Skip to main content
AI-Native Delivery

Your roadmap, shipped the new way. Inside your codebase, by week four.

An engineer joins your team, runs your delivery with agents from ticket to pull request, and leaves the setup behind. Every change is reviewed by your developers and signed by a named person.

The problem

The assistant made one team faster. The roadmap did not move.

  • You bought an AI coding assistant, and one team got faster. The backlog did not move.
  • Nobody owns the way the work gets done now, so it varies by developer.
  • Your review queue is the bottleneck, and more generated code makes it worse.
  • Nothing you could put in front of an auditor changed.
  • The pilot proved the tool works. It did not prove the work is under control.

Speed is not the problem. Nobody can show how the work now gets done, or who allowed it.

How we work

In. Build. Leave. Prove.

One job, four weeks, in production. Then it keeps proving itself.

  1. In

    We pick one value stream with you, and the measure that says whether it improved.

  2. Build

    The old way and the new way run side by side for three weeks, inside your repositories.

  3. Leave

    Your team runs the loop and keeps the playbook. We maintain it if you ask.

  4. Prove

    Every change traces to a ticket, a reviewer and a signature, and you can replay the history any day.

What we build

What you are left with.

  • An agent-run delivery loop in your repositories: ticket, spec, plan, pull request.
  • Review gates your team owns, with the rules for what may merge written down first.
  • The before-and-after measure on one value stream, taken the same way both times.
  • The playbook your team keeps, so a new engineer can run it without us.
  • The record: what the AI proposed, what was allowed, who signed it, and when.
Built for the regulator's questions

When the auditor asks how this change got into production, what do you show them?

  1. What the AI is allowed to do is written down first.

  2. Every decision is checked against those rules before it happens.

  3. A named person signs it off. The check produces the evidence; a person judges.

  4. You can replay the whole history any day and get the same answer.

  5. If anyone changes it later, it shows. Patent pending, UK application GB2620101.2.

That is what a deployment leaves running for your job. In the accessibility product today, a person on your team accepts every finding before it reaches your record.

Who this is for

Who this is for.

  • Product and engineering leaders with a mature codebase and a roadmap they are behind on.
  • Teams whose review queue, not their typing speed, is the constraint.
  • Regulated businesses that have to show how a change was made, not just that it works.

Not for

Greenfield rebuilds. This changes how an existing product gets delivered.

Why us

Two people, on every call and in your standup.

Simon Milner, Founding Architect

He designed the record: what the AI is allowed to do, checked before it acts, and replayable afterwards. Twenty-five years in Silicon Valley before that.

Jason Crispin, Founder

He owns the customer side of every deployment: what the job is, what it is worth, and that it lands. He is on the first call and every one after.

Patent pending, UK application GB2620101.2. Meet the team

How it runs

Four weeks, then it keeps proving itself.

  1. Week 1

    The baseline

    What the job is, what allowed means for it, and who signs. Written down before anything runs.

  2. Weeks 2 to 4

    The build

    Our engineer works in your codebase next to your developers. The old way and the new way run side by side.

  3. Week 4 on

    The proof

    Every decision checked and recorded. Replay it any day. We maintain it, or you run it without us.

What you keep

  • The delivery loop, running in your repositories.
  • The code, assigned to you in writing.
  • The playbook your team runs without us.
  • The record of every decision, replayable any day.
Questions

What people ask.

Are you consultants or engineers?

Are you consultants or engineers?

Engineers. The market calls them forward deployed. Ours works in your repositories, next to your developers, and ships to production. You are not left with a slide deck.

Will this work on our ten-year-old codebase?

Will this work on our ten-year-old codebase?

That is who it is for. We change how one value stream is delivered inside the product you already run. No rewrite, and no greenfield rebuild. If the codebase makes this the wrong job to start with, we tell you on the call.

Who owns the code?

Who owns the code?

You do. Everything we build in your codebase is assigned to you in writing, and the playbook goes with it.

What happens to our review process?

What happens to our review process?

It stays yours, and it gets the evidence it never had. Your developers review every change as they do today. What is new is that each change traces to a ticket, a reviewer and a signature, and nothing takes effect until it passes your rules.

Whose repositories and accounts does your engineer work in?

Whose repositories and accounts does your engineer work in?

Yours. Your repositories, your identity provider, your environments, with access you can revoke any day.

What does it cost?

What does it cost?

Scoped on the call, because it depends on the job. You leave the call knowing what it would cost and what you would keep.

Which value stream would you pick?

Thirty minutes with Simon and Jason. Bring the stream you would start with, and you leave knowing what it would take, what you would keep, and what it costs.