Say this first
“This OpenClaw update exposed the real problem with AI coding agents. Not whether they can code. Whether we can trust them when they touch real workflows.”
Second screen notes
OpenClaw talking points
Core frame
This is not a “tool update” video. This is a trust video.
You are a founder building VibeSelling, so your lens is: can an AI system be trusted inside workflows that touch customers, money, and growth?
Start on slide 01
Let the audience see the problem before you explain it. Do not over-introduce. Start with the tension.
Connect to VibeSelling
“At VibeSelling, we are building systems that help people turn URLs into customers. If a system touches acquisition, routing, cost, or customer workflows, silent changes are not small bugs.”
Keep it simple
- Users expected OAuth behavior.
- A version changed routing behavior.
- People felt the mismatch through cost/config confusion.
- The rollback fixed the immediate issue.
Use the diagram
Open openclaw-trust-break.excalidraw when explaining the chain: expectation -> silent change -> trust break -> recovery.
Your take
“Power users forgive rough edges. Founders do not forgive invisible behavior changes around money, routing, or customers.”
Who should use it?
- Technical users: try it.
- Beginners: wait.
- Founders: watch how the team handles trust and recovery.
Final line
“Magic gets clicks. Reliability gets customers. That is the real bar for AI agents.”
Fallback line
“The whole story is simple: AI agents are becoming business infrastructure. Infrastructure cannot silently surprise people.”