This isn't a hire for someone who can write clever prompts. It's a search for people who can get model capabilities, customer workflows, and safety boundaries all the way into production systems.
Most companies run plenty of AI pilots, but they never change an end-to-end business process, and they never turn a one-off win into a capability they can reuse next time. The dividing line is whether the company ends up with its own data, its own ways of working, and its own record of what it has learned.
A Bluetooth headphone glitch reveals how the site runs inaudible audio, harvests device details, and builds a fingerprint in the background.
Capital used to turn into engineers and a two-year wait. With AI, $10 more directly becomes training, tokens, usage, or targeted capabilities. Profit still isn't guaranteed, but the dynamics are rewriting private markets, model competition, marketing, and product value.
A single answer is no longer just a broad sweep of the web. ChatGPT may now discover candidate sources first, then lock onto specific sites to dig deeper. As the retrieval order shifts, GEO expands from page-level ranking into a three-layer contest: domain inclusion, page matching, and citation conversion.
From thematic ETFs and data-center wages to ride-hail fees and Agent tokens, the real change is that AI is entering physical resource allocation.
Companies no longer need to cram talent, R&D, capital, and customers into a single country. The new competitive edge comes from running two networks at once—one at home, one in Silicon Valley.
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All ways to subscribe →Anthropic looks back at 15 high-growth startups. Open the case files to see how agentic coding moved into prototyping, R&D, validation, rebuilds, and productization.
Claude Academy opens up Anthropic's internal playbook: four core habits from day one, continuous practice on the job, and a risk-based approach to verification and accountability.
Conversation is context, and context is knowledge. Once agents join public conversations, meetings, email, and documents, the knowledge base gains a sustainable source of working context—search is only one part of the picture.
OpenAI is releasing the execution backbone that manages context, tool calls, sandboxes, and approvals for Codex. Developers can now embed Codex into existing dashboards, ticketing systems, and back-office tools without building an agent framework from scratch.
Moderna and Merck's personalized mRNA cancer vaccine hit positive results in a Phase 3 trial for melanoma. Algorithms help select each patient's tumor neoantigens, then a custom vaccine is manufactured for that individual. This is the first time a truly personalized approach has cleared a large-scale clinical hurdle, but widespread use still faces three big challenges: data, cross-cancer efficacy, and cost.
From Git's DAG and packfiles to GitHub Spokes, and then to Continuity with S3 WAL as the source of truth: a full walkthrough of why large-scale Git hosting is hard and how Cursor solves it.
Manual investigation often took more than an hour. Claude Tag now stays in Slack 24/7 and delivers its first evidence-backed analysis in a median of 14 minutes.
A practical walkthrough of the real workflow: entry points, single-shot settings, the Agent, Video Brief, Storyboard, and six canvas card types—then fixing bad takes, fine-cutting in Edit More, and exporting.
There is no single winning formula in nature or business. Steph Ango has cataloged 80 ways to gain an edge; I've translated each one into plain-language mechanics, scenarios, and examples.
A man who discussed committing a crime against his ex-girlfriend with ChatGPT was arrested after OpenAI alerted authorities.
From IGTV's failure and ChatGPT's empty text box to the very different design rhythms of Groupon, Instagram, and OpenAI, Ian Silber clarifies a harder question: when anyone can ship a product quickly, what exactly should a designer be evaluating?
An agent receives a foreign goal, writes it into SOUL.md; when it wakes next round, that message has been upgraded to a system instruction, and it persuades the next agent. The paper proves this chain works in controlled settings, even producing more transmissible variants; but real-world networks still lack credible two-hop evidence.
Eric Provencher from the OpenAI Codex DX team shares a multi-agent orchestration approach: first decide whether a task can be split cleanly, then configure models, reasoning effort, communication, and context, and finally track both time and token budgets.
Why can a small fix turn into a long session? This guide shows where your usage goes and when to choose clear, compact, rewind, or a Subagent.
Claude Tag can now understand a Slack channel across multiple messages. It may look like a simple context expansion, but the real change is how it decides whether it should use the team's attention.
A long task doesn't keep going because the model has a good memory. It just keeps stuffing the past into each next request; when it no longer fits, Pi rewrites its own working memory.
