The AI Context Loop

In one line: Reviewed context can help humans and agents make better changes; unreviewed output can amplify mistakes.

The useful feedback loop is not “more text means better code.” Retrieve relevant, permitted evidence; measure whether it reduces ambiguity, rework and escaped defects. Watch for stale guidance, misleading generated summaries, mismatched definitions and feedback that simply repeats the agent's assumptions.

Business stakeholders contribute small clarifications and validate diagrams, examples or working slices. The BA reviews AI extraction before sharing; accountable owners approve changes to meaning. Developers contribute implementation constraints, tests and discrepancies rather than treating a generated specification as unquestionable.

The glossary and taxonomy carry stable term identities, qualified definitions and approved revisions. Keep domain-specific meanings distinct when a universal definition would mislead.