Claude Code, set up the way Anthropic would — if they had your codebase.
Most teams install Claude Code and hit a wall in week three. Context degrades. Skills quietly rewrite production. The token bill doubles before anyone asks why. The tool isn't the bottleneck — the configuration is. We design the setup, build the skills and MCP wiring, gate every risky action behind human review, and train your team to maintain it. You end up with a governed teammate, not a faster way to break things.
Six things that turn Claude Code from a chat window into a governed teammate.
Every engagement ships configuration your team can read, change, and own. No black boxes. No proprietary wrappers. The deliverables below are what we actually build together in a one-to-two-week Claude Code Sprint.
CLAUDE.md architecture
We write your project memory as code: conventions, SOPs, review rules, naming standards, and context boundaries. This is what stops context degradation and keeps every Claude instance aligned with how your team actually works, even when the engineer who started the project is on holiday.
Custom skills (SKILL.md)
Scoped, tested SKILL.md files that tell Claude exactly what it may touch and what needs a human gate. We compose multiple skills so complex workflows stay maintainable, and we never let a skill edit, commit, or deploy without an explicit approval checkpoint.
MCP servers for internal tools
We wire up scoped MCP connections to your own systems — CRM, ticketing, docs, search — with limited API keys, spending limits, and an explicit allow-list. That way Claude can read what it needs without getting access to everything that happens to share a login.
Hooks & CI gates
Pre-tool gates, secret redaction, and drift detection built into your workflow. The skill can't rewrite prod, access secrets, read private data, or go outside its scope without someone approving it. Governance is part of the implementation, not a separate conversation.
Sub-agent & Agent Teams architecture
We design multi-agent loops only where the problem genuinely has parallel workstreams. We also tell you when Agent Teams' 3–7× token premium isn't worth it — and build the simpler single-agent alternative that gets you most of the value for a fraction of the cost.
Team training
We teach the 4 Ds and 5 Cs as applied to coding agents: what to hand off, how to ask for it, how to judge what comes back, and how to keep data and accountability where they belong. The skill outlasts the engagement only if the team knows how to maintain it.
The same month-three death, localized to Claude Code.
Claude Code is powerful enough to hurt you quietly. The failure modes below are what we see most often in teams that installed it without a configuration layer. Every one of them is fixable with the right setup — and expensive to ignore.
No CLAUDE.md, so context degrades
Without project memory, Claude re-learns your conventions every session. Quality drifts. Decisions become inconsistent. We fix this by writing the memory down and keeping it under version control. Read how dynamic workflows and self-updating project memory keep context from degrading. Dynamic workflows explained
Skills without gates rewrite production
A skill that can edit code and commit it is a loaded weapon. We design every skill with an explicit human-approval checkpoint and a documented scope boundary, so the worst-case outcome is a blocked action, not a changed production file. Building skills for Claude Code
MCP servers with unscoped keys
Connecting Claude to your CRM or ticket system without scoped credentials is how a helpful automation becomes a data breach. We build MCP connections with limited permissions, spending caps, and audit trails, so the blast radius is always smaller than the business value. Claude Code for RevOps
Sub-agents that multiply cost without multiplying judgment
Agent Teams can speed up parallel work, but they can also burn tokens on problems that need one careful loop. We map the work before we recommend the architecture, so you only pay the 3–7× token premium when it actually buys you speed. Agent Teams vs subagents
No eval or cost tracking
If you can't measure tokens per task or quality per change, you can't optimize. We add lightweight evals and token-budget guardrails so the bill stops being a surprise, and you can prove whether Claude Code is saving time or just shifting cost. Cut your AI coding bill
One workflow. One governed Claude Code skill. One to two weeks.
We don't re-architect your whole stack, and we don't ask for a six-month roadmap. We pick one concrete workflow where Claude Code can make a measurable difference, prove it in your repo, and leave your team able to build the next one without us.
- 01
Discovery call: you name the workflow — PR review, incident triage, onboarding, release notes, or something specific to your team.
- 02
We audit how the workflow runs today, interview the people who do it, and define one measurable outcome everyone agrees on.
- 03
We write the CLAUDE.md section, the SKILL.md, the MCP wiring, and the approval hook — all in your repo, all under your version control.
- 04
We test on your real data and adjust until the outputs meet your standards. The skill doesn't ship until the team that uses it says it's right.
- 05
You get a working skill, a runbook, and a 60-minute handoff session so your team can maintain and extend it.
