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The operating model

Questions, answered without theater.

Solv changes when a team reflects, what AI is allowed to do, and how an organization decides whether improvement actually happened. Those choices deserve direct answers.

01What is a continuous retrospective?

It is an improvement practice that captures useful signals while work is happening, then lets a team interpret and act on them deliberately. The reflection is continuous; the team does not have to wait for a calendar meeting to preserve context.

02Does Solv eliminate retrospective meetings?

No. A live conversation can still be the right place for collective sensemaking. Solv removes the meeting’s burden of being the only place where memory, emotion, evidence, and action must all appear at once. Teams can meet when conversation adds value, with the signal already intact.

03How does a signal become action?

A person captures friction or an observation in the flow of work. AI processors may enrich it and propose themes, actions, experiments, or other next moves. A human resolution accepts, rejects, or parks the proposal. Only accepted work becomes a commitment, and later evidence records what actually happened.

04What kinds of work can come out of Solv?

The action model can express a feature, fix, research spike, process experiment, or another explicit commitment. Integrations can carry approved work into delivery tools. The important boundary is that an integration acts on a human resolution—not on an unreviewed model response.

05What does AI do?

AI enriches. It can organize signals, map affect to content, look for themes, challenge a proposed interpretation, recall relevant signed history, and suggest executable next steps. Every such output remains a proposal or annotation with provenance.

06Can AI decide for the team?

No. This is enforced in the event-ingestion boundary, not left to interface copy or a prompt. Processor-authored events can enter only through proposal and annotation doors. A human Resolution event is the sole promotion path from proposal to team truth.

07Why is a human approval button not enough?

Because a button is cosmetic if the model can write directly to the underlying record or trigger action elsewhere. Solv separates proposal events from resolved truth at the kernel level, records who made the decision, and preserves the rejected and parked paths as part of the history.

08Does Solv store personal identity on the ledger?

No. Ledger participants are pseudonyms. A connector may need a separate identity map to translate a workplace identity into a pseudonym, but that map remains outside the ledger. It is the only place where both identities may meet.

09Does Solv profile individual emotions?

No. Emotion attaches to content, never to a participant. Trends and research use aggregates. Solv is designed to help a team understand the character of a signal without creating a behavioral or emotional profile of a person.

10Who sees coaching nudges?

Only the facilitator surface. A coach.nudge never reaches team event feeds, catch-up streams, or exports. This routing boundary is tested because a private facilitation observation can become harmful if it is broadcast as team judgment.

11What does “verified history” mean?

Events form deterministic hash-linked history, and per-team commitment chains are signed. Any feature that relies on prior history—opening a new cycle, exporting work, or producing a learning corpus—must verify the chain first and refuse to proceed when the record has been altered.

12How does Solv know an improvement worked?

It does not treat agreement as impact. Solv’s evidence hierarchy is impact over completion over acceptance. A proposal that was accepted but never completed becomes negative learning data; a completed action still needs an observed outcome before the organization can claim improvement.

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