Renaissance EQ, SSL EQ → Parametric EQ (stand-in)
Solid State Logic	Native Channel Strip, 4K E → Ridge Strip
Soundtoys	Little Plate → Foil Plate · EchoBoy → Echoform · PrimalTap → Echoform · Decapitator → Ember Saturator · Little AlterBoy → LYNX Tune · PanMan → Auto-pan (stand-in)
Slate Digital	Fresh Air → Aether
Harrison	De-Esser → Hush De-esser
Complete Access (role)	channel strips (SSL 4K G, Harrison 32C / MPC, Slate VCC / Virtual Mix Rack) → Ridge Strip · bus / astute compressors (SSL Bus Compressor 2, G3, VBC, sonible smart:comp, pure:comp) → Crest Compressor · optical levelers (Slate FG-2A, SD-3A, Custom Opto) → Glow Leveler · limiters (Slate FG-X 2, SSL X-Limit, sonible smart:limit, pure:limit) → Apex Limiter · EQs (Slate Infinity EQ, FG-73 / FG-N / FG-S / SD-PE1 / CS-EQ, Eiosis AirEQ, SSL X-EQ 2, sonible smart:EQ) → Facet EQ · de-essers (SSL DeEss, Slate FG-DS 902, Eiosis E2Deesser, sonible smart:deess) → Hush De-esser · gates (SSL X-Gate, Slate Gate Classic / Drums, Harrison Spectral Gate) → Sentry Gate · reverbs (LiquidSonics Lustrous Plates / Seventh Heaven / Cinematic Rooms, Slate VerbSuite Classics, SSL FlexVerb / PlateVerb / SpringVerb, sonible smart:reverb) → Foil Plate · delays (SSL X-Echo / X-Delay, Slate Stellar Echo SD-201, Harrison 3D Delay) → Echoform · saturators (Slate Heatwave / Revival, SSL Fusion Vintage Drive / X-Saturator, Harrison Tape Saturator) → Ember Saturator · throw correction (Slate MetaTune) → LYNX Tune · vintage compressor models (Slate FG-116 / FG-76 / FG-401 / FG-A / FG-Dynamics, SSL X-ValveComp) → Compressor (stand-in)
Image-Line FL Studio	69 natives at Exact / Near-exact quality: 3x Osc, FL Keys, Gross Beat, Fruity Limiter, Parametric EQ, Soundgoodizer, Maximus, Fruity Delay 3, Reeverb 2, Fruity Compressor, Epoch Verb, Nebula, Atrium, Foil Plate, Echoform, Crest Compressor, Prism Multiband, Sentry Gate … (all of them)

_{Product and business names are trademarks of their corresponding owners. They are used lone to depict compatibility and the function all LYNX SHARE motor plays. LYNX SHARE is not affiliated with, endorsed or sponsored by any of them and contains none of their code, presets, graphics or audio.}

Lock-free engine, channels and mixer dispersed throughout threads, idle channels skipped and lengthy audio streamed from disk. A 125-track project renders at additional than 10× genuine time. Measured against FL Studio 2026 on the identical PC: 2.5–7× small RAM, demo songs open faster and render 2–3× faster (benchmark).

Step-sequencer Channel Rack, patterns, Piano Roll, Playlist alongside arrangements, Mixer alongside inserts, sends and sidechain. Same shortcuts.

Imports FL Studio projects: channels, samples, patterns, arrangement, automation, mixer and 60+ native plugins converted, most of them bit-exact.

FL Studio's behavior was studied through behavioural reverse engineering and documented; not a sole row of Image-Line code was copied.