What you get, and what you own after
| Deliverable | What you get | What your team owns |
|---|---|---|
| CLAUDE.md section | Project memory tuned to your conventions | Markdown file in your repo |
| Custom skill | One scoped, tested SKILL.md | Source + runbook |
| MCP wiring | Scoped connection to one internal tool | Config + credentials policy |
| Hooks / gates | Pre-tool and approval checks | CI or hook config |
| Team handoff | 60-min walkthrough | Recording + runbook |
Before/after: an anonymized team we worked with.
A 12-person engineering team had adopted Claude Code ad-hoc. Half the engineers loved it; the other half refused to touch it after Claude once rewrote a shared config file without review and broke a staging environment. The split was costing them more in coordination than the tool was saving in typing. We scoped a single workflow — PR review for a high-touch service — and built a governed skill with a mandatory approval gate, a scoped SKILL.md, and a CLAUDE.md section that captured the team's review conventions. Within two weeks the sceptical engineers were using it, because they could see exactly what Claude was allowed to change and what had to wait for a human.
Down 35% for the target service after two weeks.
Stable; the skill refused tasks outside scope instead of guessing.
Zero unapproved changes to production config.
9 days from kickoff to team-approved handoff.
Placeholder: replace this block with a real client case study once you have publishable metrics and approval. Keep the same four metrics fields.
We work with what you already use.
Claude Code and the Anthropic Agent SDK, configured for your repo, your branch strategy, and your review workflow — not as a generic assistant, but as a teammate with a defined job.
MCP servers for the tools you already depend on: HubSpot, Linear, GitHub, Notion, Postgres, internal APIs. We scope each connection to the smallest permission set that still makes the workflow useful.
Operator Stack as the open-source skills registry — plain markdown skills any developer can read, change, and maintain. The registry is the proof; the consulting is the integration, governance, and change management that makes it work inside your organisation.
EU data residency by default. All processing stays in the EU, and the human-gate / audit-trail layer is built for EU AI Act documentation requirements from day one. We never train on your data.
Frequently asked questions
Is this a SaaS tool?
No. We're a consultancy. The skills we build live in your repo as markdown files, and the Operator Stack registry is open source. You don't rent access to a dashboard — you own the configuration.
Do you work with non-Anthropic models?
We're Claude-first because that's where we have the deepest experience, especially for code. If another tool fits your workflow better, we'll say so and either support it or point you to someone who specializes in it.
How is this different from the First Skill Sprint?
The First Skill Sprint is workflow-agnostic — we can build a governed skill for any task, with any tool that fits. Claude Code Consulting is deeper on the agent architecture: CLAUDE.md, SKILL.md composition, MCP wiring, hooks, and Agent Teams. If you just need one reliable workflow, the Sprint is usually the right place to start. See the First Skill Sprint
Do you train my team?
Yes. Every engagement includes a handoff session, and teams that want broader fluency can add seats to the AI Fluency Cohort. The goal is that you don't need us for the next skill.
What about EU AI Act and GDPR?
We classify the workflow's risk tier and build the human-gate, audit-trail, and data-flow artifacts the Act expects. Processing stays in EU residency, and we never use your data for model training.
How much does it cost?
A Claude Code Sprint starts at €4,500 for a fixed-scope, one-to-two-week engagement. Larger Agent Teams or multi-skill architectures are priced on scope after discovery. The first call is free.
How fast can we start?
Usually within a week of the discovery call, once you've identified the target workflow and the people who need to be in the review loop. The sprint itself is one to two weeks.
Do you touch production?
Only behind a human gate. We don't automate anything that can commit, deploy, or send data without explicit approval. The skill can draft; it can't act on its own.
What do I need to have ready?
A codebase we can access, one concrete workflow you'd like to automate or improve, and one person who can approve outputs during the sprint. That's it for the first sprint.
What happens after the sprint?
You own the skill and the runbook. If you want to expand to more workflows, we scope the next sprint or a broader Flagship Pilot. You can also maintain it yourself using the same patterns we leave behind.
Can you also set up an LLM wiki or knowledge base?
Yes. A self-updating knowledge base is one of the most useful Claude Code skills we build, especially for teams where context lives scattered across docs, tickets, and Slack. Read how an LLM wiki fits into a Claude Code setup. LLM wiki for Claude Code
Book a free discovery call
Tell us the workflow you'd hand to Claude Code if you trusted it. We'll tell you whether we're the right fit, what a sprint would look like, and what could go wrong before you spend anything.