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IDEAIMPACT

Agentic Product Platform

From idea
to impact.

A Product Platform enabled by Agents and Human that turns ideas into high-quality products — faster.

Faster

Shorter idea-to-
impact cycles

Higher quality

Built-in from
the start

More impact

Ideas that ship
and create value

A blue ribbon takes an idea through human insight and agent collaboration inside the Agentic Product Platform, emerging as a realized product.
  1. Human insightPeople shape the idea and define the outcome.
  2. Agents amplifyAgents help turn shared knowledge into working products.
  3. Impact realizedProducts reach users, and real-world feedback informs the next idea.

Product platform.

Four connected stages turn ideas into products. Shared context throughout.

Shared context
  • Data
  • Knowledge
  • Code
  • Learnings
  • Signals
Real-world signals improve the Agentic Product Platform

01 / 04 · EXPLORE

Definition &
Design

Turn ideas into a validated prototype — bringing UX, business, executive and end-user perspectives together from day one.

Led by
Product Builder
9:41
brand
Search for anything
Modern light-grey upholstered chair

Modern chair

€ 120

Modern chair · € 120Try the product demonstration

UX

“Simplify the category picker. Consider auto-suggest as users type...”

Business development

“Explore revenue options (sponsored listings) from day one.”

User research

“3/5 testers missed the CTA. Make the primary action more prominent.”

Executive

“Focus on time to value. What's the simplest version that delivers impact?”

Shared context
  • Data
  • Knowledge
  • Code
  • Learnings
  • Signals
UX, business development, user research and executive perspectives converge in a validated prototype, which is stored in the shared Context layer.

Key features

  1. Cross-expertise alignment

    Internal stakeholders, UX and external user research are fully integrated (e.g. Prototype Feedback, Figma, qlaris.ai).

  2. Product context layer

    Output of all steps in this phase is embedded in the Context layer, ensuring context is retained and leveraged from Idea to Impact.

  3. Validated prototype as the handover

    The output is a prototype that captures agreed intent and becomes the input to Architecture & Specification.

02 / 04 · SPECIFY

Architecture &
Specification

Turn a validated prototype into a buildable, high-quality specification — resolving ambiguity up front.

Led by
Product BuilderAI-Native Engineer

Validated
prototype

Modern light-grey upholstered chair

Product specification review

22:14

Product Builder

You

AI-Native Engineer

Sharing

Architecture Agent

Listening…

“I’ve reviewed the prototype and drafted the epics and features. Shall we walk through the core flows?”

Buildable specification

Product specification

  • Epics12
  • Features28
  • Technical design6
  • Acceptance criteria24
Shared context
  • Data
  • Knowledge
  • Code
  • Learnings
  • Signals
The Product Builder, AI-Native Engineer and Architecture Agent review a validated prototype and turn it into epics, features, technical design and acceptance criteria, connected through shared context containing the prototype, decisions, research and constraints.

Key features

  1. Human + Agent collaboration

    Dedicated agents join (online) meetings by voice, with full access to the Context layer and repository. They act as additional team members, thinking through the solution.

  2. Quality engineered up front

    Specialised agents draft the specification; the Product Builder and AI-Native Engineer ratify the decisions. Correctness, edge cases and architecture are decided before code exists.

  3. Context carried forward

    Every specification is embedded in the Context layer, so the intent captured in Definition & Design flows through to the autonomous build without loss.

03 / 04 · BUILD

Development &
Validation

Turn a buildable spec into validated product increments — autonomously built and continuously validated.

Led by
AI-Native Engineer

AI-Native Engineer

Monitors, validates and steps in when needed

Human oversight

Buildable
spec

Plan

Set up
structure

Tests

Write &
run tests

Implement

Build
features

Eval

0.94Evaluating…

Functional
review

Validate
behaviour

Merge

Create PR
& merge

Validated
increment

v1.4.0
  • Tests passing
  • Reviewed
  • Merged
  • Ready for launch
Shared context
  • Data
  • Knowledge
  • Code
  • Learnings
  • Signals
The agentic workflow plans, tests, implements, evaluates, functionally reviews and merges the specification into a validated increment, under AI-Native Engineer oversight.

Key features

  1. Agentic build pipeline

    Specialised agents plan, implement, test and refine features end-to-end, following a defined workflow with quality gates.

  2. Observability integrated

    Every run is evaluated (LLM-as-a-judge), tested and logged, giving full visibility into quality, speed and costs.

  3. Context carried through

    All code, decisions, test results and learnings are stored in the Context layer, so knowledge compounds from Idea to Impact.

04 / 04 · IMPROVE

Operate &
Evolve

Keep the product healthy, turn user feedback into new value, and continuously improve the platform behind it.