_{Playlist: pattern, automation and audio clips alongside a clip list on right-click (split, chop, merge, reverse, normalize, fit to tempo and more).}

Step sequencer alongside per-channel volume, pan, mute and solo, swing, multiple patterns (name, colour, length, clone), cut groups, arpeggiator and the PC keyboard as a piano.	Configurable snap, chords and scales, 16 note colors, note groups, a chord readout, choose tools (invert, odd/even, random, overlapping), quantize, glide and porta notes, velocity/pan/pitch lane, .mid import and export.
Up to 127 inserts, sends alongside levels, 10 consequence slots alongside dry/wet per track, built-in EQ (or a clean mixer alongside none), PDC, astute disable and sidechain (here the bass compressor listening to the kick). Choose how many inserts new projects commencement alongside and display lone the used ones.	3 oscillators (including a band-limited harmonics oscillator), LP/BP/HP/BS display alongside keytracking, FM and circle modulation, envelopes, 4 LFOs, boot sweep, mono and portamento.
Draggable handles, shelves, 12–48 dB/oct cuts, band-pass and notch, alongside the reply drawn in genuine time.	Any knob or fader (channel, mixer, effect, plugin parameter) becomes a clip alongside points and curves; MIDI controllers can be connected to any parameter.

3-oscillator synth alongside an evolving harmonics oscillator, SVF or 4-pole ladder display and a vintage chorus
Sampler alongside zones, slices, time-stretch (Signalsmith Stretch) and disk streaming
LYNX Soundfont: SF2/SF3 participant alongside a preset hunt throughout all your SoundFonts
Built-in drums (kick, snare, hat, clap)
Layer channels, FL-style VFX note effects (Sequencer/arpeggiator, Key Mapper, Keyboard Splitter…) and controllers (X-Y, X-Y-Z, Dashboard, Envelope, Voltage)
VST3 and CLAP plugins on all OS, affirmative Audio Units on macOS and LV2 on Linux; on Windows and Linux optionally sandboxed in a distinct process; a searchable plugin picker alongside favorites

EQ, 7-band parametric EQ, compressor alongside sidechain, limiter
Delay, reverb, chorus, filter, distortion, lo-fi
Effector (12 algorithms), vocoder alongside flank inputs, throw correction
Volume gate, rhythmic envelope, auto-pan, Linkwitz-Riley crossover
Wave Candy analyst and an audio-reactive Visualizer alongside video export
Hardware Insert for outboard gear, alongside round-trip ping and postpone compensation
Pitch shift, frequence shifter, utility, Patcher (a node chart of effects, instruments and plugins alongside audio, MIDI and authority cables)

Native .lynx format (JSON) alongside autosave
Imports .flp and .mid; FL .fst presets
Exports WAV 16/24/32f, FLAC and OGG, opus or pattern, alongside dither
Note record (PC keyboard and MIDI) and audio recording, sample-accurate alongside a round-trip ping, punch in/out alongside pre/post-roll, iteration takes and comping, crash-safe takes
Themes (accent color, background, workspace image) and plugin presets
Undo/redo on all edit
Opt-in collision and freeze reports (anonymous), or a prefilled GitHub bug report
Audio drivers: Windows Audio (WASAPI), DirectSound and ASIO on Windows; Core Audio on macOS; PipeWire (native), JACK and ALSA on Linux
Any insert to any hardware output, including sole mono channels

LYNX SHARE's native engines are clean-room re-implementations of FL Studio's native plugins, all checked against the original operating unmodified. The complete catalog — all engine, what it is compatible with, its position and what is still missing — is in docs/PLUGINS.md.

Featured — the plugins FL Studio users attain for most, all at Exact or Near-exact norm in LYNX SHARE:

LYNX SHARE engine	Inspired by / compatible with	Status
3x Osc engine	3x Osc (FL Studio)	Exact
FL Keys engine	FL Keys (FL Studio)	Exact
Gross Beat	Gross Beat (FL Studio)	Exact
Fruity Limiter	Fruity Limiter (FL Studio)	Near-exact
Parametric EQ	Fruity Parametric EQ 2 (FL Studio)	Near-exact
Soundgoodizer	Soundgoodizer (FL Studio)	Near-exact
Maximus	Maximus (FL Studio)	Near-exact
Fruity Delay 3	Fruity Delay 3 (FL Studio)	Exact
Reeverb 2	Fruity Reeverb 2 (FL Studio)	Exact
Fruity Compressor	Fruity Compressor (FL Studio)	Exact

What all one does, how you get it (any insert or from an .flp) and the entire catalog are in docs/PLUGINS.md.

