#ai

Nobody knows what the future of software engineering looks like, and that's incredibly uncomfortable. But instead of waiting for someone to hand us the answer, I think the move is to embrace the uncertainty, because these moments of deep uncertainty have historically been moments of extraordinary opportunity.

The best practices for building with AI haven't been written yet, and that's actually exciting. This post breaks down a layered approach to AI-assisted development, from chat to coding agents to agent fleets, with practical tips for getting started no matter where you are.

AI agents like OpenClaw can run continuously on your machine, read your email, push code, and post to the internet on your behalf, often with minimal supervision. I've put together six practical guidelines for using AI Agents without losing control... favor scripts over agents for deterministic tasks, guard against prompt injection, monitor what your agent is actually doing, vet community plugins before installing them, scope permissions tightly, and minimize the data you send. This isn't a "don't use AI" post, it's a "here's how to not shoot yourself in the foot" post.

I'm scared, I'm excited, and I'm exhausted by the pace of change. All of those things can be true at the same time. This blog post is a (hopefully) grounded take on living through AI's inflection point, why the backlash is valid, and why human connection matters more now than ever.

I went from brain dump to a working productivity tool in a single day. Here's how listening to the How I AI podcast pushed me to finally experiment with personalized software, MCP, agents, and skills—and why I think it's time to get on board (with some caveats).

I spent 2025 going from skeptical to genuinely excited about AI tools. My non-tech friends and family spent 2025 learning to hate them. The AI industry has fumbled this introduction so badly that we've turned a useful set of tools into a cultural flashpoint - but the damage isn't irreversible.

I've cracked the code on breaking the eternal cycle - features win, tech debt piles up, codebase becomes 'legacy', and an eventual rewrite. Using coding agents at GitHub, I now merge multiple tech debt PRs weekly while still delivering features. Tickets open for months get closed. 'Too hard to change' code actually improves. This is the story of the workflow.