Long-form thinking on the engineering I actually do — AI agents, backend performance, and product velocity. No fluff, no hot takes for their own sake.
A practical guide to making backends fast: measure first, respect the real cost hierarchy of network over disk over memory over CPU, kill N+1 queries, layer caching deliberately, and know when async, pooling, and backpressure actually earn their keep.
How to build and validate a product fast without creating tech debt you'll regret: scope to one core loop, fake what you can, choose boring tech, instrument from day one, and refuse to abstract before you understand the problem.
A systems-design view of production agents: why naive ReAct loops fall apart, how to design tool interfaces and bounded state, and where to put guardrails, retries, and evaluation so the whole thing stays trustworthy.