A codebase your team can hold
Conventional structure, typed end to end, decisions documented. Onboarding a new engineer takes a day rather than a fortnight.
Platforms and internal tools built to carry model workloads from the first commit, not retrofitted afterwards.
A system that will eventually run AI workloads needs decisions made early: where state lives, how long-running jobs are queued, how a request that takes forty seconds is handled without holding a connection open. Adding those to a finished application is the expensive path.
We build the ordinary parts properly — authentication, roles, audit trails, background jobs, an API other teams can integrate against — and leave the seams where agents and models will attach later. Tests run on every commit, and a deploy is a routine event rather than an evening.
Your engineers are in the review from the first week. Handover is not a zip file and a call; it is a codebase they have been reading for months, with the runbooks and the reasoning written down beside it.
Conventional structure, typed end to end, decisions documented. Onboarding a new engineer takes a day rather than a fortnight.
Queues, background jobs, event logs and typed service boundaries already in place by the time the first agent needs them.
Continuous integration, reversible migrations, staged rollout and a rollback path, so shipping on a Friday is not an act of courage.
Who changed what and when, captured at the data layer, because retrofitting it during a compliance review costs many times more.
Domain model, service boundaries and the contracts between them, settled before the first endpoint. This is the decision that is painful to change a year in.
Auth, data layer, jobs, logging and the deployment pipeline land in the first weeks, so every feature after that arrives on finished rails.
Each slice is usable and demoed behind a flag. Your team reviews the pull requests as they go rather than at the end.
Load testing, error budgets, alerting and runbooks, then a handover to engineers who have already been reading the code.
Each phase ends with something you can read and act on. If the evidence says stop, stopping there is a supported outcome rather than an awkward conversation.
Tooling is a decision we make per project, against your constraints and whatever your team already runs. Nothing on this list is a requirement, and we will work inside your existing stack where it holds up.
Yes, and it is often faster. We start with a short read-in, agree the conventions already in play, and follow them rather than introducing a second style beside the first.
You do, from the first commit, in your own repository. We work on branches inside your organisation and your engineers approve the merges.
Frequently. Plenty of engagements are a platform, an internal tool or an integration layer, with AI arriving a year later or never. The architecture leaves that door open either way.
Tell us where the work sits today and what is holding it up. We will come back with the shape of a first phase, what it would prove, and what running it takes.
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