Free · 2 minutes
Method reviewed August 29, 2026

Is your product context ready for an AI coding agent?

Product context is ready when a builder can trace the customer evidence, product decision, scope, delivery context, and expected learning. The agent should not need to guess why the work exists.

Start the five-question checkRead the field guide

No account. No data saved. One reusable handoff at the end.

The context chain
  1. 1LearnCustomer evidence
  2. 2DecideDecision rationale
  3. 3DefineScope and constraints
  4. 4BuildDelivery context
  5. 5Learn againLearning loop
One broken link can make a correct implementation solve the wrong problem.

The five-question review

Turn a readiness score into a useful handoff.

Answer Yes only when a person or agent can inspect the artifact, source, or owner. Choose Unknown when the team cannot verify it.

Progress0/5

Learn · 1 of 5

Not answered
Can the builder inspect the customer evidence behind this work?

Relevant calls, tickets, research, product data, or source records are linked and current.

What good looks like: A source link, date, and a short statement of what the evidence supports.

Direct answer

What should an AI coding agent know before it builds?

It needs five inspectable handoffs. Repository context explains the code. These handoffs explain the product choice.

  1. 01

    Learn

    Customer evidence

    A source link, date, and a short statement of what the evidence supports.

  2. 02

    Decide

    Decision rationale

    A reviewed decision record with an owner, rationale, trade-offs, and open questions.

  3. 03

    Define

    Scope and constraints

    An outcome, explicit non-goals, constraints, open questions, and observable acceptance checks.

  4. 04

    Build

    Delivery context

    One reviewed brief in the delivery environment with source links and bounded permissions.

  5. 05

    Learn again

    Learning loop

    A release signal, customer-response measure, review date, and owner for the next decision.

One method, two users

People review it. Agents can call it.

The visible check and the page tool use the same questions, score, safeguards, and reusable summary. The tool accepts only four answers per handoff and stores nothing.

For a person

A guided five-question review

Inspect one handoff at a time, see what good looks like, then copy a concise review into the next conversation.

For an agent

A narrow, verifiable page tool

Call assess_product_context_readiness, receive structured actions, and show the same result on the live page.

Boundary: The score starts a review. It does not approve the work. People still choose the bet, approve permissions, and review consequential changes.

Questions

Product context readiness FAQ

What product context should an AI coding agent receive?
Give the agent inspectable customer evidence, a reviewed product decision, scope and constraints, acceptance checks, delivery context, and the expected learning after release. Keep source links and review owners visible.
Does a ready score mean an agent can work without human review?
No. Ready means the work has enough bounded context to begin. People still approve the product decision, permission scope, consequential changes, and the result.
How is product context readiness scored?
Each of five handoffs scores two points for Yes, one for Partly, and zero for No or Unknown. Eight to ten is ready only when the decision rationale and scope are not missing. Five to seven is partly ready; zero to four is not ready yet.
Is this check specific to Zentrik?
No. The method is tool-neutral. Use it with a document, issue tracker, repository, or product system. Zentrik is one way to keep the full decision chain connected.

Keep the context connected

Carry the customer reason into delivery, then return the result to the next decision.

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