AI-driven software development
AI-driven development with a human at every gate.
AI has made the work fast. We make it governed: bounded agents do the repeatable jobs, every output lands in the record, and nothing ships without a person approving the design and reviewing the release.
Start a project- week of discovery before anything is built
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- sign-offs on every piece of work: design and release
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- handover documents, because there is no handover
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What governed AI development gives you
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Speed you can audit
Agents produce research, designs, implementations and tests in minutes. The record says which agent, which inputs, which outputs.
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People where judgment matters
Design approval and manual review are human gates on every piece of work. Agents never move work past them.
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No prompt-and-pray
Agents work inside a written scope you approve. They read defined inputs and write defined outputs, nothing else.
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Replayable decisions
Any job can be re-run against a new model or policy and compared, because the inputs are in the record.
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Consistent across developers
The process is the process. Outcomes do not depend on who picked up the ticket or which assistant they prefer.
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Answers for compliance
Which model did what, approved by whom, with every step logged.
When AI-driven development needs governance
These are the signs that the speed has outrun the record.
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Pull requests arrive without a requirement
Code exists; the reason for it is in a chat window that has been closed.
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Review cannot keep up
More output than people can read, with no structure that says what needs a human.
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Every developer has a different setup
Tools, prompts and agents differ per person. Quality depends on luck.
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Something shipped and nobody knows why
The decision cannot be reconstructed because nothing recorded what was known at the time.
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You have been asked to audit the AI
Security, legal or a customer wants the model, the inputs and the approvals.
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Vibe-coded software needs a cleanup
It works, mostly. Nobody tested it and nobody wrote down why it was built that way. Bring it in as a feature request.
Do two or more of these apply? Tell us which ones and we reply with how we would run it.
How we apply AI across the lifecycle
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Research and requirements
Agents draft research reports and PRDs from your feature request. You approve the design package.
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Design
Data models, APIs and interfaces proposed as documents, reviewed at the first gate.
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Implementation
Agent-drafted code under release controls, with the implementation package in the record.
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Automated QA
Test generation and execution that writes a QA report before any person reviews.
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Manual review
The second human gate, with the agent output attached and the reviewer logged.
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Agents in your product
The same discipline applied to the AI features you ship to your own users.
Read more
The lifecycle, with AI where it belongs
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Discovery
A week with the people who own the problem. We write the feature request as the first document of the engagement and agree what done means before anything is designed.
In the record Feature request, scope, success measures
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PRD and design package
Research, requirements and design are produced and land in the record as documents you can read, comment on and reject.
In the record Research report, PRD, design package
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Design approval
A human gate. Work waits until you approve the design package. Nothing is built that the record does not say is being built.
In the record Logged approval, with the approver
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Development
Implementation runs in short cycles against the approved scope. You see progress as it happens, with the implementation package growing in the record.
In the record Implementation package
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Automated QA and manual review
Automated QA runs first and writes a report. Manual review is the second human gate. Failures go to a person instead of slipping through.
In the record QA report, review report
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Release and operation
A release candidate ships only after both gates pass. We deploy it, monitor it and operate it, and the next request starts the next run.
In the record Release candidate, release log
Governed AI development against the alternatives
| Item | AI assistant per developer | AI app builder | Sydeso |
|---|---|---|---|
| Where AI runs | Each editor | A vendor chat window | Bounded jobs inside a fixed process |
| What is recorded | Commits | A prompt history | Every document, job and step with its actor |
| Who approves | Code review, if it happens | Nobody | You, at two logged gates |
| Consistency | Per person | Per prompt | Per process |
| Replay | No | No | Re-run recorded inputs against a new model |
| Ownership | Yours | Depends on the vendor | Yours: repository, accounts, record |
How an engagement is structured.
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Week one
Discovery
A week with the people who own the problem. We write the feature request, the PRD and the design package, and agree what done means.
- Ends in a PRD and a design package you own
- You approve it before anything is built
- Comes with a price for the build
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After approval
Build
Development in short cycles against the approved scope. Automated QA writes a report on every release candidate and a person reviews it before it ships.
- Priced per project against the PRD
- Changes are new feature requests, priced the same way
- Every document is yours as it is produced
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After launch
Operate
We deploy it, monitor it and run releases, month to month. Production is where the next feature request comes from.
- Monthly, separate from the build
- Take it in-house whenever you are ready
- The record comes with it
Questions
- Is the code written by AI?
- Much of it is drafted by agents and all of it is recorded as such. People approve the design, review the release and hold responsibility for both.
- Which models do you use?
- The ones the design package names. The record shows which model ran each job, so changing models later is a re-run against the same inputs.
- How do you stop agents from making things up?
- Agents work inside a written scope, read only the documents in the engagement, and write outputs that a person reviews before anything ships. Automated QA runs before manual review.
- Can our developers use this on their own work?
- Not yet as a product. We are building the platform that runs this process for your own team. Join the waitlist on the platform page and we will tell you when it launches.
- How quickly do you reply?
- By email, with how we would run the work, not a call to book a call. Send one paragraph about what should ship first and you get a written answer.
- Where does the work live?
- In your accounts. Code in your repository, infrastructure in your cloud, documents where your team can read them. We bring the process, not a dependency.
- What happens to the work if we stop?
- You keep everything: code, infrastructure, requirements, design packages, QA and review reports. There is no handover because none of it was ever ours.
Run one feature, governed.
Give us a feature request and we run it through the process and send you the record.
Start a project