Project 2501 Core timeline archive

Stopped pausing for review after every small feature and changed to a workflow where related features are implemented, fixed, and tested together by AI.

Because having a human intervene for every small connection difference meant spending more time coordinating traffic than implementing.

Implement an Export that carries conversations and attachments together, plus encrypted Backup and Restore to another environment, then run a recovery test.

Stopped repeating a full verification cycle for every small defect. The new approach is to support the response formats together and perform one final verificat…

Because the problem has been narrowed down not to the recording or context system, but to the final step that interprets each AI provider’s specific response fo…

Refine the connection processing so GPT responses are saved correctly, then confirm that conversation continuity across Claude and GPT survives a restart.

Removed real-time memory extraction from the launch requirements and made complete ownership of the raw record the highest priority.

If the original text remains, it can be reorganized later; if the record itself is missing, the reasoning behind a decision cannot be recovered.

Complete a safe recording path that always keeps input locally while ensuring confidential information is not sent to external AI services.

Changed from centering memory on fine-grained statements to reviewing a bounded range of logs and saving what changed semantically since the previous state.

Because preserving a large number of small decisions is difficult to use for long-term judgment if it does not reveal what was being pursued or why the directio…

Finalize a new memory structure that preserves purpose, current state, reasons for decisions, and trajectory changes as differences from the previous state.

Rather than expanding a proprietary execution agent, prioritize using a proprietary conversation interface as both entry and exit, and accurately preserving the…

The execution layer can be substituted with existing AI services, but a separate mechanism is still needed to preserve one person’s decisions and context across…

Design a minimum configuration that saves conversations from the proprietary interface and brings related past decisions back into the next response.

Looking at real use, simply increasing the number of records would not reduce the burden, so the design was expanded toward managing the progress logs of multip…

To reduce the burden of humans continuously connecting multiple AI systems and threads.

Proceed to the next Work Loop that connects task-progress logs to prompt generation, report ingestion, and human review.

Moved beyond the first daily sync check and reached a point where the full local flow—from prompt generation to importing implementation reports and organizing …

The portion that could be implemented safely is now in place, so I decided the next stage is to use it in practice and identify its value and shortcomings rathe…

Integrate Project 2501 Core into real development work for several days and observe where it helps and where it gets stuck.

Moved from finalizing the design into the first execution loop that reads records and connects them to the next action.

To build a foundation that preserves work logs and decisions instead of losing them, then uses them for the next implementation, communication, and decision.

Use the daily sync in real work and check whether it helps with everyday implementation, communication, and decisions.

Does the value of work logs leading to the next action come through?

Advanced from a concept memo to a design package that can be handed to the next implementation AI.

Because a foundation that accumulates decisions and work logs as it is used needs memory, auditing, permission management, and evaluation from the beginning.

Freeze the design package in Git and begin implementing the first CLI and the skeleton for memory, auditing, and permission management.

Does this explanation communicate what I am trying to build?