21 September 2026
How we build software with AI, and keep you in control
AI does the heavy lifting, an engineer answers for it, and nothing goes live until you say so.
Not every problem needs new software. When yours does, this is how we build it.
You put what you want on a simple board. When a card moves, a team of AI specialists researches, designs, builds and tests the change. An engineer checks it, you try it in a preview, and you decide whether it goes live.
Agentic Development Lifecycle (ADLC)
A team of AI agents does the work. You make the decisions.
The Agentic Development Lifecycle (ADLC) is how we run the software part of an engagement. Work starts on your product board. When its status changes, a team of specialist AI agents researches, designs, builds and tests the change, and a delivery agent decides what happens next. An assigned engineer leads delivery, and you approve every release to production.
How a request moves through the ADLC
- People
- AI agents
- Board and environments
Where people step in
The agents ask for a decision whenever they need one, and the preview environment waits for your review. You can also add or move work on your board, or ask the Concierge to tidy it, at any time. Nothing goes to production without your review, and production runs on the stack you choose.
- 01
Agree the priorities
You and your engineer add work to your product board, and the Concierge, an AI assistant, tends the board, looks after the scheduled agents and keeps you both informed. We agree the next work, its cost and the acceptance criteria.
- 02
Develop and verify
When a card's status changes, the AI agent team picks it up. Agents can send work back to one another and ask you for a decision. A delivery agent then sends tested changes to a preview environment, where your engineer reviews them and you can try them.
- 03
Review and release
You and your engineer review the preview. After your approval, the release goes to production through your own CI/CD, on the cloud or servers you choose. Then we continue with the next agreed priorities.
Always-on agents
These run on a schedule, not a status change. They look after the project between priorities; the Concierge tends them, and their findings go to your engineer to review.
Tidy-up
Clears away leftover files and half-finished work.
Refactoring finder
Spots code that should be simpler and proposes changes.
Performance optimizer
Looks for slow spots and proposes improvements.
Opportunity researcher
Researches opportunities to grow the business and reports to your engineer.
Why a board
It keeps you in charge. Nothing gets built unless a card moves, and you decide who can move it. Use whichever board your team already likes.
A helper called the Concierge tidies the board between jobs and lets you know what is waiting on you.
What the AI does, and what it doesn't
The AI does most of the work: research, design, code, testing, security checks. When it needs a decision, it asks you rather than guessing.
The responsibility stays with a person. Your engineer reviews everything and explains the choices in plain English. You approve the release, and it goes live on your own cloud or servers.
Between jobs, a few background helpers tidy up old files, spot slow code and suggest improvements. Their suggestions go to your engineer, never straight into your code.
Why we do it this way
The risk with AI-written code is code you never agreed to, in a place you do not control. Here you set the priorities, see every change first, and own the code.
Have a problem worth solving? Book 15 minutes and tell us what a useful outcome looks like.