The Wall Street Journal ran a piece yesterday on JustPaid, a 9-person Mountain View startup. They used OpenClaw and Claude Code to stand up seven AI agents that write code, review it, and run QA around the clock. In one month: 10 major features shipped. Each one would have taken a human engineer a month or more. This story is getting passed around as proof that the autonomous engineering team is h
PostgreSQL Query Rewriting Techniques The previous articles in this series covered performance problems you fix by adding indexes, restructuring joins, or tuning memory. This one is about the queries where the plan is "fine" — every node is doing something reasonable — but the query itself is asking the wrong question, producing unnecessarily large intermediate results or forcing the planner dow
Si usas Claude Code para programar ya sabes lo que pasa: abres una nueva sesión y el agente vuelve a improvisar. El contexto de la sesión anterior desapareció. Le describes la feature de nuevo, asume cosas distintas, y acabas corrigiendo código que nadie pidió. OpenSpec resuelve exactamente eso. Es un CLI open-source que inserta una capa de especificación versionada dentro de tu proyecto. Claude C
DeepClaude: I Combined Claude Code with DeepSeek V4 Pro in My Agent Loop and the Numbers Threw Me Off DeepSeek V4 Pro correctly solves 94% of deep reasoning tasks in my loop… but the latency cost makes it unusable for 60% of my agent cases. Yeah, you read that right. And that completely blows up the narrative of "combining models is always better." Tuesday night I watched the DeepClaude post cli
DeepClaude: combiné Claude Code con DeepSeek V4 Pro en mi loop de agentes y los números me desconcertaron DeepSeek V4 Pro resuelve correctamente el 94% de las tareas de razonamiento profundo en mi loop… pero el costo de latencia lo hace inutilizable para el 60% de mis casos de agente. Sí, leíste bien. Y eso cambia completamente la narrativa de "combinar modelos es siempre mejor". El martes a la
Si tu as 30 secondes. La mémoire versionnée d'un workflow Claude Code a un effet de bord que personne ne signale : une règle mémorisée qui colle au symptôme de manière plausible court-circuite la vérification, même quand elle ne s'applique pas au compteur précis que tu regardes. Je me suis coûté vingt minutes d'exploration SQL la semaine dernière parce qu'une règle de la forme du bug — sans en êtr
This section is the map for the rest of the book. The five stages introduced in the 1.1 chapter overview (parse, analyze/rewrite, plan, portal, execute) are traced here through the actual code: which functions implement each stage, and in what order they get called. The mechanics of each of the five stages are unpacked in later chapters. Here, only the skeleton matters: how a backend starts up, ho
PostgreSQL Internals · Chapter 1 Query Processing Suppose a client sends SELECT * FROM users WHERE id = 1. The path that single line travels before coming back as a result row is longer than you might expect. Inside the PostgreSQL backend, that SQL goes through a five-stage pipeline. Backend entry and dispatch. The backend receives the message from the client and decides which processing path it s