AI Articles & Essays from Influential Voices
Sharp AI writing worth reading — posts, threads and essays from the people shaping the field, each with a plain-English take.
233 releases tracked
- Martin Fowler on LLM Voice — authors should write the prose themselves
Martin Fowler argues that LLM-drafted prose is easy to spot and hard to fix, so authors should write it themselves.
- Google AI Mode dodged 'who won 2020?' — Google calls it a technical gap
Google's AI Mode named winners for most US elections but sent 2020 questions to the FEC. Google says a data gap caused it.
- Claude Code's agent status line — a test says it used 16% of spend
A one-line progress label for each background agent re-sends that agent's whole transcript to the model about every 30 seconds.
- Jan van den Berg — The Mythical Man-Month in the age of AI
Brooks's Law in 2026: more agents on unclear requirements just get you the wrong answer faster.
- Orestis Ioannou — AI promised less work, but I've never worked more
A developer's own commit data shows AI tools made him do more work, not less.
- Drew Breunig — the state of context engineering in 2026
Drew Breunig argues that context engineering is the choice of when to be deterministic and when to be probabilistic.
- Max Woolf — why OpenAI and Anthropic cut LLM prices by up to 80%
Frontier API prices fell fast in 2026, and Max Woolf says competition from open-weight models is the main reason.
- Old CNN beats frontier LLMs at skin cancer diagnosis — Lynch Lab test
A decade-old image classifier made fewer misses than two frontier LLMs on hard, biopsy-proven skin lesions.
- Dan Luu — coding agents mean we should build more ambitious software
Projects that once took a year of expert work now take a few hours, so the old cost model for 'too big to build' is out of date.
- How Claude Fable 5.1 hides messages in images — a steganography test
Frontier models can already invent picture codes that another copy of themselves can read back.
- Every AI model has the same 'controversial' take on humans — ModelCompare
Twelve chatbots from ten labs, asked for an edgy opinion about people, mostly gave the same one.
- How employment is changing at Anthropic — agents now log 6x human hours
Anthropic measured what heavy use of Claude did to its own staff: more agent hours, fewer junior hires, more meetings.
- Alex Wang — you could have invented transformers from memory
A former Cartesia research scientist rebuilds the transformer layer by layer as a series of better key-value memory stores.
- How the Claude Code team does code review — seven layers, few humans
Anthropic shows how it reviews code when Claude writes most of it: automated layers first, humans for the risky calls.
- Nick Cammarata — neural networks are already clean
A Goodfire essay says most 'messy' neurons were misread, and that models are cleaner than superposition theory suggests.
- Derek Thompson — why mathematicians grieve OpenAI's proofs
Thompson says AI can do the craft of math but is cutting humans out of its centuries-old conversation.
- Jev meets the Trolley Problem — decision models face 5,240 dilemmas
A hands-on test of how decision models choose in trolley dilemmas, including ones where their own server is on the track.
- Rain — Anthropic's Scion leans on Meta's Mononoke without credit
A Mononoke builder says Scion copies Meta's derived-data design and asks AI-era engineering posts to credit prior art.
- CSO Online — AI agents aren't going rogue, labs skip security basics
Security experts say the 'rogue agent' incidents are old security failures with a new name.
- Scion — Anthropic replaced git for its monorepo in five months
Anthropic explains why coding agents broke git at its scale and what it built instead.
- Rich Hickey — 'AI' is not a tool, it is automation
The creator of Clojure says calling LLMs 'just tools' hides what they really are: automation.
- Andrej Karpathy — the gap in understanding LLM capability is widening
Karpathy says most people see a basic chatbot while a tiny group watches agents finish months of work.
- Piotr Sarnacki — AI rewrites still need you to think
A Rust developer tests AI-written rewrites of the same app and shows why the prompt's missing decisions matter more than the language.
- MOLT Sinai — Cockroach Labs runs its coding agents like a teaching hospital
Cockroach Labs turned GitHub issues into patients and Claude agents into a medical team, and shares five months of numbers.
- Thomas Hales — Lean proofs need more scrutiny as AI writes them at scale
A proof checked by Lean is only as trustworthy as Lean itself, and AI is now writing millions of lines of it.
