Claude Code and Codex for software teams
A governed rollout of Claude Code and OpenAI Codex gives an engineering organisation coding agents with rules: a policy on what the agents may touch, secrets kept out of prompts, review gates before anything is merged, and adoption that is measured rather than assumed. We run the same rollout in our own company, where agents open the pull requests and people merge them. What it does not do: it does not replace code review, and it does not let an agent deploy to production.
What a governed rollout contains
- Policy: which repositories, environments and data the agents may access, what they may write, and what always needs a person. Written with your security team, versioned in your repository.
- Secrets handling: credentials, tokens and customer data kept out of prompts and out of agent context, with a documented pattern developers follow and a scanner that fails the build when they do not.
- Review gates: agent-written changes go through the same review, tests and checks as human changes, and the record shows which is which. Deployment stays a human action.
- Adoption measurement: which teams use the agents, for what, and what changed in cycle time and review load, reported monthly from your own tooling, not from the vendor's dashboard.
- Six weeks for a first team of up to 30 developers, including training by role and a written operating guide; fixed price, stated in the first conversation.
Why this is an implementation, not a licence purchase
Coding agents act on repositories, run commands and open pull requests. Treating them as a chat subscription leaves the questions that matter unanswered: who is accountable for an agent's change, where its context came from, and what happens when it touches a production configuration. We answer those questions before the first team starts, and we run the pilot with one team on real backlog work so the policy is tested against reality rather than written in the abstract.
We use the same agents in our own daily operations, so the patterns we hand over are the ones we work with ourselves.
How delivery runs
Assessment with engineering leadership: current tooling, repositories, compliance constraints. Architecture: accounts, access, secrets pattern, review gates. Pilot with one team for a defined period on real work. Enablement: role-based training for developers, reviewers and leads. Operations: monthly review of adoption and policy adjustments.
Questions we get asked
Claude Code or Codex?
Both are in production use and we implement both. The choice usually follows your existing platform contracts, your model preferences and the languages and repositories involved. We do not push one over the other.
Will our source code be used for training?
Enterprise agreements for both products exclude training on customer data. We document this in the data-handling map alongside where prompts and context are processed.
How do we stop an agent from committing secrets?
With a secrets pattern that keeps credentials out of the agent's context, plus scanning in the review gate so a slip is caught before merge. This is part of the rollout, not an afterthought.
How do we know it is working?
Adoption and effect are measured from the first month: active users, work items handled with agent help, review load and cycle time. The numbers go to engineering leadership monthly.
Talk to us.
A 30-minute conversation on your scenarios. The call and the written assessment you leave with are free, whether we work together or not. The next step, if there is one, is a fixed-price six-week pilot in your environment with no obligation to continue.
Or write to us directly: info@iteractive.ai · +421 905 452 325