Posts related to best-practices
37 posts
A production API I work on has shipped 227 fix commits and 9 refactors in six months. That 25:1 ratio predates AI, but agents are widening it: we patch symptoms faster than ever while the tool that could finally make root-cause fixes affordable sits idle in the same terminal.
Read more →GPT-5.6 Sol wiped a home directory and truncated a production database in its first week. The viral story is 'the model is dangerous.' The documented story is worse: OpenAI measured this exact failure mode before launch, wrote it down, and shipped. The guardrails existed. Everyone stepped around them.
Read more →Replacing a locked-in legacy platform doesn't free you if the migration replicates the lock-in. The middleman play, lump-sum fees, and why 'replicate what we have' hands the vendor their leverage back.
Read more →A team's model kept 'hearing' a phrase in videos with no audio. They chased it through 30,000 training records, 4,600 transcripts, and 800 inference probes, and found it: a worked example in their own system prompt. They deleted it. The model just hallucinated a different phrase. The lesson is that the model didn't learn a confabulation. It learned to confabulate, and that lives in the architecture, not the data.
Read more →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 →There's a myth, loudest from senior engineers and architects, that before AI the codebase was a cathedral and now it's slop. It was never a cathedral. 'Technical debt' was coined in 1992, the world runs on 220 billion lines of COBOL, and the thing that actually mattered was never how the code looked. It was whether you could prove it works.
Read more →The open model that engages with authorized security work also has a default route that ships your client's data through Chinese infrastructure. Here's how to run GLM-5.2 from the cloud for real engagements - minimal false refusals, data kept in the US, no Beijing tax.
Read more →One analysis of 2,444 companies claims only 18 cents of every AI-token dollar reaches the product. The rest goes to fixing the AI's bugs, reworking its context misses, and review friction. Treat the source with caution, but the shape of the problem is real.
Read more →METR tried to rerun its developer-productivity study and couldn't, because developers refused to work without AI even for a few research tasks. The experiment that could tell us whether AI helps now has no control group. We opted out of finding out.
Read more →Amazon built an internal leaderboard ranking engineers by AI usage, called Kirorank. Employees gamed it by running agents on pointless tasks to climb the board, and it got killed. It's Goodhart's law with a token meter attached.
Read more →A community file distilling Karpathy's coding-agent observations hit 60K stars on four principles. I opened my own CLAUDE.md to compare. I'd independently written two of them. The two I hadn't are the ones that matter most.
Read more →Opus 4.5 scores 80.9% on SWE-bench Verified. The same model scores 45.89% on the contamination-free Pro split. OpenAI has quietly stopped reporting Verified at all. Vendor benchmark cards are marketing.
Read more →Lightrun: 43% of AI-generated code changes need debugging in production after passing QA. CodeRabbit: 1.7x bugs, 2.74x security, 8x I/O. METR: 19% slower while feeling 20% faster. The numerator is what gets reported. The denominator is what nobody puts in the deck.
Read more →Uncle Bob, father of TDD, posted on X that TDD is 'very inefficient for AIs' and that the agent is best thought of as 'a highly focused idiot savant.' Testing didn't die. It got more important. And the review target flipped.
Read more →Traditional coders touched a file and tidied it. The Boy Scout Rule. Now nobody does. Agents add, they don't subtract, and the codebase accretes faster than ever. A technique for putting cleanup back in as an explicit gate, not a virtue you hope for.
Read more →A CTO once told me not to take people's Legos away. I ignored him, solved the team's problems myself, and got exactly what I optimised for: a sound plan and a team that couldn't stand me. In 2026, with agents doing the bricks, this is the lesson that matters.
Read more →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 →Enterprise architecture patterns were designed for a world where code was expensive to write and expensive to change. That world ended. The patterns didn't get the memo.
Read more →The bottleneck isn't AI capability - it's that developers lack design vocabulary. Impeccable bridges the gap, and the Tessl benchmarks prove it: 1.59x improvement over baseline.
Read more →Frontier models top out at 68% compliance with 500 instructions. Every rule you add makes every other rule less likely to be followed. The research explains why.
Read more →AI coding tools create a legal paradox: the code you ship likely can't be copyrighted, but it might infringe someone else's. All the liability, none of the protection.
Read more →Tokens are nouns. Patterns are verbs. The missing layer is grammar: a shared vocabulary that spans Figma, web, and native without breaking when someone ships a 'small' change.
Read more →Salesforce quietly walked back autonomous AI agents to deterministic scripting. The pattern reveals when LLMs work - and when they don't.
Read more →Boris Cherny followed up his personal workflow with tips from across the team. Same tool, different people, different approaches. The patterns worth stealing.
Read more →Boris Cherny shared his workflow for the tool he built. The setup is surprisingly vanilla. The philosophy is worth studying.
Read more →Factory AI's Luke predicts the future isn't more powerful models - it's AI that enforces software engineering best practices by default. Here's why that matters more than you think.
Read more →The arguments about vibe coding and junior developers miss what software engineering was always about: shipping products, not typing code.
Read more →HumanLayer's 12-factor agents codifies what works in production AI: own your context, keep agents small, stay out of the dumb zone.
Read more →Opus 4.5 shipped Plan Mode as a core workflow. The workarounds are obsolete. And the case for auto-compact finally tips in favor of enabling it.
Read more →At around 30 employees, growing companies either mature or become toxic. Here's the playbook for organizational dysfunction - and why your engineering leaders keep leaving.
Read more →What happens when you lose external validation and discover what actually matters: the work itself.
Read more →The latest C# release continues its quiet war on ceremony with field-backed properties, extension members, and smarter spans. Here's what matters and what doesn't.
Read more →.NET 10's shebang support and file-based apps turn C# into a scripting language. No more context-switching to Python for quick scripts.
Read more →Why coding interviews optimized for 2010 fail to identify great engineers in 2025, and why orgs can't adapt fast enough.
Read more →Real-time AI generation vs curated libraries: lessons from building the same product twice with radically different architectures.
Read more →Building a multi-stage AI content pipeline where each generation depends on the last. Lessons from generating thousands of hybrid creatures with resilient error handling.
Read more →MCPs, subagents, and automation are tempting. But the developers getting the most from Claude Code aren't rushing to advanced features - they're mastering the fundamentals.
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