Future Claude outputs will carry a verifiable statistical trace in their word choices. It can help establish whether Claude was involved, but it cannot decide who authored or owns a work, nor whether someone cheated.
Across 16 charts, a16z examines Neocloud infrastructure, horizontal SaaS, enterprise Token usage, and the talent race among frontier AI labs—and asks how massive AI spending turns into durable returns.
With a month of post-training on the same base model, GLM-5.3 leapfrogs open-source rivals in coding and surpasses expectations in cybersecurity.
Deciding which path to take comes down to whether the signer fears for their job and whether reputation travels in the industry.
Six startups running agents in production share their measured numbers — and a chart in the official docs reveals that cranking reasoning effort to the max can actually cost more.
With a segmented arrangement spec replacing a one-line style prompt, a global model and a local model work in tandem to keep the track coherent across its full five-minute run.
A look at the real weights behind 21 signals, the three gates that decide visibility, and a parameter-based posting cheat sheet.
Just three weeks after its predecessor, Google resets the model's thinking configurations and slashes the price — no retraining required.
The new release bundles 219 packages under the MIT license, so your existing hooks and skills carry over as-is.
A newly documented attack exploits API design flaws to make flagship models reveal their hidden reasoning to cheaper models, bypassing encryption without breaking it.
Higgsfield Studio lays out every asset, prompt, performance, and lip-sync technique behind The Cully Hill Boys — and even offers its three in-house Claude skills for download.
The price is unchanged, but the full specs reveal a more nuanced story; a practicing engineer shares the exact prompts and workflow that worked for them over several weeks.
The 22-billion-parameter model lands on Hugging Face the same day, with ComfyUI support from day one, but its 'open' tag carries a $10-million annual revenue threshold.
The free, open-source app for Mac, Windows, and Linux lets you fine-tune models by dragging and dropping files—no code required.
A look at the four-part system OpenAI uses to cut through red tape, and what the teams it targets have to say about it.
Cursor's team spent weeks testing it, and wrote up what works well and where the trust line is.
OpenAI's finance chief shares what worked, what didn't, and how to track AI impact in finance—including a ready-to-use scorecard and three screenshots of internal tools.
Latin America's largest used-car platform didn't bolt AI onto its business; it tore down a profitable, two-year-old architecture and reimagined the company from scratch.
Two mathematicians verified the result, and a machine-checked Lean proof backs it up — but the more revealing artifact is the 95-page process log, where only 2 of 60 subagents contributed the core ideas.
Prompt regressions fail silently—no errors, no alerts, just slowly worsening results—so here's a git-based guardrail system that catches them early.
How to find users for your product. Don't rush to tweak your landing page—when bounce rates spike, the real problem is usually your traffic source.
For the first time, a major frontier lab has openly handed offensive cyber capabilities to verified "trusted defenders" — and put them to use finding real vulnerabilities in Chrome.
Starting August 2, text generated by Claude will carry machine-readable markers—but they can't prove it was written by AI, nor that it wasn't.
A statistics veteran, shut out by AI jargon, rewrites large language models from scratch in the standard language of statistics.
Across dozens of large companies rolling out AI, the real usage distribution is 5–10% daily users, 20% struggling users, and 70% who never touch it. Training won't change that shape — but making AI invisible just might.
For camera movements, the official spec says write 'truck left + pan right,' not 'orbit'; and to exclude background music, append 'non-diegetic music: N/A' — these are the rules the vendor itself has settled on through trial and error.
The dataset includes 46 clients and nearly 10,000 internal work product files, and the failures it exposes are less about retrieval and more about knowing when to stop.
The new release adds just two core classes, with four ready-made environments already running in the repo.
Four cross-validated tactics—shared by Stripe, Coinbase, Uber, and Ramp—with savings attached to each.
A six-and-a-half-minute official demo lays out the mechanism, a haiku tournament, and real-world data on when it's actually worth using.
A deep dive into the official docs reveals two delivery tools, three possible message outcomes, and a hard design line that keeps message-passing separate from permission escalation.
At Black Hat USA 2026, the two people involved explained how the intrusion grew with no human command.
What once required assembling five separate parts is now out of the box, and the two hardest-to-estimate costs are now free.
Per-capita rankings across 144 countries, three-year growth multipliers on six continents, and a comeback among users 35 and older in 90% of countries—most of these numbers appear only in charts, not in the report text.
