Ai-coding Tag

Ai-coding

Posts related to ai-coding

172 posts

← Back to all posts

Grok 4.5 Trained on the Answer Key

xAI's launch page for Grok 4.5 is a wall of green bars led by a token-efficiency chart. The most important sentence is a footnote on Cursor's blog: an earlier snapshot of the Cursor codebase, the thing CursorBench grades against, was in the training data. The exam graded itself, and the answer key came stapled to it.

Read more →

A Lonely Way to Ship

Anthropic's own engineering lead for Claude Code said the quiet part: as the team leaned into agents, work 'could start being a lonely experience because we all started just working with our agents so much.' The fix they reached for was pair-programming lunches. The company that builds the most-used coding agent on earth noticed it isolates people at scale, and shipped it to everyone anyway.

Read more →

One-Shot Taste: Redesigning This Blog with Claude Fable 5

X is flooded with Fable 5 one-shotting landing pages, and design leaderboards briefly crowned it king. So I handed it this blog. The interesting part wasn't what it generated: it was that it read the site's own design doc and found the site guilty of violating it. What the viral demos get right, what they hide, and why the model's most useful design skill is enforcement, not inspiration.

Read more →

The Fifth Rule

Karpathy's four CLAUDE.md rules went viral: ask don't assume, simplest solution first, don't touch unrelated code, flag uncertainty. The most-upvoted reply added a fifth that quietly reverses the whole point: don't hesitate to suggest a better way. The four rules tame a model that wanders. The fifth one trusts a model that thinks. Which set you want depends entirely on which model you're running, and most people copy the file without checking.

Read more →

The Coding Moat Was Never the Code

Anthropic studied 400,000 Claude Code sessions and found the best users weren't the best programmers. Managers, lawyers, and salespeople land within a few points of software engineers, and management scored highest of all. The skill that transfers isn't syntax. It's knowing what the right thing to build is, which is the one thing a bootcamp never taught.

Read more →

The Expensive Middle: Claude Opus 4.8 vs Sonnet 5

Sonnet 5 lands within a few points of Opus 4.8 on most work and looks 2.5x cheaper, but that discount inverts on real tasks: at high effort Sonnet is so token-hungry it often bills more per task than Opus. The usage squeeze, meanwhile, is self-inflicted: agentic work now fans out dozens of subagents across parallel workstreams. Opus 4.8 became the expensive middle, though its real problem was never the price. It's the position.

Read more →

The Archetype Under the Title

Boris Cherny, who built Claude Code, says engineering, product, design and data science are melting into one role, and what's left is five archetypes: Prototyper, Builder, Sweeper, Grower, Maintainer. I read the list and realised I'm all five, because building solo with agents leaves no one to hand a phase to. The framework is thirty years old. What's new is that it just became the primary axis instead of the secondary one.

Read more →

The Editor Is Now a Host

Cognition killed Windsurf overnight via an over-the-air update, rebranded it Devin Desktop, made the default UI an agent command center instead of a code editor, and shipped an open Agent Client Protocol so Codex, Claude, and OpenCode can all run inside it. The bet underneath: the IDE wins by being the place agents report for work, not by having the best autocomplete. The editor was always the wrong center of gravity.

Read more →

Cutting While Winning

GitLab laid off 14% of its workforce and branded it the 'agentic era': agents now handle review, approvals, and handoffs, so fewer humans sit in those loops. It did this while beating earnings, revenue up 23%. I've argued AI is usually a scapegoat for cuts companies already wanted. GitLab is the case that complicates it - either the first honest agentic layoff, or the most fluent AI-washing yet.

Read more →

One Went Dark, Two Went Open

In the same 72 hours the US export-controlled Fable 5 off the planet, China's open-weight labs shipped two major coding models into the commons: Kimi K2.7 on June 12, GLM-5.2 on June 13. One model went dark behind a national-security letter; two more went open under MIT. The diffusion layer didn't pause for America's panic. It shipped through it.

Read more →

The Fool's Errand

Every hour you spend making the current generation of AI tools more compliant is an hour the next release writes off. I've documented this pattern for a year without naming it: frameworks absorbed, prompt tricks obsoleted, guardrails outlived. Here's the name, the receipts, and the one kind of scaffolding that survives.

Read more →

The Velvet Rope Was a Turnstile

Anthropic just released Fable 5, a Mythos-class model for everyone, eight days after filing its S-1 and days after calling for a brake pedal on frontier AI. The danger narrative ended exactly when the monetization was ready - and one of the three 'safety' classifiers guards the moat, not the public.

Read more →

It Was Always an IPO

Anthropic filed a confidential S-1 on June 1 at a $965B valuation, eclipsing OpenAI. Read backwards from the filing, the last two years stop looking like a safety lab's awkward compromises and start looking like a pre-IPO playbook executed on schedule.

Read more →

The Last Slow Thing

Everything in software got a fast mode this year except understanding what to build. The proof is in the labs' own org charts: the companies selling the models that supposedly end software engineering are paying $600k for engineers to go sit in customers' offices. The bottleneck moved all the way up to the conversation.

Read more →

Benchmarks Are Bullshit

Berkeley just built an agent that games AI benchmarks. Karpathy called it months ago. The best coding model doesn't top the charts, the highest-ranked Chinese models disappoint in practice, and the entire leaderboard industry optimizes for the wrong thing.

Read more →