By Simeon Griggs Houseplants often die from over-watering, not neglect. It is easy to project human needs onto them: "If I am thirsty, they must be thirsty too." But many indoor plants actually benefit from drying out between waterings. Similarly, your empathy can lead to misinterpreting signals from your database. You don't like feeling overwhelmed, so you don't want your database overwhelmed eit
The Autonomous Paradox In 2026, we’ve moved past simple chatbots. We are building Production-Grade RAG pipelines and autonomous agents that can plan, execute, and iterate. But as an architect, I’ve noticed a glaring hole in our "Agentic" future: Identity Sprawl. We are giving agents non-human identities (NHI) with "Full Admin" permissions just to ensure the RAG works smoothly. We are effectively
Agentic Coding Is Not a Trap: I Answered the Viral HN Post With My Own Production Logs I made the exact mistake that viral post criticizes: I gave an agent an ambiguous task and went to make coffee. Came back 40 minutes later to 23 modified files, three broken tests, and a refactor nobody asked for. I'm not telling this to complain — I'm telling it because that day I started keeping logs of my a
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
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
What if your Kubernetes cluster simply refused to run unsigned images? I spent some time experimenting with enforcing image provenance in a small Kubernetes setup using MicroK8s. The idea was simple: Only container images with valid cryptographic signatures are allowed to run in the cluster. For this I used: GitLab CI/CD (build + signing pipeline) Cosign / Sigstore (image signing) Kyverno (admissi
You asked Claude to build a feature. It worked. You shipped it. Six weeks later, you're adding something related, and nothing makes sense anymore. The code is technically correct but completely opaque. You can't remember why anything was structured this way. Claude can't figure it out either — it starts guessing, and the guesses start breaking things. This is the scenario I keep seeing. And it's n