Offering · Value & decisions

AI for Product Owners, with decisions kept human.

For a product owner, AI risk lies in decisions and commitments. AI can draft; the product owner owns prioritisation and what is promised to stakeholders. We help product owners move faster without losing the evidence behind every decision.

See the five tiers How you'll know it's working
Who it's for
Product owners, product managers and portfolio leads.
Where the risk lives
Invented requirements, unsupported claims and stakeholder commitments.
What stays human
Prioritisation, scope and anything promised to stakeholders.
Your first result
A reviewed story or stakeholder update, traced to real evidence, on day one.

The engagement

Five tiers, from one product owner to the portfolio.

Each tier ships something your product team keeps. Open "trust controls" to see how identity, guardrails, evaluations, observability and cost are handled at that tier.

1

Day one · The product owner alone

Orientation

A safe, accountable way to start using AI, without handing over decisions.

We shipA business AI setup under the product owner's own login, a clear boundary for customer, roadmap and commercial data, and a first reviewed artifact traced to real evidence.

Trust controls
Identity
A business AI plan under the product owner's own login. No personal accounts or shared logins.
Safety & Guardrails
Customer interview and feedback data is anonymised. No confidential roadmap, pricing or commercial data goes into unapproved tools, and training on data is off. Nothing reaches stakeholders without the product owner's review.
Evaluations
Outputs are checked against product knowledge and sources the product owner knows well. Any requirement, insight or claim that can't be traced to real evidence is rejected.
Observability
Prompts that worked are kept, and AI-drafted stories, summaries and stakeholder updates are marked.
FinOps
One seat, or the company's existing plan.
2

Day two · With the team

Implementation

Bring AI into the work with the team through shared agents and skills, so product work is transparent and consistent.

We shipShared product agents and skills (a story writer, feedback synthesiser and release notes drafter) with named owners, plus a team agreement on what AI may draft.

Trust controls
Identity
Shared agents and skills have named owners; team members use them under their own logins.
Safety & Guardrails
Prioritisation, scope commitments and stakeholder promises stay with the product owner. Every requirement or insight cites its source evidence, and AI involvement is visible to the team.
Evaluations
AI-drafted stories are checked against the Definition of Ready and INVEST criteria, with team feedback from refinement.
Observability
Artifacts are traced to source evidence (interviews, feedback, tickets) and the agent or skill that produced them.
FinOps
Shared team seats, with usage reviewed alongside the team's regular retrospective.
3

Two-week engagement · The product owner's reusable kit

Distillation

Faster delivery, fewer tokens and more consistent product artifacts.

We shipTemplates and skills for product vision, discovery synthesis, user stories with acceptance criteria, backlog refinement, prioritisation rationale, release notes and stakeholder updates, filled from real product context.

Trust controls
Identity
Every template and skill has an owner and a version; every artifact shows which template and sources produced it.
Safety & Guardrails
Anonymisation, evidence citation and "product owner decides" boundaries are built in. Templates leave no room for invented requirements or fabricated customer evidence, and stakeholder-facing output has a review step.
Evaluations
Reference inputs (interview notes, feedback sets, backlog items) with known good outputs. Checks confirm stories meet the Definition of Ready and insights match source feedback.
Observability
Usage shows which templates are adopted, skipped or rewritten; artifacts trace to the template, inputs and evidence.
FinOps
Tokens and time per artifact, measured before and after: your proof of value and baseline.
4

A few weeks · Across the product or portfolio

Expanding

Extend the kit across the portfolio and connect it to where product evidence and work already live.

We shipRead-only connections to Jira, Azure DevOps, Confluence, customer feedback and analytics, a cross-product traceability view, and cost reporting per product or value stream.

Trust controls
Identity
Connections use scoped service identities, read-only by default. The product owner remains the approver.
Safety & Guardrails
Customer data stays anonymised; commercial data is only processed in approved tools. A human signs off before AI updates any backlog, and no commitment leaves the team without product owner approval.
Evaluations
Tier 3 reference inputs are re-run whenever templates, connectors or models change, with spot checks of insights against source data.
Observability
Every story, insight and prioritisation decision is linked to its source data and backlog item.
FinOps
Costs are tagged per product or value stream and reported to sponsors against the Tier 3 baseline.
5

A few months · The product practice and portfolio

Scaling

Govern AI-assisted product management as a practice across the portfolio.

We shipA register of product templates, skills and agents, policies for evidence standards and external commitments, and outcome measures that link AI spend to product value.

Trust controls
Identity
A register with owners, versions and permissions, tied to company login and access reviews.
Safety & Guardrails
Customer privacy, evidence standards and approval rules for external commitments, aligned with frameworks such as ISO/IEC 42001 or the NIST AI RMF.
Evaluations
Outcome measures: adoption, customer outcomes or delivery predictability against a baseline.
Observability
Decisions are traceable from customer evidence through to delivered outcomes.
FinOps
Cost per artifact, feature or product outcome, reported alongside product value.

Why Context Compression matters.

When stories, insights and stakeholder updates come from templates that require evidence and preserve decision rights, stakeholders can trust the artifacts, not just the person who wrote them.

The reference inputs and baselines created here are what later tiers use to connect AI cost to product value.

Value evidence

How you'll know it's working.

Measured against the baseline set in Tier 3, so the numbers stand up to scrutiny. How we make ROI trustworthy

Time per artifact

Stories, syntheses and updates, before and after the kit.

Readiness and rework

Share of stories meeting the Definition of Ready first time.

Evidence traceability

Share of decisions and claims linked to real customer evidence.

Product outcomes

Adoption, customer outcomes and delivery predictability.

Start with one product owner and one artifact.

Day one ends with a reviewed, evidence-backed story or update your team can use.

See what day one looks like
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