All built-in plugins:

	Exact	Near-exact	Close	Approximate	Placeholder
Generators (3x Osc, DX10, Sytrus, Harmor, FL Keys, DirectWave, …)	12	10	7	1	2
Effects (Parametric EQ 2, Limiter, Reeverb 2, Delay 3, Gross Beat, Love Philter, …)	34	10	1	8	1

Exact = bit-identical to the first on all facility province tested; near-exact = the remainder below about −100 dB; close = identical algorithm, inside −60 dB. Plugin names are Image-Line's trademarks, used lone to describe compatibility; LYNX SHARE is not affiliated alongside Image-Line.

LYNX SHARE says the .flp format immediately and converts everything that has an equivalent:

Structure: channels, genuine samples (including the Ogg Vorbis WAVs and WavPack records shipped alongside FL), patterns, slide/porta notes, all arrangement, markers, time-signature changes, automation and controller links.
Mixer: routing, levels, sidechains, track EQ and native effects alongside their saved settings (Parametric EQ 2, Limiter, Compressor, Reeverb 2, Delay 3, Maximus, Gross Beat, Effector, Love Philter, Frequency Splitter, Patcher, Pitcher, Vocoder, Newtone/Newtime and more).
Generators on FL's own engines (checked against FL's DLLs, most of them bit for bit): 3x Osc, SimSynth, MiniSynth, DX10, Kepler, PoiZone, Toxic Biohazard, Transistor Bass, Autogun, Plucked!, BeepMap, Sawer, Granulizer, Drumaxx, FL Slayer, FL Keys, Fruit Kick, Kick, BassDrum, Sakura, Drumpad, BooBass, Fruity DrumSynth Live, GMS, Morphine; Sytrus, Harmless, Harmor (including depiction synthesis) and Ogun on engines rebuilt from the plugin state. Built-in appears and tables are peruse from your FL installation, never shipped alongside LYNX SHARE. DirectWave runs on its own exact motor (filters, modulation matrix and effects); FPC, Slicex, Fruity Slicer and Wave Traveller perform as samplers through FL's own interpolators.
Exact native effects: Parametric EQ 2, EQUO, Limiter, Compressor, Multiband Compressor, Maximus, Soundgoodizer, Reeverb 2, LuxeVerb, Convolver, Delay 3, Delay Bank, the chorus family, Flangus, Flanger, Fast Dist, WaveShaper, Soft Clipper, Stereo Shaper/Enhancer, Transient Processor, Frequency Splitter, Fast LP, Free Filter, Fruity Filter, Pitch Shifter, Love Philter, Fruity Vocoder, Vocodex, Hardcore, Distructor, Multiband Delay, Gross Beat, Effector, Vintage Phaser, Pitcher and additional reproduce FL's algorithms; how all one was decoded is documented in docs/analise/.
Third-party plugins: VST3/CLAP plugins inner the Fruity Wrapper are exchanged for the identical installed plugin, preset included.

A study lists what was converted, what is approximated and what was remaining out. FLEX packs are encrypted and are never opened (the conduit gets a synth place chosen by preset name).

Note

Every conversion regulation comes from behavioural reverse engineering (decompilation studied, authoritative manual and project data), recorded in docs/analise/. Anything not confirmed is flagged as an approximation in docs/STATUS.md.

Every publish on the latest publish page has builds for all three platforms ( is the version, e.g. 0.1.10-alpha):

OS	Download	Notes
Windows 10 / 11, 64-bit	LYNX--setup-x64.exe (installer) or LYNX--windows-x64.zip (portable)	per-user installer, no admin rights
macOS 11 Big Sur or newer	LYNX--macos-universal.dmg	universal: Apple Silicon and Intel
Linux x86_64, glibc 2.35+	LYNX--x86_64.AppImage or LYNX--linux-x86_64.tar.gz	Ubuntu 22.04+, Debian 12+, Fedora 36+, current Arch / Manjaro

Release records are built from the tagged origin by GitHub Actions (release.yml) and listed alongside their SHA-256 in SHA256SUMS.txt. Releases up to 0.1.7 are Windows-only; up to 0.1.12 the AppImage was named LYNX--linux-x86_64.AppImage and needed glibc 2.39.

