New interview demo · AI agents
Tibo’s AI Agent Workflow Model
Tibo described faster inference, cloud agents, selective autonomy, and the cost of fragmented human attention. This model turns those relationships into a system you can manipulate.
The source
Matthew Berman · Tibo interview
Open on YouTube ↗How to Understand the Next Wave of AI Before Everyone Else
The transcript connects ultra-fast inference, adaptive personal agents, cloud execution, full automation, and human attention as a scarce operating resource.
The exact prompt
One request made the system visible.
Prompt sent in ChatGPT
Build an interactive AI-agent workflow model showing how speed, autonomy, cloud resources, and human attention change the optimal setup.
The finished artifact
Change the constraints. Watch the workflow settle.
This is the working model. Switch workload lenses, move every lever, and follow the transcript evidence back to the exact interview moments.
Built from the spoken ideas in the available timestamped transcript.Interactive controls run locally in your browser.
YouTube Conversation V1 understands the ideas spoken in the available timestamped transcript. This model’s numeric outputs are illustrative scenario calculations, not OpenAI forecasts.