How to predict what PostgreSQL would do with a query without running it — the statistics the planner reads, where they live, and how an offline analyzer reconstructs the plan from collected pg_class, pg_indexes, and pg_stats data, plus the honest boundary between structural prediction and the live cost model.
Notes from a Tel Aviv meetup talk on AI-first coding in 2026: why developer skepticism is mostly outdated, where the real concerns sit (trust, security, fun), and how to share adoption inside a team without mandating it.
Claude Code Workshop & Best Practices Speaker: Evgeny Potapov, ApexData co-founder & CEO
Once the layers from Part 1 are in place and the code from Part 2 has been written, the on-call experience changes. Part 3 of a series on observability strategy: the practices that reduce the rate of escalations from on-call rotations to the developers who built the system.
Observability is not a tool you buy; it is code you write, and a meaningful fraction of the code in a working production system. Part 2 of a series on observability strategy: how much code is instrumentation, what that means for how a team works, and what it costs in development time.
An observability strategy designed from the people the system serves, not the boxes it runs on. A top-down tour of the layers — user experience, business signals, tracing, service monitoring, infrastructure, user feedback — and what each one answers.