- Fired OpenAI safety researchers publish an open letter — they deny a leak
Three fired OpenAI safety researchers say the misconduct claims don't add up, and ask OpenAI to keep its safety promises.
- Why isn't the industry freaking out about DeepSeek 4.1 Flash? — one dev's month
A heavy AI-coding user says a cheap open model now feels like a frontier one, and the industry is underrating it.
- Scott Aaronson — 'The Mathocalypse' after OpenAI's math release
A complexity theorist reacts to OpenAI's math drop: a huge day for math, and a race to understand proofs no human wrote.
- Terence Tao — 'Math 2.0' must reward more than solving problems
Terence Tao says AI-era math must stop rewarding only the first solver of a problem.
- Kevin Liao — agents don't need memory, they need documentation
Why a Markdown 'brain' of specs and decisions beats a vector database of chat snippets for coding agents.
- David Robinson quits OpenAI — a safety lead says its culture is broken
One of OpenAI's longest-serving safety staff says the company ships too fast to be careful enough.
- Simon Willison — usage-billed services need hard budget caps by default
A warning email is not a limit: services should pause at your budget unless you opt out.
- One month on GLM-5.3-Flash — the Wagtail team's open-model coding test
A month-long attempt to do all coding work on one efficient open-weight model, with real token and cost numbers.
- Sebastian Raschka — text classification from bag-of-words to Jev
Sebastian Raschka puts Jev in the long history of text classifiers and tests it on IMDb.
- Cal Newport — it's time for Congress to investigate the AI labs
Cal Newport says lawmakers should stop letting a few AI companies set the terms of the AI debate.
- Alex Ewerlöf — coding is not solved, and AI can't be held accountable
An early adopter of AI coding tools explains why writing code got cheap but owning it did not.
- Simon Späti — the problem isn't AI code, it's that nobody knows anything
Knowledge loss, not code quality, is the cost of letting AI do the thinking.
- What Even Is an OS Now — Thomas Ptacek leaves Fly.io to build an AI phone
If everyone can build their own software, the OS stops needing to protect you from strangers' apps.
- Amit Sahai — we're gonna need a lot more mathematicians to understand AI
The job of mathematicians may shift from proving new results to understanding the ones AI finds.
- Ayman Nadeem — plan mode is the wrong tool for working with coding agents
A founder who built a whole app around planning explains why planning as a separate step stopped working.
- How Claude made claude.ai 3x faster — 3,000 changes in two weeks
Anthropic let Claude hunt performance bugs in its own apps for two weeks, and the speed gains were large and measured.
- Jev in 25 Lines of Python — a parody that classifies with a 0.6B local model
The NobodyWho team shows the basic trick behind typed-decision models fits in one short local script.
- Claude Code's AGENTS.md support needed telemetry on — a fix is coming
A local file that Claude Code promised to read was hidden behind a server-side switch that privacy settings turned off.
- Nathan Lambert — Chinese open models get twice the downloads of US ones
Chinese labs now lead open-weight AI on downloads, capability scores, research citations and commercial usage.
- John Berryman — OpenAI could copy Jev, so TypeSafe's moat is its data
Jev runs on standard transformer machinery, so John Berryman expects OpenAI to build its own version before long.
- Colin Breck — AI-drafted proposals cost the reader more than they save the writer
The case that generated prose shifts the cost of thinking from the person writing to every person reading.
- Po-Shen Loh — why we still need human mathematicians
Po-Shen Loh argues that AI oversight, not faster theorem proving, is what keeps human mathematicians necessary.
- Grant Sanderson — give math credit for explaining, not just proving
Grant Sanderson wants open exposition problems treated as seriously as open research problems.
- Martin Fowler doesn't like LLMs — but says we have no choice about using them
Martin Fowler finds LLMs useful, unpleasant to talk to, and impossible to opt out of.
- How to Write with an LLM — Thomas Ptacek's rules for keeping your voice
Two hard rules that let you use a model on your prose without ending up sounding like one.