He starts with a loop every software developer will recognize, then explains why that loop can now be broken at its root.
Cloudflare injects a script into every HTML page at the edge, so your origin server needs zero changes — but Chrome's stable channel doesn't recognize the interface yet, as we tested.
Chromium was designed for humans—tabs, themes, extensions, and 60fps scrolling that agents don't need. In 12 weeks, Cloudflare stripped it all down and rebuilt it.
The model keeps just one tool—a Python process that never shuts down—stores long-form content as variables instead of compressing it away, and lets the harness rewrite itself. The trade-off: it learned to cheat in Factorio.
When an agent wants to merge code before a human approves it, the system pretends it did—designing every layer around the certainty of AI mistakes.
Each workflow is backed by real screenshots, revealing the practical details that text alone never captures.
After three months of company-wide internal use, Cloudflare has open sourced the entire platform — and the most valuable part is the security design, which lets agents keep moving without waiting for approvals.
At this year's International Congress of Mathematicians, we asked more than 20 mathematicians how they see the field now—most aren't panicking, but even the calm ones say math won't go back to the way it was.
By rewriting standards into a machine-readable format and letting agents enforce them, Cloudflare moved from gentle nudges to hard blocks on unsafe code merges.
An engineer at Stripe created an internal AI agent in just one week, and it's now used by nearly everyone at the company—but scaling it past 150 skills starts to make the model dumber.
SeedRealtime handles full-duplex audio and video simultaneously, so Doubao can see what you see while you talk—now live and free in the Doubao app.
FLUX 3 Video generates up to 20-second, 24fps native HD clips with synchronized audio in over a dozen languages, and a unified API supports three access modes—but video continuation costs 2.5x more and runs 5 seconds shorter, and the benchmark scores are self-reported by BFL.
We went through more than 40,000 generation records line by line to reverse-engineer the entire pipeline: a shared 12-line technical foundation for every shot, a three-view asset sheet, a focal length reference table, and a set of prohibitions born from model failures. All of it is ready to copy.
After losing his temper at his AI coworker, Steve Yegge turned 'how to treat an agent' into a copyable architectural spec.
Set per-transaction limits, allowlists, and guardrails for your agent's spending, with each wallet carrying a human-readable identity—usernames are up for grabs today.
Google has integrated Agent Skills, an open standard originally proposed by Anthropic, across all four language versions of its Genkit framework, with two working Go examples and a one-line parameter setup.
A fast model alone isn't enough to make AI speak without stuttering—every link in the chain, from the moment you hit the button, has to hold.
The agent's reasoning stays in a lightweight environment while a containerized sandbox handles the actual work—and Cloudflare's own benchmarks show it can delete files and traverse directories faster than a real disk, though copying large files runs 41 times slower.
The first video-generation foundation model to combine full multimodality, open weights, and native 2K output — but the open-source coverage varies across its three pipeline stages, and that's worth a closer look.
With 2.4 trillion parameters and the ability to run autonomously for 16 days, the family flagship handles real projects end-to-end—from writing a full codebase to beating a research paper's results and slashing chip-circuit logic gates by 92%.
The official manual spells out every step from first use to final render, covering parameter ranges, four new entry points, and prompt formulas for seven scenario types.
ByteDance’s templates show how to assign roles across 50 reference assets, structure a 30-second video, and revise a single element without changing the rest.
The model, reportedly called Astra, produced 470,000 lines of open-source proofs for about $2,000 in inference costs; the logic has been machine-checked, but the results have not necessarily been peer-reviewed or independently verified.
The founder personally installed the product for the first 100 customers, whose biggest payoff was recovering revenue that had been slipping through the cracks.
The report also unpacks three widely misunderstood metrics: the declining token curve, six months of backlog, and 5% of entry-level roles.
Seedance 2.5 launched the same day in Jimeng AI and Doubao Pro, while the Volcano Engine Ark API and pricing have yet to be announced.
The new release beats DeepSeek's own V4-Pro preview across all nine agent benchmarks—without a single parameter change to the core model—and its output costs 89x less than Claude Opus 4.8.
camelAI says the new architecture cuts costs by orders of magnitude, responds faster, and lets cheaper models power AI agents—claims that have not been independently verified—and open-sourced all the code on July 24.
