An opinionated list of Python frameworks, libraries, tools, and resources
SOFTWARE ARCHITECTURE & REFACTORING 3 Domain-Centric Architectures Every Software Architect Should Know The first concern of the architect is to make sure that the house is usable; it is not to ensure that the house is made of brick. — Uncle Bob The expression domain is occurring in software bibles for a very long time now and is heavily discussed in the book Domain-Driven
Or: what broke on my first three attempts so you don't have to repeat it I've built two prediction markets from scratch. The first one crashed on testnet. The second one launched but had zero users for two months. The third one? Actually works. Here's what I learned in the process. Ask yourself three boring but critical questions: Binary outcomes (Yes/No) or multiple choices? Who decides the trut
What Should Humans Design When AI Can Write Most of the Code? AI can now write code. Not perfectly. Not always safely. Not without review. But it can write a great deal of code. It can generate functions, create tests, call APIs, build UI components, handle common errors, and produce large amounts of implementation detail at a speed no human developer can match. This changes the meaning of prog
Claude + Mobile via MCP: Giving the Model Hands on a Real Phone I plugged in a Pixel two months ago, ran one command in Claude Desktop, and watched it open Maps and start navigation to my home address from a single sentence prompt. It was the first time I'd ever seen a language model physically operate a phone. Latency was about two seconds per action; the part that surprised me was the third st
AI-Native Mobile Testing: What It Actually Means in 2026 The phrase "AI-native" has been thrown around in the testing space since 2019. Almost every tool calling itself that just bolts a language model on top of Appium and ships the same brittle XPath selectors with a new label. That's not AI-native testing. That's Appium with a chatbot. This post is about what AI-native actually has to mean to
The Missing Control Plane for Local AI Agents I sat with my Pixel for 20 minutes trying to get Claude Desktop to dictate a Slack message via accessibility. It was miserable. The model was capable. The transport wasn't. That gap — between an AI that can reason and an AI that can actually do — is what I've been working on with Drengr. This post is the version of the argument I'd give to anyone bui
We are currently witnessing a massive shift in AI development. We’ve moved past the "Chatbot" era and into the era of Agentic Systems—AI that doesn’t just suggest text, but actually executes code, moves money, and modifies databases. However, there is a fundamental architectural flaw in how most agents are built today: we are giving "Intelligence" and "Authority" to the same probabilistic model.