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Spending 3 months coding by hand

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Why This Matters

This article highlights a developer's three-month retreat focused on coding without AI, emphasizing the importance of deep understanding and hands-on experience in programming. It underscores the evolving role of AI in software development and the value of foundational knowledge amidst rapid technological advancements. For the industry and consumers, it serves as a reminder of the need to balance automation with core skills to foster innovation and maintain control over complex systems.

Key Takeaways

Brooklyn, New York. March 2026.

I decided to move to Brooklyn for a coding retreat.

There were some personal reasons that brought me back to the US. But rather than heading immediately back to work, I wanted to take some time to focus on coding things mostly without AI — at precisely the time when many successful programmers are saying programming is a solved problem.

Given that I’m now six weeks through this retreat, I’ll also take some time to explain what I’ve been doing in that time.

Aily Labs

For the past two years, I’ve been building AI agents at Aily Labs in Barcelona alongside some super talented engineers. One of my first projects was building a web search agent we could use internally in early 2024… almost 6 months before Anthropic’s Building Effective AI Agents article came out and a year before OpenAI’s DeepResearch came out! We were also early on Cursor, early on using LLMs to make knowledge graphs, and constantly testing out new approaches for our use cases.

One of my favorite parts of working at Aily was leading a weekly journal club. I chose to present papers that described how open source LLMs were built, including DeepSeek R1, Ai2’s Olmo 3, and Meta’s Llama 3 paper. All of these helped us understand the evolving tradeoffs between training models internally or building workflows around SOTA closed models. I was already hooked on LLMs since the first time I tried them in 2023, but I found my curiosity kept bringing me back to learning about how they worked and how to apply them.

A Key Element of the Craft

At the same time as I was learning about LLMs and agents, I was also using them to code. I learned that when writing code “by hand” I was actually doing two things: writing what I wanted and learning the code base. When I used a coding agent however, I would get exactly what I specified in my prompt, for better or worse. By this I mean that if I didn’t know what I wanted exactly, coding agents would be happy to make many assumptions for me. This almost always meant that I didn’t learn as much, and that I wouldn’t have a good grasp of the codebase.

At the exact same time, coding agents helped me iterate quickly and ship software that worked well (after some dutiful testing, of course). They were also, I found, excellent tutors.

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