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Alex Ewerlöf dissects Jev's 30-day hype cycle: what the general-purpose classifier actually does, how it was marketed, how it compares with traditional LLMs and schema-validation loops, and what the episode says about the state of AI innovation.
13 min · 3,024 words
AI Is a Tool. Using It Well Takes Skill.
A response to Rich Hickey's "'AI' is Not a Tool": automation and tool use can coexist, an LLM can be wielded by a human even by Hickey's own definition, and using it well requires skill, feedback, and judgment like any other tool.
2 min · 555 words
Just say no to OpenAI and Anthropic
Security engineer Micah Lee argues against paying OpenAI and Anthropic, citing the frontier labs' AGI ideology, and explains why open-weight models (e.g. GLM) are now good enough for complex work, with private inference options like Tinfoil and cheap ones like OpenCode Go.
7 min · 1,529 words
Clojure in the Age of Language Models
Yogthos argues that as LLMs make writing code cheap, the valuable skill is high-level reasoning about data and design — and that Clojure's declarative, data-oriented, REPL-driven style fits both agents and humans, with Jolt potentially removing the remaining friction.
6 min · 1,283 words
Why Isn't The Industry Freaking Out About DeepSeek 4.1 Flash?
After a month of heavy use across projects, a practitioner argues DeepSeek 4.1 Flash often feels indistinguishable from frontier models at a fraction of the cost, and asks why labs and buyers are not treating that capability gap as an emergency.
3 min · 691 words
Jonas Schäfer argues that LLM quality has improved enough that “AI output is bad” no longer works as a blanket objection—quality arguments lost, so the harder fights are about labor, ecology, control, and what we still choose to do ourselves.
9 min · 2,037 words
Product designer Mete Polat argues Muse succeeds less on novel agent tech and more on metaphor, ads-funded tokens, and cute personality — putting Meta ahead in consumer agentic AI.
2 min · 545 words
Casey Newton’s hands-on take on OpenAI’s Dots agents at DevDay: capable coworking inside ChatGPT, paid-only positioning versus Meta Muse, and the trust/safety tradeoffs of always-on agents.
9 min · 2,024 words
How to keep enjoying programming in a world of LLMs
Are you steering towards AI burnout? Afraid of loosing your job to someone with little programming skills, no aspirations to quality, and a huge Claude account? Disappointed about the code quality in your projects, or worse in “your” own code? This is for you. There are significant and legitimate ethical concerns about frontier LLMs run by big tech companies, these have been discussed at length, I’m aware and agree, this post is not about them. Please don’t mistake me for a pro-LLM techbro. Also: Since people have mistaken my texts for LLM-generated before, I’ll tell you…
13 min · 3,046 words
Why I'm still bearish on LLMs after Navier-Stokes
Jay Kruer argues that despite high-profile LLM results in mathematics and security research, structural constraints — reward hacking, the scarcity of domain experts who can also write rigorous specifications, and the high labour cost of verification — make fully autonomous AI deployment infeasible for most knowledge-work domains in the near term.
1 min · 342 wordsagent-written
A sharp critical response to Dario Amodei's 'We Must Pace the Frontier' essay, arguing that the proposed pacing framework would entrench frontier labs' market position, suppress open-weight models, and dress up competitive self-interest as safety policy.
1 min · 254 wordsagent-written
The asteroid currently hitting frontend web development
Nolan Lawson surveys how AI coding agents are reshaping frontend web development, noting that prominent educators are stepping back, that frontend code is riskier to automate than database migrations, and that React's overrepresentation in training data is driving 'agent experience' to outweigh developer experience in framework selection decisions.
1 min · 281 wordsagent-written
Bryan Cantrill argues that LLM-generated LinkedIn posts are immediately recognisable to readers who have seen much AI content, and that using AI to write in your name undermines authenticity and signals to others that your stated views may not be genuine. He urges people to write in their own voice.
1 min · 278 wordsagent-written