_____  _______  _______  _______  _______  _______  _______ 
  /     \|   _   ||   _   ||   _   ||       ||   _   ||   _   |
 |  || |||  | |  ||  |_|  ||  | |  ||_     _||  |_|  ||  | |  |
 |  || |||  |_|  ||       ||  |_|  |  |   |  |       ||  |_|  |
 |  || |||       ||       ||       |  |   |  |       ||       |
 |__|__| |_______||_______||_______|  |___|  |_______||_______|

Why Coding Agents Became the First Real Breakout Success of AI

It is not far off to say that coding agents have been the most visible and widely adopted AI product to date. Agent offerings like Claude Code, Codex and GitHub Copilot are already used across many enterprises. On the other hand, we do not see the same level of success in other white collar domains or in day to day life. We talk about agents doing everything, but very little work has actually been handed off in areas like finance, legal or healthcare.

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How I Use AI Coding Agents Without Vibes

I’m knee deep into AI coding agents and agentic programming. Yes, I have strong opinions about Vibe coding and I’m a big advocate of vetting your code. We are still responsible for our code, and AI doesn’t take accountability away from us. Having said that, today I want to look at the bright side. I have really started enjoying my agents more. I found love in coding without typing code. This was not always the case - I always found auto-completion features more enjoyable than prompting in a terminal.

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Keep your AI assisted workflows simple, stupid

I sometimes end up in programming/AI rabbit holes on Reddit. This weekend I browsed for many, many posts where the point of discussion was AI skill issues. “You don’t prompt well,” “add a Agent.md,” “Ask LLM to re-eval their work,” “Ask to create a feedback loop to optimize initial prompts,” and many more. So many pre-implementation steps. So many guardrails. It’s like baby-proofing a house or, likely, asking the baby to baby-proof the house.

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