An engineering process built for AI-assisted delivery
AI compresses the time between an idea and working software. Discipline is what keeps that software correct. Here is exactly how we combine the two.
Five phases, each with a clear exit condition
Nothing moves forward on a status report. Each phase ends with something you can see, run or measure.
- 01
Align
Week 0–1
We agree on the business outcome before writing code, and name the metric that tells us the work succeeded.
Research synthesis and requirement drafting are AI-assisted, so alignment takes days instead of weeks.
- Stakeholder and user interviews
- Success metrics and guardrails
- Scope, risks and non-goals
- Engagement model selection
- 02
Architect
Week 1–2
A thin vertical slice proves the risky parts of the architecture early, while decisions are still cheap to change.
Model-assisted option analysis and scaffolding generation, weighed against experience before anything is adopted.
- Target architecture and data model
- Spike on the highest-risk assumption
- Environment, CI/CD and observability setup
- Definition of done and quality gates
- 03
Build
Ongoing
Weekly increments to a real environment. Every change is read by a human and gated by automated checks.
AI pairs on implementation, tests and refactors. The principal engineer owns design, review and accountability.
- Weekly demos on deployed environments
- Trunk-based development with short-lived branches
- Human review on every AI-assisted change
- Specialists added from the network when scope needs them
- Continuous documentation of decisions
- 04
Harden
Before each release
Performance, security, accessibility and cost are treated as release criteria rather than post-launch cleanup.
Generated edge-case tests and evaluation datasets expand coverage beyond the happy path.
- Load, security and accessibility testing
- Evaluation suites for AI behaviour
- Runbooks, alerts and SLOs
- Cost and performance review
- 05
Operate & scale
Post-launch
We run the system, watch how it is used, and feed real usage back into the roadmap — or hand it over cleanly.
Anomaly detection and log summarisation shorten the path from signal to root cause.
- Monitoring, incident response and patching
- Usage analytics feeding the roadmap
- Continuous improvement backlog
- Handover, training or transition to your team
The rules we do not bend
AI-first, human-accountable
AI accelerates research, code, tests and documentation. A principal engineer still owns every design decision and reviews every line that ships.
One owner, no handoffs
The person who scopes the work is the person who builds it. Nothing is lost between a salesperson, an account manager and a delivery team you never meet.
Small on purpose
We run a deliberately small number of engagements at once. When scope needs more range, we add vetted specialists to the work rather than padding a team.
Weekly working software
Progress is demonstrated on a deployed environment every week, not reported in a status document.
Transparent commercials
Clear rates, clear scope and a written engagement model. No surprise change requests for work that was always implied.
Yours to own and to leave with
Code, infrastructure, credentials and documentation live in your accounts from day one, documented well enough for another team to take over without a discovery phase.
Common questions about our delivery
What does “AI-first” actually mean in your delivery?
It means AI is used in the day-to-day mechanics of engineering — requirement analysis, code generation, test writing, migration analysis, documentation and operational triage — and it also means we know how to build AI features into your product. What it does not mean is unreviewed generated code: every change is read, reasoned about and signed off by the principal engineer, and gated by automated checks.
You are a small studio. How do you deliver work of real scale?
Three ways. AI removes most of the mechanical effort that used to require extra hands, so one experienced engineer covers ground that recently needed several. We keep only two engagements active at a time, so your work gets genuine attention rather than a slice of a shared team. And when a project needs range we do not have in-house — specialist mobile, design, security or data work — we bring in vetted specialists from our network under the same standards and the same accountability. If a project genuinely needs a twenty-person team, we will tell you that in the first call.
What happens if the principal engineer is unavailable?
Continuity is designed in rather than promised. Everything runs in your accounts and repositories, decisions are documented as we go, and infrastructure is reproducible from code. For longer engagements we name a backup engineer from our network up front, so there is always someone briefed on your system.
How quickly can an engagement start?
A discovery sprint can usually begin within one to two weeks of the first conversation, subject to current capacity. Larger builds depend on the skill mix required, and we will always give you an honest start date rather than an optimistic one.
Who owns the code and the intellectual property?
You do, in full. We work in your repositories and cloud accounts wherever possible, and IP assignment is part of the contract from the start.
Can we change engagement model later?
Yes, and most clients do. A typical path is a discovery sprint, then a pod for the initial build, then a support retainer once the product is live and stable.
How do you handle data privacy and security?
We scope data access to the minimum required, keep client data out of model training, prefer providers with zero-retention terms for sensitive workloads, and can work entirely within your own cloud and tooling when your policies require it.
Do you work with existing in-house teams?
Often. We can lead delivery, embed alongside your engineers, or act purely as an advisor and reviewer — the engagement model is chosen to fit how your team already works.
Why choose a studio over an agency of the same price?
You get the senior engineer instead of the sales team. There is no bench to keep busy, no margin on junior hours and no incentive to stretch scope, so the advice you get is the advice we would follow ourselves. The trade-off is capacity: we cannot start five projects next month, and we will say so rather than take the work.
Let's scope your next build
Discovery calls open shortly. Send us the outcome you need in the meantime and we will reply personally, with an honest view of when we could start.