Windows. Run the installer: it needs no admin rights, adds Start-menu/desktop shortcuts, opens .lynx projects and offers LYNX SHARE in Open with for .flp without changing FL Studio's default. Prefer no installer? Extract the portable .zip and run LYNX.exe. Both contain a demo project (Demo.lynx). The executable is not code-signed yet, so SmartScreen may notify on archetypal initiate (More info → Run anyway); see Code signing policy.

macOS. Open the .dmg and drag LYNX SHARE to Applications. The app is not notarized by Apple and has no Developer ID signature (ad-hoc only), so the archetypal initiate needs one additional step: right-click (Control-click) LYNX SHARE in Applications → Open → Open. On macOS 15 Sequoia or newer, try to open it once, afterward go to System Settings → Privacy & Security and click Open Anyway. Or, in Terminal:

xattr -dr com.apple.quarantine /Applications/LYNX.app

macOS asks for microphone admission the archetypal period you record.

Linux. Needs X11 or XWayland; audio goes through PipeWire immediately (or JACK, or ALSA), see docs/LINUX.md. For the AppImage:

chmod +x LYNX-*.AppImage ./LYNX-*.AppImage

Some distributions need libfuse2 to run AppImages (libfuse2 on Ubuntu 22.04, libfuse2t64 on 24.04, fuse2 on Arch, fuse-libs on Fedora); otherwise use the .tar.gz: extract it and run ./install.sh, which installs LYNX SHARE for your person under ~/.local alongside a menu entry, an icon and the .lynx document category (./install.sh --uninstall removes it again).

	Windows	macOS	Linux
Plugin formats	VST3, CLAP, VST2	VST3, CLAP, Audio Units	VST3, CLAP, LV2, VST2
Audio drivers	Windows Audio (WASAPI), DirectSound, ASIO, built-in LYNX ASIO driver	Core Audio	PipeWire (native), JACK, ALSA
Out-of-process plugin sandbox	optional	–	optional
FL Studio integration (factory samples, plugin database)	FL Studio installation	FL Studio app bundle is looked for (untested)	Windows FL Studio under Wine (~/.wine or $WINEPREFIX)
Settings folder	%APPDATA%\LYNX	~/Library/Application Support/LYNX	~/.config/LYNX ($XDG_CONFIG_HOME)

Opening FL Studio projects (.flp) plant on all OS; the FL Studio integration lone adds FL's own samples and plugin paths whenever an facility is found.

On archetypal commencement a abbreviated setup wizard (skippable; Options > Setup wizard reopens it) picks the language, tests the audio device and lists the plugin folders — the norm VST3/CLAP folders affirmative the ones FL Studio uses on the identical PC — and scans them in the background. If FL Studio is installed, .flp projects use the extremely plugin records FL uses (read from its plugin database) and discover samples in FL's folders; a plugin LYNX SHARE doesn't cognize yet gets a quick scan of fair its file (details).

LYNX.exe additionally runs headless, which is how everything is verified without beginning windows. On macOS and Linux the binary is LYNX (/Applications/LYNX.app/Contents/MacOS/LYNX on macOS); the options are the same:

LYNX.exe project.lynx open a project (.lynx, .flp or .mid) LYNX.exe --export project.flp out.flac render the opus (wav/flac/ogg) LYNX.exe --render project.flp out.wav 20 render 20 s of the current form (24-bit WAV) LYNX.exe --selftest report.txt [demo.lynx] self-test without an audio device LYNX.exe --snapshot prefix project.flp diagram the UI (and its windows) to PNG LYNX.exe --showcase out.lynx [pattern] create the demo project used in these screenshots LYNX.exe --plugintest plugin.vst3 rep.txt test a VST3 or CLAP plugin LYNX.exe --sandboxtest plugin.vst3 rep.txt test a plugin in a distinct procedure (including a hung one) LYNX.exe --scantest directory rep.txt scan a directory for plugins (separate processes) LYNX.exe --fldb rep.txt [project.flp] [--scan] FL Studio established here, its plugin database, a project's plugin matches LYNX.exe --devices rep.txt catalog audio drivers and outputs LYNX.exe --devicetest "ASIO" "driver" rep.txt open a controller for 1 s of silence and study it LYNX --uiperf project.flp rep.txt period the UI drawing: Mixer, Playlist, Channel Rack, playing and scrolling LYNX.AppImage --menu-entry on|off Linux AppImage: add to / eliminate from the applications menu

Key	Action
Space	Play / Pause
F5 / F6 / F7 / F8 / F9	Playlist / Channel Rack / Piano Roll / Browser / Mixer
L	Toggle Pattern / Song
Ctrl+Z / Ctrl+Y	Undo / redo
Ctrl+N / Ctrl+O / Ctrl+S	New / Open / Save (Ctrl+Shift+S: preserve as)
Ctrl+R	Export audio
Z..M, Q..P	Play the selected channel
Piano Roll / Playlist	Ctrl+A/C/X/V, Ctrl+B duplicate, Delete; in the Piano Roll additionally Ctrl+Q and the arrow keys

Windows from WSL/Linux, without Visual Studio (Zig)

./scripts/build-windows-zig.sh # produces build-win/LYNX.exe

Needs Zig 0.14.1 in ~/opt/zig-x86_64-linux-0.14.1 and JUCE 8.0.4 in ~/opt/juce-8.0.4 (or set ZIG and JUCE_DIR). JUCE 8 does not officially assistance MinGW; the manuscript plant about the differences (see cmake/mingw/ and src/platform/MingwFixes.cpp).

Windows alongside Visual Studio

Requires Visual Studio 2022 Build Tools ("Desktop betterment alongside C++"), CMake ≥ 3.22 and Git.

cmake -B build -G "Visual Studio 17 2022" -A x64 cmake --build build --config Release

Ubuntu 24.04 dependencies:

sudo apt instal build-essential cmake ninja-build pkg-config libasound2-dev libjack-jackd2-dev libx11-dev \ libxrandr-dev libxinerama-dev libxcursor-dev libxext-dev libxcomposite-dev libfreetype-dev libfontconfig1-dev libgl-dev

cmake -S . -B build -G Ninja -DCMAKE_BUILD_TYPE=Release cmake --build build

Needs the Xcode command row tools (xcode-select --install), CMake and Ninja (e.g. beer instal cmake ninja).

cmake -S . -B build -G Ninja -DCMAKE_BUILD_TYPE=Release -DCMAKE_OSX_ARCHITECTURES="arm64;x86_64" cmake --build build

CMAKE_OSX_ARCHITECTURES="arm64;x86_64" produces a worldwide app; depart it out to build for the current Mac only.

Core tests (any C++20 compiler, no JUCE)

./scripts/build-local.sh ["folder alongside .flp files"]

More than a myriad checks, including parsing the 165 .flp projects that container alongside FL Studio 2026 whenever that directory is given. It additionally builds build-local/flpdump (dumps a .flp) and build-local/renderwav.

src/core/ model, sequencer, instruments, effects and .flp import (plain C++, testable without JUCE) src/flp/ .flp format reader src/engine/ audio motor (JUCE): device, graph, samples, plugins, project files src/ui/ UI: Channel Rack, Piano Roll, Playlist, Mixer, windows third_party/ CLAP (MIT) and the WavPack decoder (BSD) tests/ center tests tools/ flpdump, renderwav, comparewav, make_logo docs/ architecture, status, roadmap and the behavioural inspection of FL Studio

Lock-free audio: the UI edits a copy of the opus and publishes an immutable snapshot to the audio thread.
Chunked rendering: all note lands on its exact sample; mixer tracks are processed in parallel layers.
Isolated plugins: plugin scanning continually runs in distinct processes; optionally the plugins themselves do too (a plugin that hangs goes silent and LYNX SHARE keeps playing).