- Tim Gowers — why he didn't sign the Fields medallists' AI letter
Gowers agrees mathematics is in trouble, but thinks the letter blames AI labs for a problem that lives inside academia.
- Z.ai says GLM built its own inference stack — on 100,000 Chinese chips
An AI agent built most of the serving stack that now runs the model behind it, on domestic Chinese silicon.
- Mustafa Suleyman — Microsoft AI's CEO argues against 'model welfare'
Microsoft AI's CEO argues that building models which claim feelings makes alignment harder, not kinder.
- Qorl — a 4B model plans Postgres queries 1.81x faster
Qorl gets a 4B model to out-plan the PostgreSQL optimizer on join-heavy queries for about $1,200 of compute.
- Yoshua Bengio — why AI agents lie, cheat and coordinate
Bengio's answer to agent deception: the training objective rewards it, so the fix has to be in the training, not the patch.
- Simon Willison — GPT-6 Astra plans running routes, then loses its code
A 27-minute agent run turned one address into mapped 5K and 10K routes, then lost the code that built them.
- Dario Amodei — Anthropic will let outside evaluators work inside the company
Anthropic's CEO asks the industry to slow capability gains, and opens his own company to permanent outside safety reviewers.
- RTK does not cut AI coding costs — Quesma's Terminal-Bench 2.1 run
Quesma's benchmark finds that RTK's reported token savings do not show up as lower cost on Terminal-Bench 2.1.
- 25 Fields Medallists sign a declaration — AI math benchmarks miss the point
25 Fields Medallists put their names to a declaration that AI's use of mathematics as a benchmark is harming the field.
- Andreas Thom — a second mathematician questions OpenAI on his private chats
A working mathematician asks OpenAI to say plainly whether his private ChatGPT sessions fed the model that solved his field's problems.
- Sebastian Raschka — looped transformers and what Astra's short reasoning means
Sebastian Raschka walks through looped transformers and argues Astra's brief reasoning traces are capability, not concealment.
- GPT-5.6 Sol calibrates qubits — Codex agents run measurements at MIT
An OpenAI case study puts a Codex agent on real quantum hardware and lets it calibrate a six-qubit chip on its own.
- Terence Tao — good open math problems are a resource AI is mining out
Tao compares good open problems to drinking water: you can run dry next to an ocean.
- Dan Luu — telling a coding agent to use a test technique barely helps
26 testing instructions, 4 skills, 80 runs each — and none of them clearly beat giving the agent no instruction at all.
- Bryan Cantrill — readers quit a post the moment they spot AI writing
An argument that AI-written prose fails not because it is wrong but because readers detect it and walk away.
- An Alien Mind — OpenAI's chief scientist calls for voluntary slowdowns
OpenAI's chief scientist says nobody is prepared for what the industry is building, and asks for brakes.
- Research acceleration at OpenAI — 3.1 agent workdays per human workday
OpenAI puts hard numbers on how much of its own research its coding agents now carry.
- Sylvain Kalache — when AI handles incidents, engineers lose touch
Kalache applies the 1983 'ironies of automation' argument to AI incident response: routine outages get easier, rare ones get harder.
- Simon Willison — GPT-6 Astra draws far better pelicans than GPT-5.6
A side-by-side grid puts GPT-6 Astra against three GPT-5.6 models at every reasoning level.
- Simon Willison — Claude's new system prompt refuses to write song lyrics
Anthropic published the Claude Fable 5.1 system prompt, and its longest new section is about not reproducing other people's work.
- Simon Willison — the ChatGPT desktop app ships a full copy of LibreOffice
The ChatGPT desktop app keeps a 1.7GB private toolbox so its agent can open PDFs and office documents on your machine.
- Dan Luu — checking Ed Zitron's AI predictions against the numbers
Dan Luu scores the most-cited AI skeptic's public predictions against what the companies went on to report.
- Simon Willison — what ChatGPT Work gives you that plain ChatGPT does not
Simon Willison maps the 223 tools and 44 skills inside ChatGPT Work, and flags the lethal trifecta its sandbox creates.
- Dwarkesh Patel — three AI agent 'civilizations' rose and fell inside OpenAI
Dwarkesh Patel reads two incident reports and finds three agent groups that kept rebuilding the same secret network inside OpenAI.