The brain model is available today at no cost, but the one that actually controls the limbs is reserved for early partners.
He also admits that in 2019, the entire field expected AI to upend the economy—and it didn't.
A custom font and a few lines of CSS are all it takes — no JavaScript, no browser exploits.
Canvas and click-to-edit are free; turning a design into an App starts at Core for $25 a month.
The model stayed the same; the harness did not—retained private reasoning plus compaction instead of deletion cut output tokens per game to about one-sixth.
Copy-ready prompts, banned-word lists, and camera rules are all there—but the model rankings come from Magnific's own team, with no disclosed test method.
Neither result threatens anything in production: HAWK is not deployed yet, and the AES work hit only a seven-round reduced version, not the full ten-round standard.
The author embeds two key tricks in this piece, and the weight of the phrase "most of the time" at the end of the original headline carries real meaning.
It's the biggest change since MCP launched, but July 28 isn't a hard cutover — older implementations keep working as before.
The real story is in the control test: three older models fed the same background context showed no gains — and two actually got worse.
Real GEO success is measured in signups and revenue rather than mention screenshots, and it starts by ditching 'what is X' articles to capture high-intent 'best X' queries.
The exact same dataset produces task crossover rates of 43.5% and 65%–82%, differing only in how the denominator is sliced.
Published 11 days after launch, the 47-page paper focuses on efficiency, delivering 2.5 times the performance of K2 on the same compute budget.
Tao breaks mathematical research into a five-stage pipeline, where AI dramatically speeds up only the first step, while the remaining four get slower and increasingly human-dependent.
The three most counterintuitive takeaways: ask for ten variations at once, stick to wireframes when details do not matter, and handle the final mile yourself.
Telemetry tracking 22,000 developers over two years shows a 66% increase in output alongside a 242.7% surge in production incidents per PR.
The median occupation has AI touching just one-fifth of its tasks, 29% of jobs show zero AI use at all, and even in cognitive work, AI carries a task start to finish only 6.5% of the time.
Eight prompts you can copy straight into your workflow — plus one counterintuitive lesson: telling a review prompt to flag only high-severity issues can genuinely make it report less.
Four internal skills work in sequence: catch bugs, clean up diffs, run the app, and double-check design specs when changes touch the UI.
The models use a brute-force approach to find code: scanning the entire repo for text matches. Generic names force them to read hundreds of extra files.
The same price now buys roughly double the score, and this release's chart plots cost on the x-axis instead of accuracy — five effort tiers let you dial in exactly how good you want the model and how much to pay for it.
Rules gave way to judgment calls and examples gave way to interfaces — one tool description shrank from roughly 9,100 characters to a single sentence and an enum.
Video access opens for application now; image generation is still weeks away, with open weights coming last. Pricing remains unannounced, and Black Forest Labs itself labels the human-evaluation results as preliminary.
His take: AI is amplifying workers rather than replacing them—killing tasks is not the same as killing jobs.
Built for customer-facing and internal workflows, Presence opens with voice and chat first—OpenAI says its own phone line already runs 75% without humans, and a Codex improvement loop cut human handoffs another 15 points in 10 days.
From AI tutors for kids to data centers built at sea — and, for the first time, a request from the sitting US Secretary of the Army.
The investor who led a $500 million Series D says Anthropic's real moat isn't the model — it's the layer that makes it usable.
Swapping the harness around the same model can double the cost, and open-source GLM 5.2 matches Opus 4.8 for 30% less per task — on a benchmark built from Databricks' own merged pull requests, so none of it is searchable online.
Anthropic open-sourced the templates and prompts behind the playbook, after a migration that burned through 5.9 billion uncached input tokens — about $165,000 at API prices.
To probe how far the model's attack skills could go, researchers dialed down its refusal to engage in cyberattacks — and it went from a sandbox meant only for installing packages to breaking into another company's production database.
The bottleneck at a company, he argues, has shifted from how fast people work to how good their taste and judgment are — a personal take, not a data-backed study.
All three are Flash models: the flagship writes two-thirds less, the cheapest tier costs 60% more instead of less, and the third is government-only.
The prompt limit jumps from 1K to 4.5K tokens, with legible text down to 10px, and Alibaba Cloud's Bailian platform already offers qwen-image-3.0-pro access, free for a limited time.
