Skip to content
BigTree108

AI coding assistant adoption: GitHub Copilot, Claude Code, Cursor and Codex

AI coding assistant services for engineering teams: GitHub Copilot, Claude Code, Cursor and OpenAI Codex rolled out with policies, repository instructions and security controls, coding agents that open pull requests and fix builds inside your CI, AI code review, AI-written tests checked by mutation testing, legacy code upgraded with AI help, and training and pairing for your developers, with dedicated AI-assisted developers for your team or a rollout delivered end to end.

AI coding work we take on

  • Rollout of AI coding tools

    GitHub Copilot, Claude Code, Cursor or Codex rolled out to your engineering teams with licences, policies and editor settings in place, starting with a pilot team and a baseline of delivery metrics.

  • Governance and security

    Rules for which repositories, data and secrets the tools may see, content exclusions, approved models and MCP servers, audit logs, and secret scanning on every pull request.

  • Repository instructions

    Coding conventions, build and test commands and architecture notes written into the repository as AGENTS.md, CLAUDE.md or Copilot instructions, so agents follow your rules rather than guessing them.

  • Coding agents in CI

    Agents that pick up issues, open pull requests, fix failing builds or update dependencies inside your CI, with every change going through the same review and tests as a person’s.

  • AI code review

    Automated review on every pull request for bugs, security issues and broken conventions, tuned to cut the noise so reviewers keep reading it.

  • AI-written tests

    Unit, integration and end-to-end tests written with AI for code that has none, checked by mutation testing so they catch real faults rather than only raising coverage.

  • Legacy code with AI help

    Old code read, documented and upgraded with AI assistance: framework upgrades, language migrations and dead code removed, each step proven by tests.

  • Training and pairing

    Hands-on sessions and pairing with our engineers, covering how to brief an agent, how to review its output and which work to keep for people.

  • Measuring the effect

    Cycle time, review time, change failure rate and developer feedback compared before and after, so the rollout is judged on delivery rather than on lines of code.

Hire AI-assisted developers

  • Dedicated AI-assisted developers

    AI-assisted developers who join your team full time, work in your tools and process, and report to your lead. You interview them; we carry the Ukrainian contract, payroll, invoicing and leave.

  • AI coding adoption projects

    A defined piece of AI coding adoption with a scope, a fixed plan and a named lead on our side who owns the result and reports progress in your channels.

  • Ongoing AI coding adoption

    AI coding adoption as a continuing service: the same people every month, a backlog you prioritise, and hours you can see in our portal and on the invoice.

The dedicated team page explains how specialists join your team, and the outsourcing page covers project delivery, take-overs and how we charge.

Who works on your AI coding adoption

  • Senior engineers

    Daily work with AI coding agents, review and pairing

  • DevOps engineers

    Agents in CI, policies and audit logs

  • Security engineers

    Secret scanning, data rules and tool review

  • QA engineers

    AI-written tests and mutation testing

  • Delivery managers

    Pilot, metrics and rollout

The rules we work by ourselves

Our own engineers build with AI coding agents under the rules we would set for you: instructions kept in the repository, tests and analyzers in the pipeline, every change through a pull request, and no secrets or client data in a prompt.

A rollout starts with one team and a baseline, so its effect on delivery is measured, and widens when the numbers and the developers agree that it helps.

Other AI development services we provide

AI development overview

Questions about AI coding assistants

Which AI coding tool should we use?

GitHub Copilot fits teams on GitHub and Microsoft licensing, Claude Code and Codex suit agent-style work across a whole repository, and Cursor suits developers who want AI built into the editor. Many teams use more than one; we pilot on your codebase and compare.

Is our code safe with AI coding tools?

With business plans whose terms exclude training on your code, content exclusions for sensitive repositories, secret scanning and review of every change, the risk is managed like that of any other tool with access to the code. We set those controls up before the rollout.

Can you provide developers who already work this way?

Yes. Our engineers work with AI coding agents every day and join your team with that practice, inside your rules on which tools and data are allowed.

How quickly can AI-assisted developers start?

When the right AI-assisted developer is available, the start is gated only by your interview and the NDA and IP assignment. Otherwise we run a search, which typically produces candidate profiles within two to three weeks, and nobody starts until you have said yes.

How do we hire AI-assisted developers through BigTree108?

Tell us the work, the seniority and the hours you need. We propose one or two people with their profiles, you interview them the way you would interview your own hire, and you sign one agreement with BIG TREE 108 LLC and receive one invoice a month.

Who owns the work they produce?

You do. Every specialist has a signed contract with BigTree108 that assigns all work product to the company, and our agreement with you assigns it onward. Code, designs and documents are delivered into your own repositories and tools, not kept where only we can change them.

Rolling out AI coding tools?

Tell us the size of your team, your stack and the tools you are considering. You get an answer within one business day: a pilot plan, a governance checklist, or candidate profiles.

Email hello@bigtree108.com How we respond