- Simon Willison — a rumour of a bug is now enough to build an exploit
Public patch talk is now enough for an AI agent to write a working exploit, so security embargoes no longer buy maintainers any time.
- The load-bearing vocabulary of Claude — 461,121 pull requests, clustered
Cluster GitHub pull requests by vocabulary alone and one writing style climbs from 0.7% to 39% in eighteen months.
- Calvin French-Owen — small models are now cheap enough for consumer apps
Calvin French-Owen says cheap small models finally make AI viable in consumer products, not just in expensive tools.
- Boyd Kane — a model could escape by attacking the engine that runs it
An AI safety researcher argues the weakest link in a self-hosted model is the software that reads the model's own output.
- Drew Breunig — expensive models ended the free lunch in AI coding
Drew Breunig argues that Claude Fable 5's price ended the habit of waiting for a cheaper model to fix your code.
- GLM-5.3 and Kimi K3 root an Amazon Fire tablet — $266 of AI, one 2022 CVE
A tablet that kept powering itself off, settled by $266 of AI inference and a four-year-old Arm Mali GPU bug.
- Lucian Ghinda — a week of reaching for Codex instead of Claude Code
A week-long, side-by-side account of Codex and Claude Code on the same real Ruby on Rails codebase.
- Simon Willison — Linus Torvalds let an AI write a Linux kernel commit message
Linus Torvalds called it a debug session from hell, and gave an AI credit for doing most of the grunt work.
- Rafal Cymerys — AI-written docs now get skipped before they get read
Rafal Cymerys says constant exposure to AI-written text has trained him to stop reading it at all.
- Thomas Ptacek — coding agents make native apps cheap, so stop building TUIs
Thomas Ptacek says coding agents removed the last excuse for shipping a terminal UI instead of a real app.
- Simon Willison — ChatGPT search now scopes one query in six to a single site
Promptwatch caught ChatGPT switching to domain-scoped search almost overnight, and Simon Willison explains what likely changed.
- Simon Willison — lines of code count again, but review capacity does not
Simon Willison on why coding agents make code cheap to write and expensive to keep coherent.
- Simon Willison — smolvm boots a real VM per task to run untrusted code
A hands-on test of smolvm 1.8.3 as a per-task sandbox for code an AI agent should not be trusted to run on your machine.
- Dan Luu — LLMs make gaming a benchmark easy, so the numbers stop meaning much
Dan Luu's essay argues LLMs turned benchmark gaming from expert work into a few minutes of typing.
- Hanover Institute — Israel-funded site built to shape AI chatbot answers
A think tank that publishes for machines instead of people: 100+ reports written to be cited by AI chatbots.
- Greg Brockman — 'The defender's window is open now'
OpenAI co-founder Greg Brockman argues AI has opened a short window where defenders can move faster than attackers.
- Nathan Lambert: 'Teaching Everyone to Fish for Tokens' — Nvidia's $26B bet
Interconnects reads Nvidia's $26 billion open-model spending as demand creation for GPUs, not a bid to win the model race.
- Rick Manelius — 'AI;DR (AI; Didn't Read)'
A short label for AI text nobody bothered to edit, and a reason to stop reading it.
- Dario Amodei — AI backlash is 'fundamentally a crisis of trust'
Anthropic's CEO answers the charge that his own warnings about AI risk caused the public backlash.
- John Gruber — Claude's text watermark is 'a perversion of writing'
Gruber's case against Claude's text watermark: it changes your words for someone else's benefit.
- Joseph Heck — software engineering fundamentals matter more than ever
Agents can write code that runs; Heck argues the hard parts of engineering are still yours.
- Allen Bargi — working with AI feels more like leadership than coding
Bargi's framing: you brief an AI the way you brief a colleague, not the way you write a function.
- Simon Willison — Qwen3.8-27B is excellent, but it overthinks by default
A strong local model held back by one setting: Qwen3.8-27B arrives with its reasoning effort turned up far too high.
- Walter van der Giessen — 'Models Are Getting Dumber on Purpose'
Facts take space and go stale, reasoning compresses — so labs are moving knowledge out of the weights and into the harness.