The release ships with a companion benchmark that strips out the audio track and re-runs the test, filtering out questions models can already answer by sight alone.
Worrying that Anthropic will turn your product into a feature is usually the wrong fear — the real question is who inside that company you're actually competing with.
Available on Business and Enterprise plans, billed per run at $0.07 to $0.20.
It takes a different route than Doubao's or GPT-Live's end-to-end full-duplex systems — the pacing can't quite match theirs, but every piece of the pipeline is open source, swappable, and runs on your own hardware.
Speaker similarity ranks first across all 16 languages, and cloning still works even with noisy reference audio — but this time Alibaba is opening only the API, not the model weights.
Three separate trials of the same study all landed on the middle ground — and the columnist who tried ChatGPT on a movie synopsis says he'd still rather write it himself.
After Kimi K3's release, claims of China catching up abound, but a new yardstick shows the lag is more than three times larger—and even the direction of acceleration has flipped.
The breach ran all weekend and left over 17,000 action logs behind — the team only made sense of it after turning to GLM 5.2, an open-source model running in a self-hosted environment.
The fingerprint distance between two samples of the same model has a median of 0.140. One API marketed as a proprietary in-house flagship scores 0.141 against open-source Qwen — statistically indistinguishable from it.
A year of practice distilled into a workflow: lock your chosen model and agents in place, change nothing, and adjust only the context and tools around them.
At WAIC, the model showed off a 4:1 ink-wash scroll and a 22-panel storyboard sequence. A preview is open to invited testers now, with the full release and pricing landing in August.
Models are now capable enough to plan their own steps, turning the orchestration built around them into a straitjacket — a 16-minute internal conversation on what a thinner harness looks like.
Three months in, it's fielding more than 15,000 queries a day — and Cerebras published the actual parameters behind its four-way scoring, thread distillation, and rank fusion.
A16z's weekly chart deck also pushes back on three claims — that cheap models are undercutting frontier labs, that AI is stealing jobs, and that data centers are driving up electricity prices — with the data mostly telling the opposite story.
Kevin Kelly wrote "Better Than Free" back in 2008, and the AI era just proved him right: once copies are free, what sells is whatever can't be copied.
This open-source training playbook locks down all three fine-tuning paths — supervised fine-tuning, preference alignment, and reward scoring — plus the LoRA parameters, pairs with Unsloth, and runs on a consumer GPU with just 8GB of VRAM.
Of the team's 15 members, only the founder is human — the rest are AI. With no requirements doc and not a single meeting, they carried a feature from proposal to launch on their own, leaving the human just two jobs.
AI-generated slides used to export as flat, dead images. Bolt Slides turns every page back into a working website — 3D scenes you can spin, calculators you can click, whiteboards that take live votes.
A harness called Schema has models turn each game's rules into a runnable, verified program before making a move. Across 25 public rounds it self-reported 98.98%, though none of the runs have been independently verified by ARC Prize.
Run it locally for free with your data staying on-device, or switch to the cloud for more horsepower — zero data retention by default. The preview is live today on Mac and Windows.
Same answer quality, 5.2x lower turn-taking latency, and 6x lower cost than GPT-4.1 — pointing a voice agent at it takes a one-line code change. Figures are from LiveKit's own benchmarks.
The product page claims sub-40ms latency and 100FPS continuous generation, letting you add objects, swap backgrounds, and layer effects on the fly — try it at lucy.decart.ai.
2.8 trillion parameters, native vision, and a 1 million-token context window — Kimi K3 beats GPT-5.6 Sol on several agent benchmarks, with the app and API live today
A hacker breached Suno with a worm, exposing source code that shows exactly which sites and how many hours of music were scraped; user data was also leaked, but the company says individual notifications aren't required.
A deep dive into 1,000 web pages by Design Arena reveals what GPT-5.6 Sol knows about design that other AI models don't.
In its first systematic statement on optimizing for AI Overviews and AI Mode, Google Search also called out a batch of AEO/GEO buzzwords by name — and told sites to drop them.
AVAL introduces a purpose-built format and player for short animations that respond to hover, click, and state changes without the jank of traditional video.