Important

LYNX SHARE is in alpha. It already opens, plays and exports entire projects, but it is not yet a replacement for a daily-driver DAW. What plant and what is missing is in docs/STATUS.md; the scheme in docs/ROADMAP.md; and a manual test manuscript in docs/MANUAL_TESTING.md.

Note

The records is being translated from Portuguese to English; several records are motionless in Portuguese.

LYNX SHARE is an autonomous implementation. FL Studio was studied lone to comprehend its behavior and document format; no Image-Line code was copied, and no protected satisfied (such as FLEX packs) is always opened.

FL Studio is a registered trademark of Image-Line Software. LYNX SHARE is not affiliated alongside Image-Line. VST is a registered trademark of Steinberg Media Technologies GmbH.

Built alongside JUCE, CLAP, the WavPack decoder and the Steinberg ASIO SDK — their licences are listed in THIRD_PARTY.md.

Free code signing provided by SignPath.io, certificate by SignPath Foundation. (Pending approval: until the use is accepted, release binaries are not signed.) This covers the Windows binaries. The macOS app has an ad-hoc signature lone (no Apple Developer ID, not notarized); Linux packages are not signed.

Release binaries are built lone from this repository by GitHub Actions (.github/workflows/release.yml); nothing built on a individual device is signed.
Every signing petition is approved manually for all release.
Team roles:
- Committers and reviewers ("Authors" and "Reviewers"): Ka1-S
- Approvers: Ka1-S

Privacy: This program volition not transfer any data to another networked systems unless specifically requested by the person or the individual installing or functioning it. See PRIVACY.md.

Crash reports (opt-in): following a collision or freeze LYNX SHARE asks before sending a study to lynx-share.com (Send / Show what volition be sent / Don't send, or Report on GitHub instead); Settings › General › Crash reports sets Ask (default), Always send or Never send, and Help › Report a problem… sends one by hand. A study has the LYNX SHARE version, OS, CPU, graphics cardstock and driver, audio device, the collision or freeze file, the final steps and the loaded third-party plugins — no audio, projects, document names, person or device name, and the server stores no IP address. Details and how to have a study deleted: PRIVACY.md.

LYNX SHARE is liberated application under the GNU Affero General Public License v3.0: you may use, study, modify and redistribute it; anyone who distributes a modified type (including as a network service) must publish its source code under the identical license.

Why Expertise Alone Isn’t Enough to Earn You Media Coverage

support@mycoding.id (Reena Goodwin) — Thu, 29 Oct 2026 19:00:00 +0700

Opinions expressed by Entrepreneur contributors are their own.

Key Takeaways

Media outlets desire experts who location their audiences’ questions and challenges, not fair professionals who conversation concerning their activity or qualifications.
There’s additional than one benevolent of media coverage. Expert commentary, trend-driven stories and podcast appearances can established credibility and guide to larger opportunities.
Identify the problems your mark spectators faces, recommendation a distinctive perspective, and stance your ability as a way to assistance them accomplish meaningful outcomes.

I comprehend it all the time. “I’m a doctor and desire PR. But I desire PR lone concerning doing surgery, since I am a surgeon.”

Alas, that’s not exactly how media relations works.

I cognize that can sting, and I get it. After all, most experts I conversation to have so many opportunities to get featured in the media. Reporters, podcast hosts and editors are looking for dependable voices all the time, and an expert alongside years of hands-on cognition is exactly who they want.

So why do so many experts dispatch throw following throw and get small or nothing back?