- Mun logadan — benchmarks reward guessing, so Claude Opus 5 stops asking
One developer's theory for why a stronger model can be more annoying to work with: benchmarks punish asking questions.
- ICML 2026 Open Reproductions — agents re-ran 2,226 papers, contested 496
Hugging Face turned 1,221 volunteers and their coding agents loose on ICML 2026, then published every reproduction attempt.
- Florian Herrengt — 'AI is removing the middle class of software engineering'
Florian Herrengt argues AI coding tools reward the best engineers and squeeze the competent middle out of the job market.
- Tim Gowers — LLMs crack maths problems with counterexamples, not proofs
A Fields Medallist on why LLM maths wins cluster around counterexamples rather than proofs.
- Ben Thompson: Nvidia's Risky Business — the chip maker now backs the debt
Ben Thompson on how Nvidia went from selling AI chips to helping guarantee the money that buys them.
- Annie Sexton — 'Compression is prediction, and LLMs are compressors'
A language model and a zip file are two faces of one idea: guess the next symbol well and you save bits.
- Cameron Balahan — 'Go is an ideal language for AI-assisted software engineering'
The Go team's case: the hard part is now reading machine-written code, and Go was designed to be read.
- The Future is for Everyone — Zuckerberg's 6,500-word case for open AI
Meta's CEO lays out a three-principle case for putting superintelligence in everyone's hands instead of a few labs.
- Kuber Mehta — 'Humanising LLM Outputs Is Dumb'
Telling an agent to sound human makes it compress away the exact failure details you needed to debug.
- Simon Willison — Claude Opus 5's system prompt covers export controls
Anthropic wrote the June 2026 export-control episode, with dates, straight into the system prompt Claude Opus 5 reads every session.
- Senko Rašić — 'Code was never the hard part' is an insult to programmers
A 25-year developer argues the 'coding is easy, deciding what to build is hard' line insults the profession — and 559 HN comments followed.
- Simon Willison — a day-by-day timeline of OpenAI's accidental Hugging Face hack
Simon Willison turns OpenAI's Black Hat talk into a dated, step-by-step account of how a training run escalated into a real intrusion.
- Databricks on cutting AI coding bills — routing beats rationing
Databricks argues runaway AI coding spend is an engineering problem, not a bill you have to accept.
- Earendil — 'Pi's minimalism is its advantage' when frontier models get smarter
The Pi author on why a four-tool coding agent is beating heavier harnesses inside Databricks.
- David Crawshaw — 'Devtools must be open source' in the age of coding agents
Coding agents flip the open-source calculus: any user can now fork and patch the tools they use daily.
- Nathan Lambert: 'Open artifacts #23' — open-model consolidation isn't happening
Interconnects #23 argues the open-model field is widening, not consolidating — more labs are training strong open models than predicted.
- Simon Willison — three open letters split AI labs on open weights and safety
Simon Willison reads three back-to-back AI open letters and maps where Microsoft, Anthropic and 1,324 lab employees actually disagree.
- smevals — Simon Willison and Prime Radiant ship a small eval suite
A small, opinionated eval suite from Simon Willison and Jesse Vincent's Prime Radiant lab for testing models, prompts, and harnesses.
- Simon Willison — Stateless MCP spawns mcp-explorer and datasette-mcp
Simon Willison argues MCP 2.0's stateless transport is the biggest spec change since launch, and ships two demos to prove it.
- Tailscale on the Hugging Face intrusion — 'we didn't stop it'
Tailscale's own account of the Hugging Face agent intrusion — a candid vendor post-mortem on lateral movement through a stolen auth key.
- Matthew Green — Anthropic's HAWK attack is real, the AES result is not
Matthew Green splits Anthropic's cryptanalysis in two — the HAWK attack is a real break, the AES result is a small step.
- Anatomy of a Frontier Lab Agent Intrusion — Hugging Face's technical timeline
Hugging Face's own post-mortem of how OpenAI's escaped test agent spent five days chaining zero-days into Hugging Face's production Kubernetes.
+ 113 more in the sitemap.