[ashed96]

I'm building a startup myself and we vibe code everything, except core/complex parts where AI struggles.

My workflow:

1. Give the agent detailed task + relevant file contexts (so it doesn't waste time searching)

2. Guide it with continuous feedback when it veers off

3. Jump in manually if it's going completely wrong direction

I use Claude Code for the agent work, Cursor for manual edits.

Key insight: AI coding works as well as your architecture does. I make all architecture decisions, file structure, organization -- AI just writes the implementation logic.

Clean architecture = better AI output.

I believe This is becoming the norm because it gives startups massive velocity advantage. That's probably why your CTO is pushing it.

Career impact? As a senior who understands what AI writes, you're gaining superpowers, not losing skills. You were previously bottlenecked by implementation speed and needed other engineers. Now you can be a 10x engineer - as long as you can envision the architecture, AI helps you build it faster.

The key is knowing when to guide vs when to take over. That judgment comes from experience.

[spk265]

Thank you for your response.

If it's ok, could you please share if you follow a certain structure when defining the detailed task for the agent.

[ashed96]

No specific structure - you'll need to experiment based on your project.

I treat it like briefing a senior engineer. Example:

"Currently we have X, Y, Z but it has ABC limitation. We need to support FOOBAR. What are our options?"

Agent suggests 3 approaches.

"Go with Approach 1 but remove the Z part. Implement it."

Try being specific about constraints and current state. The agent fills in the implementation details, but you drive the decisions.