AI enablement agency · for enterprise teams
Your best people know how the work gets done. Your AI doesn't — yet.
Commit Memory captures the institutional knowledge locked in your experts' heads and commits it as versioned, reusable skills — the operating instructions your AI harnesses read before they act. So every agent, copilot and assistant works the way your company actually works.
Fixed-scope engagements · Works with Claude, Copilot, Cursor and your own internal agents · Your knowledge stays yours
Built for the harnesses your teams already use
The problem
You bought AI. You didn't get your company's judgement.
Off-the-shelf AI is generically competent and specifically clueless. It doesn't know your architecture, your compliance line, your tone, or the hard-won lessons that live in your senior people. So the output is plausible, inconsistent, and quietly off — and the people who could fix it are the ones too busy to write it all down.
Knowledge trapped in heads
Your standards, playbooks and "how we do it here" live in a handful of experts, a few Slack threads, and nowhere you can point an AI at.
Inconsistent AI output
Every prompt is a fresh roll of the dice. Two teams ask the same question and get two different answers — neither matches how you'd actually do it.
The same context, re-typed forever
People paste the same background into every chat. That effort evaporates the moment the window closes. Nothing compounds.
What we do
We turn how your company works into skills your AI can read.
A skill is a small, structured document that tells an AI harness how to do one job the way you do it — when to use it, the steps, the rules, the examples, the traps to avoid. We interview your experts, mine your existing docs and code, and commit that knowledge as skills your agents load automatically. Institutional memory, version-controlled.
Before Commit Memory
- Knowledge lives in senior people and tribal habit
- AI answers are generic and vary run to run
- Onboarding a new hire — or a new agent — takes months
- Every AI tool starts from zero context
- Best practice erodes the moment someone leaves
After Commit Memory
- Knowledge is captured, versioned and owned by you
- AI answers are consistent and on-standard, every time
- New hires and new agents inherit your playbook on day one
- Every tool reads the same source of truth
- Expertise compounds instead of walking out the door
How it works
A productised engagement, not an open-ended consulting bill.
Fixed scope, fixed steps, a defined set of committed skills at the end. You know exactly what you're getting and when.
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01
Discover
We map the workflows where consistency matters most and where AI is already being used — or badly wants to be. We pick the highest- leverage skills to build first.
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02
Extract
Structured interviews with your experts, plus a pass over your existing docs, wikis, tickets and code. We surface the rules and judgement that never got written down.
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03
Commit
We author each skill in a clean, harness-ready format, test it against real tasks, and iterate with your team until the output is indistinguishable from your best people.
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04
Install & hand over
We wire the skills into your harnesses, train your team to maintain them, and leave you with a versioned skill library you own outright. No lock-in.
What you get
A skill library your whole organisation can build on.
Versioned skill library
A structured, source-controlled set of skills — reviewed, tested, and documented — that plugs into your harnesses.
Harness integration
Wired into Claude, Copilot, Cursor or your internal agents, so skills load automatically at the right moment.
Authoring playbook
Templates, standards and a review process so your team can write and maintain new skills long after we're gone.
Team enablement
Hands-on training so your people know how to extend the library and keep it current as the business changes.
Where it pays off
Anywhere a wrong-but-plausible answer costs you.
Engineering
Code review standards, architecture conventions, incident runbooks, secure-by-default patterns.
Support & success
Tone of voice, escalation rules, product edge cases, the answers only your veterans know.
Sales & marketing
Positioning, objection handling, brand guidelines, what you will and won't claim.
Legal & compliance
Review checklists, red lines, jurisdiction rules, the clauses that always need a second look.
Operations
SOPs, vendor policies, approval flows — the procedures that must be followed the same way every time.
Onboarding
Give new hires — and new agents — an assistant that already knows how your company does the work.
Engagements
Start small. Prove it. Scale what works.
Productised, fixed-scope engagements — no open-ended retainers. Start with a pilot on one workflow; expand once you've seen the output.
Pilot
Prove the model on one workflow
- 1 high-value workflow
- 3–5 committed skills
- Expert interviews + doc mining
- Integrated into one harness
- ~2–3 weeks
Department
A full skill library for one team
- One department end-to-end
- 15–30 committed skills
- Authoring playbook + templates
- Multi-harness integration
- Team enablement & training
Enterprise
Org-wide institutional memory
- Multiple departments
- Governance & review process
- Central skill library & standards
- Ongoing maintenance option
- Rollout & change management
Pricing is quoted per engagement after a short scoping call — sized to the workflows and the number of skills involved.
FAQ
The questions enterprises ask first.
What exactly is a "skill"?
A skill is a small, structured document that tells an AI harness how to perform one job your way — when to use it, the steps, the rules, worked examples, and the mistakes to avoid. Harnesses like Claude and Copilot load the relevant skill before they act, so the output reflects your standards instead of a generic best guess.
How is this different from a prompt library or a wiki?
Prompts and wikis are passive — someone has to find them, read them, and remember to apply them. Skills are active: they're written in a format your AI harness reads and applies automatically, they're version-controlled, and they're tested against real tasks. It's the difference between documentation and a program.
Who owns the skills you create?
You do — outright. We hand over a versioned skill library that lives in your systems. There's no platform lock-in and no ongoing licence required to keep using what we build.
Does our proprietary knowledge stay confidential?
Yes. We work under NDA, keep your knowledge inside your environment wherever possible, and never reuse a client's institutional knowledge anywhere else. Your expertise is your competitive edge — we treat it that way.
Which AI tools do the skills work with?
The ones your teams already use — Claude and Claude Code, GitHub Copilot, Cursor, and custom RAG or agent stacks. Skills are authored in an open, portable format, so they're not tied to a single vendor.
How much of our team's time does this take?
Less than you'd expect. The heaviest lift is a few structured interviews with the experts whose knowledge we're capturing — we do the writing, testing and integration. A pilot typically needs only a handful of hours from your side.
Commit your institutional knowledge before it walks out the door.
Book a short scoping call. We'll find the one workflow where consistent AI output would pay off fastest — and show you what committing it as skills looks like.