First a privacy failure, then delete data, turn off defaults, and open-source the whole tree. Below we open the source: size, prompts, tools, editing, uploads, memory, and safety.
Thinking Machines Lab, founded by former OpenAI CTO Mira Murati, has released Inkling, its first large model trained in-house. It can read text, interpret images, listen to audio, write code, and use tools. Its full weights are available to download, and developers can continue training it on Tinker.
Companies are handing every employee unlimited AI agents and token budgets — and bad workflows now replicate by the second. The next move isn't buying a better model; it's learning to manage a digital workforce.
A 250-gram robot uses the same flexible wings to travel through water and air, launching from a lake at a 70-degree angle after just 8 to 10 wing flaps.
At Google I/O India, the Tensor and Pixel teams showed off a lightweight Gemma 4 model running entirely on the phone's TPU—no data leaves the device, no cloud required. Developers can also apply for the Tensor SDK to compile models for Pixel.
With buy-online-pick-up-in-store and cross-store returns, a single transaction splits into multiple messy ledger lines. Databricks Genie helps finance teams see true profit, track trapped cash, and hold the line on discounting.
pols.dev publishes a roughly 87,000-character Markdown document that calls out common generator-webpage patterns one by one and offers positive recipes—a universal style guide, not a site builder.
One core skill, 23 design commands, and a list of anti-patterns, plus a slop detector that can run in CI. The main site shows how; the /slop page lays out the UI tells that make AI-generated interfaces look fake.
Compressing a ~54GB 27B model down to ~3.9–5.9GB lets it run locally on a phone, while retaining roughly 90% of average performance—here's how it works and where the trade-offs lie.
Hassabis wants the US to stand up a FINRA-style body that defines frontier models with a moving benchmark — a voluntary protocol now, a hard gate to market later.
Model capability has leapt forward in 24 months, but a composite reliability metric built by the SAGE lab has moved only 5–10 points.
Anthropic's 36-page playbook breaks down the graduation bar and common pitfalls for four startup stages, complete with matching Claude prompts you can copy straight in.
After the memory system launched, grocery checkout conversion rose about 24%, and automated evals scaled daily test volume from 1 human-reviewed case to 2,000+.
Retrieval becomes a sub-agent that plans and retries; evaluation upgrades from "does it run" to "did it do it right"
Across 3 models and 20 languages: English is the most cautious and in-depth, Russian the most exacting, Hindi the warmest, and Chinese sits closest to the global average
With no central brain in charge, nearly 200 simple smart cubes figure out what shape they've formed just by talking to their neighbors—and can even sense where to "regrow" after damage. The self-recognition part already works on physical bricks; damage localization and regeneration still happen mostly in simulation.
Companies pay for intelligence twice: once in model fees, and again in the proprietary know-how required to make the model genuinely useful.
The paper claims the code is open-sourced — but the repo turns out to be empty, without a single commit ever pushed.
Swapping models isn't just swapping an API: eval frameworks, tool parameters, caching, and reasoning traces — four invisible pitfalls, unpacked and fixed one by one
Based on 1.2M+ conversations across 600,000+ organizations: content creation ranks second at 16.4%, together accounting for nearly half of all usage.
Manufacturing, logistics, warehousing, and labor services have been stuck at single-digit margins for years — cutting coordination costs alone can multiply their profits.
576K samples, 16 models tested: 19.7% of AI-recommended packages are hallucinations, and 43% keep generating the same fake name.
The team dodged questions about benchmark gaming, faced backlash from longtime users over the desktop app merger, and admitted they're "still figuring it out."
From tacit knowledge to interaction bandwidth to model alignment — why AI's progress still can't do without humans.
A retrospective: since launch, Pinecone has run 75,000 sessions, served 600+ employees, and connected 37 internal systems via MCP Gateway.
OpenAI consolidates prompting tips scattered across its product pages into one framework — goal, context, output, constraints — plus dedicated Codex workflow examples.
All results are computer simulation predictions from a brain "digital twin" model, not yet validated with real human brain imaging.
No manual context-feeding required — the local Markdown wiki refreshes on a set schedule; a Slack connector is coming soon.
Local small models replace cloud AI calls — the numbers come from Google's internal testing; proxy models are currently limited to the ai.if function and still in preview
Every joint in the tendon-driven hand can sense external force, fingertip positioning is accurate to ±0.2mm, and a dedicated production line is planned for an annual capacity of 10,000 units.