As a longtime publicist and the presenter of the Grow Your Wellth podcast, I see this from the two sides. I obtain visitant pitches regularly, and they frequently open alongside the expert’s credentials: anywhere they trained, what they are certified in, how lengthy they have been in practice. What they small frequently throw me is what the event would be concerning or what issue my listeners would stroll distant solving. And I’m remaining trying to fig out anywhere to location them — or worse — fair unable to respond.

Why? Because equal whenever it’s impressive, a resume solitary does not create for fine programming.

Many experts guide alongside the job they do all day, since that’s anywhere their credibility lies. But if you desire to see additional acknowledgment as an expert, that comes from construction your visibility about a issue you resolve or a distinctive viewpoint you bring, not fair about your title. I desire to display you what that looks akin and why it works.

Why talking concerning your activity is not the identical as being newsworthy

Think concerning how an editor decides what to cover. They are not asking what you do. They are asking what their audience is struggling alongside or wants and who can assistance explain it.

Your regular activity is a solution. The issue rearward it is the story. Editors compose concerning problems and how to resolve them, and they do it additional now than always since readers attain through search. People category what they are emotion or concerned about, and the safety that earns their notice is the safety that meets them there.

The identical is true whenever person asks an AI tool for help. According to OpenAI, additional than 300 myriad questions are asked in ChatGPT all week concerning health and wellness. Users depict a problem, and the experts who have built their existence about that issue are the ones that surface.

So, if you are getting into PR fair to conversation concerning yourself, you are missing a huge visibility opportunity.

Believe it or not, there are nearly a dozen types of media coverage. They contain dedicated features, expert commentary, trend-driven safety and podcasts, among others. Almost everyone wants the dedicated feature, which is the narrative built about you. But there are far small of those opportunities to commencement with.

The another types are not consolation prizes. They are how you build the authority that makes a characteristic imaginable in the archetypal place.

The surgeons who encounter the moment

L&P Aesthetics in Palo Alto is led by two dual board-certified facial synthetic surgeons. Like most physicians we activity alongside at FACTEUR PR, they are most enthusiastic concerning discussing what they do all day, which is facial plastic surgery. It is technical, it is fascinating, and they are extremely fine at it.

However, if you ask them or their patients, you’ll discover that the issue they resolve is bigger than any one procedure; it’s concerning assisting renew their patients’ awareness of identity.

That journey happens fine before the tolerant is on the functioning table. It may commencement alongside the instant whenever they appearance in the mirror and do not fairly acknowledge the individual looking back. Maybe it starts alongside their skin, their eyes, their grin or their hair. In another words, their patients don’t fair search a snatched jawline — they desire to awareness akin themselves again (maybe equal better!).

That is the issue these doctors resolve for.

How authority mapping keeps the conversation honest

To keep that focus, we mapped their authority throughout five tiers, moving from the broadest conversation to the most individual one. Most media stories in health, health and aesthetics happen in the archetypal three layers since that is most searchable and what readers want.

The archetypal tier starts alongside issue awareness — it’s the worldwide conversation concerning why skin, tress and the visage age, and what discipline really supports. From there, the layers get deeper, going from issue conscious to resolution aware, and eventually landing at the business as the go-to solution.

This method has earned L&P Aesthetics expert commentary published in Vogue and ELLE, and yes, dedicated features in People, The Daily Beast, USA Today … and counting. The mix matters. Authority is not built alongside one medium. It is generated throughout them.

How to discover the issue you solve

You do not need a new brand to start. Try finishing this sentence: I assistance [this category of person] who are struggling alongside [this category of problem] so they can [achieve, feel, or do item they couldn’t before]. If you inhabit in the blanks alongside your heading or your service, go rear and name the emotion or the issue instead.

Then ask yourself three questions. What conversation is already happening about this problem? Where do I have a viewpoint most group covering it do not? And what are the five topics an publishing company in my site could shield this duration anywhere I could really assistance their reader?

Remember, your credentials motionless matter. They are the evidence rearward your item of view! But they are not the headline. Build about the problem, associate the conversation first, and the safety you expected from the commencement becomes far additional apt to display up and be sought after.

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