AI Workflow on Bruce on AI Engineering

AI Development Methodologies Compared: From Vibe Coding to SDD

Wed, 11 Mar 2026 18:00:00 +0800

In early 2025, Andrej Karpathy coined “Vibe Coding” and the AI-assisted development revolution began. By Y Combinator Winter 2025, 25% of companies had 95% of their code generated by AI. But the honeymoon didn’t last — quality issues, technical debt, and project chaos forced the industry to rethink how humans and AI should collaborate on code.

This article is a deep dive into the six major AI development methodologies that emerged from this reckoning. I’ll break down what each one gets right, what it gets wrong, and — most importantly — which one you should actually use. This isn’t a surface-level overview; it’s built from hands-on experience, Martin Fowler’s team analysis, Peter Steinberger’s evolving workflow, and real production data.

High-Frequency Commits: Ship 100+ Commits/Day Without Chaos

Tue, 10 Mar 2026 18:00:00 +0800

AI coding tools have fundamentally changed how fast developers ship code. With assistants like Claude Code generating, refactoring, and testing code at machine speed, many teams now produce 50 to 150 commits per day — and that number keeps climbing.

But here is the uncomfortable question: when commit frequency skyrockets, why do some projects accelerate while others descend into chaos?

Tmux Complete Guide: From Basics to AI-Powered Multi-Agent Workflows

Tue, 03 Mar 2026 10:00:00 +0800

If you work in the terminal, you’ve probably lost an SSH session during a long-running task. Or struggled to juggle multiple terminal windows while debugging. Or watched helplessly as Claude Code’s conversation vanished when your laptop went to sleep.

Tmux solves all of these problems — and in the age of AI-powered development, it has become arguably the most important terminal tool you can learn.

AI Workflow Playbook: From Prompts to Production Code

Fri, 30 Jan 2026 10:00:00 +0800

Most people have been using AI for months, yet they’re still stuck in “ask a question, get an answer” mode. They’ve had plenty of conversations with ChatGPT, but when it comes to real work, the results always feel lacking — answers are too generic, generated code won’t run, or the output screams “written by AI.”

The problem isn’t that AI is bad. It’s that we’re using it wrong.

This article is a practical AI workflow methodology distilled from real-world experience — covering how to ask better questions, how to write effective prompts, how to use AI for programming, and how to deploy AI in enterprise settings. If you’re still figuring out how to make AI genuinely useful, this guide is for you.