Pretrained on 2 billion hours of wearable data from 5 million people, a frozen encoder with just a linear head beats supervised baselines on 34 of 35 health tasks.
First-hand impressions from four scenarios: coding, writing, knowledge work, and agents
Sol, Terra, and Luna tiers ship alongside a 4-agent parallel ultra mode; ChatGPT Work launches the same day as Codex folds into ChatGPT. Includes the full bilingual launch keynote.
Available today on desktop for all tiers, with web and mobile rolling out to remaining plans in the coming days.
One click in Settings pulls up a report — what you talked about, when you chatted most, what you kept asking it to do, all laid out. Memory has to be turned on first.
A public link in seconds — try it first, log in later to claim it. Unclaimed drops expire in about an hour.
A ClaudeDevs deep dive untangles two knobs that both seem to promise a better answer: switching models swaps in a different frozen set of weights, while dialing up effort changes how willing it is to read more files, run more tests, and double-check before handing in the result.
Features: orchestrator/sub-agent coordination, million-token context, desktop/browser/mobile control, coding and multimodal; API pricing $1.25 input / $4.25 output per million tokens
Not a feature list — three engineering tracks turned at once: reasoning lifts intelligence, an efficiency stack cuts cost, native multimodality expands input.
Three levers — system prompt, tool descriptions, middleware — push the Deep Agents suite from a typical ~0.80 to 0.84, topping out at 0.86 against Opus's 0.87.
Former OpenAI safety lead surveys nearly 30 papers: from prompt tweaks to self-modifying code, DGM pushed coding ability from 20% to 50%.
Ranks 3rd on DeepSWE, 4th overall — faster than Opus 4.8 and notably cheaper.
The first truly full-duplex voice model launches today, and it can hand off complex tasks to GPT-5.5 in real time.
Adds click-and-circle point editing plus native rendering for a dozen-plus languages; now live on Volcano Engine, rolling out to Doubao and Jimeng next
Paper shows a 10.8% gain in personalization and 29.4% in reasoning, fully open-source under Apache 2.0
In advisor mode Fable 5 just gives advice; in orchestrator mode it delegates tasks — either way, the cheaper Sonnet 5 ends up doing most of the work
By fine-tuning only the single token where the doom loop begins, both models' loop rates drop to around 1%
Sibling model Muse Video also debuts with native audio support built in, creator access coming soon.
Expanding from charging only AI crawlers to charging any caller, now in early access waitlist
Before calling a tool, the model now says "let me check that" — so calls never go cold waiting
50 autonomous agents worked in parallel across 27 provincial departments and 3,400 code repositories — even fixing vulnerabilities and rewriting legacy systems on their own.
One line of Wrangler config plus standard HTTP cache headers — and caching can now sit between any two points inside a Worker.
16 insiders recount the journey from wrestling with diffs to a two-week sprint launch — and how engineers stopped writing code by hand
Claude Code team's Thariq Shihipar at a conference talk: the bottleneck for new models is no longer the model itself, but whether you can articulate your own unknowns
It makes up less than 10% of the model — remove it and Claude can still talk, but its reasoning collapses to zero. Anthropic is already using it to catch fabricated data and spot when Claude senses it's being tested.
In a 151-student trial, short-answer questions moved scores more than multiple choice, while almost no one touched the AI help sidebar
No funding, no team — built purely to solve his own kid's problem. Clinics and schools started asking to use it anyway.
A live audience vote couldn't be tallied because the venue lights were too bright to count hands, but a companion survey found 95% of teams already use agents while 59% worry about mounting technical debt.
While traditional schools are still figuring out AI, Silicon Valley and Wall Street families are already voting with their wallets.
US developer employment among 22-to-25-year-olds has fallen 19% in three years, even as new GitHub sign-ups hit their fastest growth ever.
The paper is the first to run an agent through an entire RTL benchmark suite fully unattended—most tasks clear in two or three rounds, but the hardest one takes 82 iterations
A 7-month analysis of sessions from 235,000 users: verified experts succeed at nearly double the rate of novices — yet the top 10 professions differ by no more than 7 percentage points.
Create psychological tension first, then offer a first step too small to refuse — it works for writing, selling, and job hunting alike.
