Development team services
Help your team deliver faster, and more predictably
Your developers are capable. Delivery is still unpredictable, standards drift, and there is pressure to adopt AI without anyone being sure what safe looks like. That is almost always a system problem rather than a people problem.
You might recognise one of these
- “We commit to dates and miss them, and nobody can say why in advance.”
- “Every developer here has a different opinion about how we do things.”
- “Our senior engineer is the bottleneck for every decision.”
What we do about it
When delivery is unpredictable, the instinct is to look for the underperforming developer. It is almost never that. It is a deployment process that takes a day and so batches changes into risky releases. It is the absence of an agreed way to make decisions, so each one is relitigated. It is a test suite nobody trusts, so every change is verified by hand and hope.
Those are system properties. They do not respond to encouragement or to hiring, and they compound: every one of them makes the next change more expensive than the last.
So we start by finding out where the time actually goes. We baseline lead time, deployment frequency, change failure rate and estimate variance, and we talk to the engineers — who generally know precisely what the problem is and have often said so more than once.
Then we agree a small number of changes with the team, and we implement the first ones with them. That distinction matters more than anything else on this page. A document describing better practice changes nothing; standards that the team helped establish and has seen working survive our departure. The transfer is of reasoning, not of conclusions.
Where AI belongs in this, we are pragmatic. Coding assistants genuinely help experienced engineers on well-understood work, and genuinely mislead inexperienced ones on unfamiliar work. Test generation is useful with human review and dangerous without it. The value comes from adopting them with clear review practices and clear rules about what data may be shared — not from adopting them enthusiastically.
For technical readers
We baseline the four DORA metrics — lead time for changes, deployment frequency, change failure rate, time to restore — plus estimate variance and defect escape rate. Not because the numbers are sacred, but because "delivery feels slow" is unarguable while "median lead time is eleven days, of which nine are waiting for a manual QA environment" points directly at what to fix.
In practice the highest-leverage change is usually deployment automation, not code quality. A team that can deploy safely gets faster at everything else, including improving code quality, because the feedback loop shortens.
Capabilities
What this covers
Architecture office hours
A standing slot where your engineers can bring decisions to someone who has made them before.
Agile delivery improvement
Agile as a disciplined system for shipping small increments, not a calendar full of ceremonies.
AI developer-tool adoption
Coding assistants, test generation with human review, codebase explanation — plus the data-handling rules that make it safe.
Code quality programmes
Review practices, automated testing proportional to risk, and standards the team actually agreed to.
DevOps maturity
Repeatable builds, deployment automation, environment separation, observability that gets used.
Mentoring and technical leadership
Growing your senior engineers so the dependency on outside help decreases over time.
Deliverables
What you end up holding
Tangible artefacts, not a verbal summary. You keep all of it.
- Architecture and codebase assessment with prioritized findings
- Delivery-process observations and a concrete improvement plan
- Engineering metrics baseline: lead time, deployment frequency, change failure rate
- Technical standards and architecture decision record practice
- AI usage and data-handling policy for developers
- Test and quality strategy proportional to actual risk
- Onboarding material so the standards survive turnover
- Coaching plan for your senior engineers
How the engagement runs
Typical shape and duration
-
Assess — 2–3 weeks
Where the delivery friction actually is. Frequently not where the team assumes, and rarely where the executives assume.
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Agree — 1 week
A small number of changes the team has genuinely bought into. Imposed standards decay the moment we leave.
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Implement together — 6–12 weeks
We work alongside your engineers on the first items rather than handing over a document. That is how the reasoning transfers.
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Sustain
Architecture office hours or fractional leadership at a reducing cadence, until you do not need it.
Where it usually starts
Modernization and Architecture Assessment
A structured review of an existing application, architecture and delivery process, followed by a prioritized modernization roadmap and clear build, refactor, replace or retain recommendations.
- Duration
- 2–3 weeks
- Format
- Remote, with codebase and environment access
Questions we are usually asked
Will you tell our team they have been doing it wrong?
No, and we would be wrong to. Most delivery problems come from constraints — deadlines, staffing, decisions made years ago by people who have left — rather than from carelessness. Teams that feel judged hide exactly the information we need.
Our developers are sceptical of consultants. Fairly.
Reasonable. The way we address it is to do the work with them rather than produce a report about them, to share findings with the team before the executives, and to be specific enough that they can check our reasoning. Sceptical engineers are usually persuaded by specificity.
How do you measure whether this worked?
We baseline before starting: lead time for changes, deployment frequency, change failure rate, defect escape rate, and estimate variance. Improvement should be visible in the numbers, not just in how meetings feel.
Can you just help us adopt AI coding tools?
Yes, and it is a common starting point. It involves tool selection, review and verification practices, secure data-handling rules, and honest measurement of whether it actually helped — which is less obvious than vendors suggest.
Do you take over the team?
No. We work alongside it and deliberately reduce our own involvement over time. If we are still essential after a year, we have failed at the actual job.
What if the real problem is a person?
Occasionally it is, and we will tell you privately and plainly. But we look at the system first, because it is right far more often and because it is the part we can actually fix.