AI for Developers

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AI for Developers

Fabled Too Hard? How I Stay Engaged in AI Development

About three years into AI adoption, I've learned what burns me out, what speeds me up, and how I stay engaged in agentic development work.

AI for Developers

In learning how to work with AI agents, my team discovered how much of our team's experience had never been written down before.

AI for Developers

Let's look back on 2 months of agentic development on a HIPAA app: what we let an AI agent ship, and where humans stayed in the loop.

AI for Developers

Using spec-driven development, we cut up a large feature into vertical slices. It made our code delivery efficient & easy to test.

AI for Developers

While I haven't figured out how to replace my entire job with "loops" yet, I started with an MVP for my daily SDLC "loop."

AI for Developers

Using LLMs and AI agents can accelerate our output exponentially. But there is a dangerous side effect to this velocity.

AI for Developers

Strangely, designing a useful agent loop turns out to be eerily similar to designing feedback loops in "pre-AI" software engineering.

AI for Developers

I'm not all that convinced I'm all that much faster with AI. The code comes out faster, sure. But the code was never the whole job.

AI for Developers

I recently wrote about my client team's decision to make human code review optional. Enough time has passed to share some honest reflections.

AI for Developers

AI reads code better than humans can, and Grep is 10,000 times faster than human eyeballs! What do we find joy and pride in now?

AI for Developers

The insight isn't just about adding AI analysis to your tooling. It's about deliberating on what problem you're asking it to solve.

AI for Developers

In software's history, the limit on what you could ship was how fast you could type and build. Execution got cheap. Attention got expensive.