Coding agents speed up implementation, but review, architecture decisions, handoffs and releases still run at the old pace. We help engineering organisations turn individual AI use into an agentic delivery system, built hands-on with your teams, in your codebase.
When every engineer has an agent, output goes up and the bottleneck moves downstream: into review queues, undocumented architecture, knowledge that lives in people’s heads and release processes built for a slower era. AI that stops at the IDE makes the system busier, not faster.
Review piles up
Generated code lands on the same few senior reviewers. Pull requests queue up and quality turns into guesswork.
Context stays private
Prompts, rules and decisions live in individual chat sessions and disappear with them. Every engineer starts from zero.
No proof it works
Licences are paid and usage is up, but nobody can show whether delivery actually got faster or safer.
Rules, skills and architecture notes live with the code, so every engineer and every agent works from the same ground truth.
Shared context in the repo
Rules, skills and architecture notes live with the code, so every engineer and every agent works from the same ground truth.
Beyond code completion: agents support refinement, planning, implementation, review, testing and operations.
Agents across the lifecycle
Beyond code completion: agents support refinement, planning, implementation, review, testing and operations.
Tests, security checks and contracts decide what moves forward. People own the decisions that matter.
Quality gates that scale
Tests, security checks and contracts decide what moves forward. People own the decisions that matter.
Roles, rituals and decision rights change with the tooling, or nobody can run the new system.
An operating model to match
Roles, rituals and decision rights change with the tooling, or nobody can run the new system.
Assess
Interviews, a repository and pipeline review and your delivery data give you a baseline, the first constraint to fix and a prioritised roadmap.
Enable
Hands-on agentic engineering training on your stack and your code. Teams leave with shared practices, and rules and skills checked into the repo.
Pilot
One real value stream. We work inside your team to run the new workflow end to end and measure what changed.
Scale
Roll out across teams, adapt the operating model and build internal ownership, so the system keeps improving after we leave.
Assess
Interviews, a repository and pipeline review and your delivery data give you a baseline, the first constraint to fix and a prioritised roadmap.
Enable
Hands-on agentic engineering training on your stack and your code. Teams leave with shared practices, and rules and skills checked into the repo.
Pilot
One real value stream. We work inside your team to run the new workflow end to end and measure what changed.
Scale
Roll out across teams, adapt the operating model and build internal ownership, so the system keeps improving after we leave.
Usage numbers don’t prove impact. Every engagement starts with a baseline and a clear hypothesis, so you can show leadership what improved and where the next constraint sits.
Throughput
Merged pull requests per week, lead time to production
Adoption
Share of work done with agents, per team
Quality
Change failure rate and escaped defects
Confidence
How safe engineers feel shipping a change, 1 to 5
Every metric
Baseline, target, data source and review date
Claude Code, Cursor, GitHub Copilot, Codex or your own agents: we’re tool-agnostic and hands-on with all of them. We onboard onto the stack you run today and focus on the workflow around the tool.
Our own delivery teams build agent-first every day. What we recommend, we have run on real client projects first.
No slide decks from the sidelines. We pair with your engineers, write the rules and skills together and leave them in your repository.
The people who scope the engagement stay in the delivery work. No sales handoff, and no junior bench learning on your project.
It’s a good start for individual speed. The gains stall at review, handoffs and release. We work on the delivery system around the tools, so faster coding turns into faster, safer delivery.
We’re tool-agnostic: Claude Code, Cursor, GitHub Copilot, Codex and custom agents, on the stack you already run. The practices matter more than the tool.
No. Most engagements start with an assessment or a training. Each phase ends with evidence and a decision, and you choose whether to continue.
Quality gates are part of the setup from day one: tests, security checks and review rules that agent-written code has to pass. We work within your compliance requirements, including EU-hosted models where needed.
Good engineering is mostly discipline: clear ownership, honest estimates and systems you can operate at three in the morning.
I have taken over enough projects in trouble to know that the rewrite is rarely the answer. Understanding what is there, stabilising it and moving it forward usually is.
For me, software is only done when your team can run it.
