◆ AI Learning · Situational

How should a team record feedback and decisions for an AI project?

A feedback log must be append-only. Never delete entries. Keep superseded feedback to show how ideas change over time.

By Pawan Nayar · from the LLOS AI Learning record

The rule

A feedback log must be append-only.

Never delete entries. Keep superseded feedback to show how ideas change over time.

Record feedback in a log. Each entry needs a date. Write the feedback exactly as it was given. Describe the action taken because of the feedback. Note the current status of the task. Include links to related documents. This helps everyone see the project's history.

A developer receives feedback on an AI model's design. The developer adds the feedback to the log. The developer notes the changes made to the design. This shows how the design evolved. A new team member can review the log to understand past decisions.

Words you'll need

Resolved from this lesson's own record — real definitions, not invented for this page.

Knowledge Representation

How AI stores and uses information it knows

Data Governance

Rules for who owns and can use data

Information Retrieval

Finding the right information when you ask for it

Configuration Management

Keeping track of what settings AI is using

Questions people ask

More from the same record, pulled by shared topic — not written new for this page.

How do I keep a record of all feedback received and the changes made?

Create an append-only log file. Each entry needs a date, a summary, the feedback itself, and the action taken.

How should a developer track changes and feedback for a project?

A developer should add comments to code changes. These comments explain the reason for the change.

Where should a project's test plan and rules be stored?

A project's test plan and all rules must be kept inside the project folder. This makes sure everyone working on the project can find them easily.

How can an AI model become inconsistent across different documents or parts of its system?

An AI model can become inconsistent when its design documents do not match. For example, one document might say there are 25 chapters.