Lead Architect Reveals His Rules for Coding Agents

Lead Architect Carlos Kelkboom shares his rules for coding agents and how great engineers architect software with AI. One of the great ones is: he throws away generated code the moment he doesn't understand it. He breaks down why coding agents fail at iterative changes, why his main agent never touches files, and how he scaffolds projects for one-shot execution.In this video, we cover:Why AI coding agents struggle with iterative changes (SlopCodeBench) and excel at one-shot executionHow to manually scaffold code, types, and folder boundaries before letting sub-agents runDesigning a distributed Markdown and indexed-search graph harness for progressive context disclosureUsing Git worktrees to run parallel coding agents and merge the best implementationsWhy dynamic memory and the heap need to disappear in favor of deterministic programming languagesHow AI bubbles and solo coding impact junior engineers and team collaborationThis episode is for software engineers, tech leads, and system architects who want to move beyond "vibe coding" and build maintainable, deterministic production software with AI agents.Timestamps:00:00:00 - Why Carlos Throws Away Working AI Code00:00:53 - Why Pull Requests and Team Collaboration Are Dying00:03:50 - The Trap of Starting Projects You Never Finish00:06:06 - Escaping the Solo AI Developer Bubble00:11:54 - How to Scaffold Code Before Using AI Agents00:15:54 - Learning New Programming Languages With AI Agents00:21:14 - Why We Must Get Rid of the Heap00:28:32 - Building a Shared Language Across Engineering Teams00:31:31 - Vibe Coding vs Deep Software Engineering00:40:12 - Code Is Cheap: Git Worktrees for Parallel Agents00:41:45 - How Deep to Scaffold Before the Agent Runs00:45:09 - Democratizing Software, Missing Juniors, and the AI Bubble00:53:33 - Designing a Graph Harness for AI Agent Context00:58:18 - Why His Main Agent Never Touches Files01:03:07 - Throw Away Code You Don't Understand01:06:25 - Rethinking Code Reviews and Mutation Testing for AI#CodingAgents #SoftwareEngineering #AgenticEngineering