I Built an Open Engine That Connects Claude, ChatGPT, and Codex Together

YouTube/Substack · YouTube · Read

• The bottleneck in modern AI workflows isn’t model capability — it’s the integration layer: humans manually shuttle work between Claude, Codex, ChatGPT, maintaining context across each handoff (“the transcript commutes while you wait”).
• Open Engine is a copy-paste handoff framework (no API engineering required) — a seven-part task record that preserves source decisions, visible constraints, an audit trail, and “receipts” (evidence of completion), so each subsequent agent inherits full context rather than starting blind.
• The “one-loop audit” reframes handoff friction: instead of asking “is this automatable?” ask “is the handoff structure good enough for an agent to claim this work?” — the bottleneck is specification quality, not capability.
• Practical takeaway: build task records that outlive individual model sessions; the Open Engine’s handoff structure is the infrastructure layer beneath the model choice.