Twindem Team FAQ for controlled AI delivery --:-- UTC
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Twindem FAQ

What does Twindem track during an agent run?

A run can record the execution client, run role, provider, model, device, status, outcome, timing, summary, error summary, token usage, and cost.

A run can record the execution client, run role, provider, model label, model ID, device, status, outcome, timing, summary, and error summary. Usage can be attached to that run: input tokens, output tokens, cached input tokens, total tokens, cost, and whether the value is estimated.

This lets teams connect AI activity to real delivery work, instead of only seeing a monthly provider invoice disconnected from projects and tasks.

Related questions

If our developers already use Codex or Claude Code, why do we need Twindem?

AI coding tools help individual developers move faster. Twindem adds the company layer: board items, phases, second-agent review, evidence, usage, cost, and audit events attached to the work.

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What does controlled AI delivery mean in practice?

Controlled AI delivery means AI work starts from a delivery item, moves through a defined workflow, and keeps the useful record attached: runs, summaries, findings, evidence, usage, cost, comments, handoffs, and board events.

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Why is the second agent important?

The same agent that produces the work should not be the only reviewer of that work. Twindem separates implementation and review so a second agent can challenge the output, inspect risks, open findings, and drive a fix loop before human approval.

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Can Twindem turn architecture work into development tasks?

Yes. Architecture work in Twindem is not just a document. It can produce concrete development task proposals, with rationale, scope, dependencies, and evidence expectations, so the team can approve what should become delivery work.

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