Why Prompts Break Long-Running AI (And What Replaces Them)

Most AI development today is still prompt-first — great for short tasks, fragile for long-running systems.

In this video, I introduce a different approach: constitution-driven AI.

Instead of relying on ever-longer prompts, we design AI agents with an explicit constitution — a stable rule set that governs behavior over time. This pattern is especially important for long-running agents, complex codebases, and systems where consistency and safety matter more than clever outputs.

We cover:

Why prompt-first AI breaks down as systems grow

What a “constitution” is — and how it differs from a system prompt

Why long-running agents require governance, not just instructions

A real-world workflow for deriving a constitution from an existing project

How this looks in practice using modern AI coding agents inside VS Code

When this pattern does — and does not — make sense

This isn’t a tool demo or a hype video.
It’s an architectural pattern for building AI systems you can actually trust at scale.

If you’re working with AI agents, autonomous tools, or large codebases, this mental model will change how you think about AI-assisted development.

Chapters (optional but recommended)

00:00 Why prompt-first AI breaks
00:40 What a constitution is (and isn’t)
01:20 Long-running agents explained
02:00 Deriving rules from real systems
03:00 Governed execution in practice
03:40 When to use this pattern

Who this video is for

AI developers and architects

Engineers working with long-running agents

Teams scaling AI beyond one-off prompts

Anyone frustrated with brittle AI behavior

#AIEngineering #AIDevelopment #AIArchitecture #AutonomousAgents
#LongRunningAgents #ConstitutionDrivenAI #AIGovernance
#AgentDesign #PromptEngineering #ClaudeAI #VSCode