Give your agent a way to verify its work. This can dramatically improve the quality of output. With this process in place, Claude Code was able to write 90%+ of its code itself. When generating software at a faster rate than you can review it, the bottleneck shifts to proving that it works. @bcherny and team invested enough in verification, we've been able to move fast while maintaining stability. Code reviews aren't going away, but you need to think of it differently. One human reading through line-by-line is no longer going to work as a gate, it needs to evolve into a multi-layered verification system, built with fast deterministic feedback loops for your agents. This is where e2e tests, feature maps (as @poteto has been advocating), property tests and multi-agent adversarial reviews come in. These all provide opportunities to catch errors early and fix them before things get out of hand. You don't have enough eyeballs for the amount of code being written so your focus needs to be on product intent, risk assessment and evaluating evidence rather than reviewing code. Delegate the code checking work to your automated tests, scale your approvals based on risk, and turn your test failures into living evaluations. This approach helps maintain speed without losing reliability. Let the agents do what they do best and let you focus on what makes you irreplaceable: judgement, direction, and ownership. We tried to capture how we handle code review and verification in this writeup. Hopefully it's helpful.

There's been a lot of debate about AI vs human code review recently. Here's some actual data and observations from inside Meta: - Engineers now push ~3x the code they did a year ago. Human review capacity obviously didn't triple. - In an analysis involving 535k+ reviewed diffs, the production-incident rate for AI-reviewed diffs was 1/50th that of human reviewed. - The revert rate for AI reviewed diffs was 1/3rd of the human reviewed. - Median review wall time dropped by 35% compared to human-reviewed diffs. - Experts then looked at every production incident caused by AI-approved diffs. A human reviewer wouldn't have caught any of those issues anyway in a manual review. - Meta's internal coding agent lands ~3,000 diffs a week, and 59% need zero human edits. Human review as default for most code changes is already obsolete, and might even be riskier. Source in comment below.

a weird inversion with LLMs is the models improve faster than the tinkerers when i see people with custom workflows and setups they're all addressing problems that don't exist anymore the person naively using vanilla codex is more likely to be experiencing state of the art

"This is not the time to doom, baby. This is the time to bloom. Intellectually, spiritually, and productively. Put down your anxieties, arrest your neurotic impulses, and decide to be happy about the present, the future, and..." world.hey.com/dhh/what-on-ea…

You can now set Claude Code's output style to Concise. Claude leads with the result, keeps responses short, and still gives full detail when you ask. Turn it on in /config → Output style, or set "outputStyle": "Concise" in settings.json.

I'm so freakin sick of how Claude talks. It's not just annoying, it's infuriating. The honest evaluation: it's the precise mechanism driving my current headache. It's the load-bearing root cause of my daily stress. It's genuinely painful, and that matters.

No model survives the "are you sure?" They all fold instantly.

Over the past month, some of you reported Claude Code's quality had slipped. We investigated, and published a post-mortem on the three issues we found. All are fixed in v2.1.116+ and we’ve reset usage limits for all subscribers.