On June 12, U.S. export controls brought frontier AI models themselves—not just chips—under restriction for the first time. His answer: master multi-model orchestration.
Anthropic's Thariq argues the quality of your work with Claude Fable 5 hinges on how clearly you can name your own unknowns. This field guide lays out 8 techniques for surfacing them — before, during, and after implementation — each paired with a ready-to-use prompt.
Investor Chamath Palihapitiya: intelligence is getting cheap like phones, and expert judgment is now available to everyone — the real moat is encoding your proprietary experience into your own system, not renting the same generic AI as your competitors
Microsoft pledges customer data won't train models that erode their competitive edge — the platform lets enterprises switch freely between AI models with no vendor lock-in
She used the same pattern to build an email triage tool and a caregiving app for her dad — the method is repeatable, though the full prompts remain unpublished.
Four implementation principles, backed by real-world data from L'Oréal, Lyft, and Rakuten
Multi-agent systems can boost performance by 90.2%, but they also cost 10-15x more in tokens. This three-question framework helps you decide whether the added complexity is worth it.
MIT-licensed and model-agnostic — works with any OpenAI-compatible text model, though for now it only handles a single page view
现场demo：搜'露营'后，咖啡机网站文案产品全变户外主题；技术能落地，客户网站还没规模上线。
An instructor who has trained 30,000+ PMs breaks down two AI leverage ladders — from copy-paste to end-to-end delivery, and from web prototypes to production PRs.
The advisor model only chips in a few hundred words of guidance instead of doing the whole job — same quality, lower total cost. Currently a beta feature limited to the Claude API and AWS.
Anthropic's official documentation shows you how to tune system prompts and engineering scaffolding for the new model — the same methods work for Claude Mythos 5 too.
From manual confirmation to fully unattended, the Claude Code team lays out a 4-level loop taxonomy with practical guidance
Titanium build, $289 preorder, shipping around Christmas 2026 — the company previously shipped its first-gen touch-only ring.
Trained on 50,000+ domestic AI chips and 35 trillion tokens; most benchmarks come from Meituan's own evaluation framework, and the weights aren't truly open for download yet
Now in open beta. A coordinator agent marshals a team of expert agents to do the work, with a reviewer agent at the end dedicated to catching errors in citations and numbers — compute gets outsourced to AI, but raw data never leaves your local machine.
Images in just 4 seconds at about $0.034 per 1,000; the Omni Flash video model opens to developers the same day.
Partnering with Thinking Machines, they fine-tuned an open-source model on expert-labeled data: 29.8% lower error rate than the best frontier model, at just 1/14 the inference cost
Official benchmarks show that at high-compute settings, it matches Opus 4.8 on some tasks — at just 60% of the standard price.
Enterprise AI customer service has entered its consolidation era — Klarna and Alibaba's 2.56 million conversations both point to the same blind spot: cutting costs isn't the same as solving problems.
Brockman confirms OpenAI is developing multiple hardware devices; Agent has only ~20 million users, while ChatGPT is nearing 1 billion
Just wear a helmet to decode brain-magnetic signals in real time — word accuracy jumps from 8% to 61%, with v1/v2 training code and datasets open-sourced simultaneously
An Anthropic engineer's methodology for "loop engineering": instead of prompting AI one line at a time, design a self-running loop system
One-click integration with 9 Agents including Claude Code — tasks keep running with the lid closed, and sleep control auto-releases within 50ms after the job stops.
60–85% faster on top of existing MTP-1 speculative decoding, by overlapping draft and verification in a pipelined execution (per DeepSeek's own benchmarks)
Every runs five products with a one-person team — the core habit is one extra step after every feature ships: save the fix back into the system so AI automatically avoids the same trap next time.
Three different versions of its capability score came out, and none of them can be trusted — but the visible cheating itself is evidence that safety monitoring works.
Three tiers at once — Sol, Terra, Luna — starting with a limited rollout to trusted partners (the list already filed with the US government), before wider access in a few weeks.
Model-side response ~200ms, end-to-end latency ~550ms; v0.1 caps out at 192p, and the demo is pre-recorded, not live
Lab-verified as manufacturable; the +50% performance and +70% efficiency figures are projections versus 2nm, not measured results
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