Rohit delivered our MVP in 5 weeks — on budget and ahead of schedule. His architecture decisions saved us from rewriting everything when we scaled.
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Claude Code Consultant — Roll Out Agentic Coding Across Your Team Without Lowering the Bar
Claude Code is the strongest agentic coding tool shipping today, and most teams use about a tenth of it. I set it up the way I run it myself — skills, hooks, MCP servers, subagents, CI pipelines, guardrails — so your engineers ship faster and your review bar stays where it is.
The Problem
Your engineers already have Claude Code. What they do not have is a shared setup: no CLAUDE.md that encodes how your codebase actually works, no custom skills for the tasks you repeat every week, no hooks stopping the agent from touching things it should not, no MCP servers connecting it to your internal tools, and no answer to the question a CTO eventually asks — is AI-written code lowering our quality bar? Individual developers get individual results. The teams pulling ahead in 2026 treat Claude Code as infrastructure: configured, governed, measured, and taught. That takes someone who has run it at scale, not a lunch-and-learn.
What You Get
- ✓Team-wide Claude Code baseline: CLAUDE.md conventions, permissions model, and settings that encode how your codebase really works
- ✓Custom skills and slash commands for your recurring engineering work — migrations, release notes, test scaffolding, incident triage
- ✓Hooks and guardrails: blocked destructive commands, enforced lint and typecheck on every edit, review gates before anything merges
- ✓MCP servers connecting Claude Code to your internal systems — issue tracker, databases, observability, internal APIs — with scoped permissions
- ✓Subagent and workflow design for multi-step tasks, including unattended headless runs in CI where they are actually safe
- ✓Cost and usage governance: which models for which tasks, context budgeting, and reporting so spend stays predictable
- ✓Hands-on working sessions with your engineers — they leave running the setup, not watching me run it
- ✓Written playbook your team owns, plus a 30-day follow-up review of what stuck and what did not
Tech Stack
Claude CodeClaude APIClaude Agent SDKMCPGitHub ActionsTypeScriptPython
Timeline
Team rollout: 2-6 weeks. Advisory: a single working session.
Related Work
Frequently Asked Questions
What does a Claude Code consultant actually do?
Turns Claude Code from a tool individual developers poke at into infrastructure the whole team runs on. Concretely: I audit how your engineers use it today, write the CLAUDE.md and permission model that encode your codebase's real conventions, build custom skills for the tasks you repeat, add hooks that block the failure modes you care about, wire MCP servers to your internal tools, design subagent workflows for multi-step work, set up cost governance, and run working sessions so the setup survives after I leave. The output is a configured, documented environment plus engineers who know why it is configured that way.
Can't my team just read the docs and set this up themselves?
They can, and the docs are good. What the docs do not tell you is which of the hundreds of possible skills, hooks, and MCP servers matter for your codebase, what breaks at team scale, and where the agent quietly makes your code worse. I run one of the largest personal Claude Code setups I know of — 387 skills across 34 clusters, mapped publicly in Agentic OS — and an eight-stage autonomous pipeline, claude-autodev, that takes requirements to reviewed, tested branches. That is the accumulated judgement you are buying: skip the six months of trial and error and start from a setup that already works.
How do you stop AI-written code from lowering our review bar?
Guardrails at three layers. Before the agent edits: CLAUDE.md conventions and a permission model that keeps it away from things it should not touch. During: hooks that run lint, typecheck, and tests on every change, and block destructive git or shell commands outright. After: a review workflow where AI-written changes carry the same evidence a human PR would — a spec, a diff explanation, passing tests — and a separate reviewer pass that has not seen the plan. Your review bar does not move. What moves is how much of the work reaches that bar without a human typing it.
Can Claude Code run unattended in CI, and is that safe?
Yes, for bounded tasks with hard gates. Headless runs work well for things like dependency bumps with test verification, generated release notes, issue triage, and spec-driven implementation in an isolated worktree that ends in a PR — never a direct push. The safety comes from the gates, not the model: every stage must produce a real artifact (passing tests, an approved review file, a non-empty spec) before the next runs, and a failed run parks with a written diagnosis instead of a confident-looking green. I run this pattern in production for a client's daily content pipeline, and open-sourced the engineering pipeline version as claude-autodev.
Where does our source code and data go?
Wherever your Claude plan sends it, and nowhere else. I configure Claude Code inside your accounts — Team or Enterprise plan, or your own API keys via Bedrock or Vertex if that is your compliance posture — with permissions scoped to what each workflow needs. MCP servers I build run in your infrastructure with your credentials. I sign an NDA before the first call and I never need standing access to your repos after the engagement ends.
We also use Cursor, Codex CLI, or Copilot — does this still apply?
Mostly, yes. The durable parts — codebase conventions, MCP servers, review guardrails, task decomposition, eval discipline — transfer across agentic tools, and several of them read the same MCP servers and similar instruction files. I standardise on Claude Code because it is the deepest tool for team-level configuration today, but the playbook is written so your team is not locked to it.
How is this different from your fractional AI engineer engagement?
This engagement is about your engineers shipping faster with AI. The fractional engagement is about me shipping AI systems — agents, LLM features, integrations — inside your product. They combine well: many clients start with a Claude Code rollout and keep a fractional retainer for the AI backlog. If you are not sure which you need, the scoping call sorts it out in thirty minutes.
Related Engagements & Reading
Fractional AI Engineer →
Senior AI delivery on a part-week retainer — the engagement most Claude Code rollouts grow into.
MCP Integration Consultant →
Production MCP servers connecting Claude Code and your agents to internal systems.
Claude Code plugins and context engineering →
How skills, plugins, and context budgets fit together in a real setup.
Claude Code dynamic workflows guide →
Multi-agent workflows: when to fan out, when to pipeline, when not to bother.
Claude Code vs hiring a developer →
The honest line between a developer multiplier and a developer replacement.
Testimonials
What Clients Say
We needed a WhatsApp bot for our clinic chain. Rohit understood the problem immediately and shipped a working solution that our staff could use without training.