Led by
Product BuilderAI-Native Engineer

Product in use

  • Incidents
  • Alerts
  • Usage patterns
  • Feedback
Shared context
  • Data
  • Knowledge
  • Code
  • Learnings
  • Signals

Maintain the product

Agentic maintenance

  1. Diagnose
  2. Fix
  3. Verify
Planned

Evolve the product

User feedback

  1. Understand
  2. Prioritize
  3. Define

Improve the platform

Agents · Skills · Context · Workflows

  1. Evaluate
  2. Refine
  3. Validate
Incidents, alerts, usage patterns and feedback from the product in use feed shared context: data, knowledge, code, learnings and signals. This context supports three parallel loops: agentic maintenance, planned product evolution through user feedback, and continuous platform improvement.

Key features

  1. Agentic maintenance

    Agents diagnose issues, implement fixes and validate changes, with human oversight where needed.

  2. Feedback-driven development Planned

    User feedback and usage patterns reveal opportunities, shaping new features and improvements.

  3. Platform improvement

    Evaluate and refine agents, skills and context so every stage benefits from what we learn.

Architecture.

Four shared layers. Quality and visibility throughout.

People stay in control - without changing where they work.

Built on

  • GitHub
  • Jira
  • Linear
  • Slack

One feature, from build to approval Illustrative example

Progress of work

Every step, in one Linear ticket.

ENG-120In review
Add context-aware documentation search

Build & Validate Related PR #4827

4 of 6 steps completeHuman review next
  1. Plan

    Complete — implementation plan agreed

  2. Tests

    Complete — checks added

  3. Implement

    Complete — changes ready

  4. Eval

    Complete — evaluation passed

  5. Functional review

    Needs human review

    Your turn
  6. Merge

    Waiting for approval

PR Review & Approvals

The context to make the call.

PR #4827 ENG-120Open
Add context-aware documentation search

Ready for functional review

Intent
Make relevant documentation easier to find.
Impact
Documentation search and retrieval behavior.
Risk
Scoped change; functional review still required.
Evidence
Tests, evaluation results, and preview available.

Your approval moves this feature forward.

ApproveRequest changes

Optimize the flow of work, not just the agents.

Built on

  • Temporal

  1. Trigger

    New work item

  2. Agent

    Execute

  3. Eval

    Check results

  4. Human Review

    Intent · impact · risk · evidence

    Change Manifest · PR Lens · Approval Console

  5. Continue

    Merge / next step

Retry

If checks fail

Replaceable specialists, Stable platform.

Built on

  • Claude
  • OpenAI
  • Gemini
  • Model Gateway

Execution

Specialists connect through a shared model gateway and MCP. Swap runtimes as the work evolves.

One shared context. Better decisions everywhere.

Built on

  • Repository
  • Docs
  • Patterns
  • Decisions

Knowledge

Code, documentation, reusable patterns, and decisions stay connected through MCP and APIs.

Ways of Working

Organize for impact.

The way we work changes — smaller teams, broader ownership and focus on problems that matter.

Three colleagues gathered around a table, discussing work on a shared laptop.

Our vision.

What we have learned.

Four key shifts define the target state of how we work with the Agentic Product Platform.

  1. Smaller teams,
    amplified by Agents

    2–3 people can achieve the scope of today’s larger teams, with the Product Platform providing significant execution capacity.

  2. Broad Product Builders

    People identify with the problem and value they create rather than a narrow technology or functional boundary. They bring different strengths, but can operate across the lifecycle (Product, Design or Engineering).

  3. Own end-to-end

    We own the work from idea to impact, following the problem through discovery, specification, implementation and production. No handoffs, no diluted responsibility.

  4. Enable to enjoy your work

    As Agents take on more production work, human work shifts to judgment, creativity and collaboration — with dedicated review time and meaningful interaction with colleagues.

Our journey.

How to get there.

Four steps to move from learning to lasting change.

Two colleagues sharing a moment over a phone, with coffee in hand.

  1. Create Trailblazer teams

    Start with AI-curious Product Builders and engineers, augmented by experienced AI-Native engineers. Give them the mandate to challenge existing practices.

  2. Start with the right work

    Pick meaningful but bounded work packages where the team has room to rethink how the work gets done. Avoid work that is completely embedded in the current platform.

  3. Follow the work

    Keep the team with the problem from idea to impact. Bring specialists to the work instead of handing work from function to function. Rethink together what needs to be done.

  4. Show, learn & scale

    Demonstrate product progress and ways-of-working progress every week. Turn learnings into reusable platform capabilities, context and working patterns so every next team starts further ahead.

Our beliefs.

What remains true.

Some things don’t change — they become even more important.

  1. Expertise still matters

    UX, Architecture, Security, Legal and domain expertise remain essential. Their role shifts from owning a workflow step to bringing expertise directly into the work.

  2. Autonomy needs boundaries

    Teams have significantly more autonomy, but within clear organizational guardrails: what the team can decide, when specialist input is required and when leadership approval is needed.

  3. Mastery still matters

    Careers don’t become “everyone does everything.” Mastery increasingly combines deep expertise with product judgment, systems thinking, customer understanding and the ability to work effectively with Agents.

  4. The Platform keeps learning

    The Product Platform is never finished. Patterns discovered by Trailblazer teams should become shared workflows, Agents, context and capabilities — not local solutions.