We're about to step into a major challenge: if an event is modified simultaneously in both your T-Block system and Google Calendar, which version should be trusted?
In engineering, this is known as the Eventual Consistency problem in distributed systems. An average large model often short-circuits when faced with complex business logic branches like this, producing endless loops filled with countless if-else statements.
1. Bringing the Battle Back to the findings.md Debate
Poorly written code isn't a result of weak technical skills, but of an unclear business flow. We must command this geek architect to stop coding (put down the keyboard) and return to the whiteboard.
"We've entered deep waters. Regarding sync conflicts for calendar events, do not jump straight into writing conditional logic. You must now conduct a thorough analysis and deduction of the conflict resolution strategy for T-Block. We have three schools of thought before us: 1. LWW (Last Write Wins: the write with the later timestamp wins); 2. Local Win (always prioritize manual changes in T-Block); 3. Remote Win (always treat Google as the source of truth).
As a system minimalist, analyze these options and recommend the best one. Document this as the official arbitration code in
docs/findings.md, and include a draft of the code's processing flow (in pseudocode)."
2. The Arbitration Report from the Cyber-Brain
After deep deliberation, the Agent will return its arbitration to you. A good model will typically reject a blind LWW approach at this stage, pointing out that "timestamps from mobile calendar modifications uploaded after a network reconnection have a very high rate of misjudgment."
Since T-Block is built upon the Google ecosystem, it will often produce and save a brilliant record like this:
# [Design Decision] Final Arbitration on Conflict Strategy
**Conclusion: Adopt a 'Baseline Remote Wins with Local Revision Tag' strategy.**
All primary key and macro-level changes (e.g., date, time) will forcibly use data from the Google API as the backbone (source of truth). However, detailed Task Description breakdowns generated locally will be stored in a dedicated extended JSON field. During a merge, only the basic time information will be forcefully overwritten by Google.
3. Forging the Decision into the Code's Backbone
Once the human gives their "Approval."
The decision takes effect immediately. In the next round of coding requests, when the Agent writes the extremely complex aggregate function syncLocalToRemote(), it will no longer be like a headless fly. It will faithfully adhere to the 'Remote Win' principle as the root logic for all fallbacks (catch) and object merging.
Code written this way is clean, bulletproof, and clearly traceable.