This repository was created entirely with GPT-4o as the sole AI collaborator. No Copilot. No Codex. Just raw model output combined with human orchestration.
Despite those constraints, the same workflow was applied throughout, and it consistently produced working code, research receipts, and living documentation.
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Problem Definition (Human):
- I define the issue clearly, including logs, repro steps, or desired outcome.
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Reasoning & Targeting (GPT-4o):
- Isolate the likely source of the bug or design gap.
- Suggest paste-ready code blocks.
- Provide reasoning on file placement and dependencies.
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Execution & Refinement (Me):
- Insert code directly into the repo.
- Sanity-check with local runs and minimal edits.
- Commit results as experimental receipts.
- First-shot success: Many fixes landed on the first attempt — showing that clarity + orchestration beats brute force.
- End-to-end repo creation: From experimental browser agents to reinforcement-flavored scaffolds, every folder here emerged from this workflow.
- Proof under constraints: If it worked with only GPT-4o, the method’s success with multiple tools (Asari + Copilot + Codex) is not chance but inevitability.
This repo demonstrates that human-AI collaboration can scale even under minimal conditions. With weaker models, it still produced breakthroughs. With stronger models and supporting tools, the same pipeline evolves into a frictionless one-shot dev stack.
⚡ This is engineered skill — a reproducible method — not luck.