Who joins
Business owners, architects, developers, testers, security and operations leads.
01 / CODE TRANSFORMATIONINDIA + ASEAN
Transform how your enterprise builds software.
Improve how your enterprise designs, builds, modernises and operates software. Start with an AI-DLC workshop, then apply the method to your delivery teams and applications.
Plan an AI-DLC workshopA SHARED WAY TO BUILD
THE STARTING POINT
Set the stage with an AI-DLC workshop.
Bring business, engineering, security and operations together around a real backlog item. Our AI Development Life Cycle (AI-DLC) workshop helps your team work from requirements and design through implementation, testing and review, using tools such as Kiro or Codex where appropriate.
Use the workshop to agree the delivery method, security and safety checks, and a scoped pilot. Continue with embedded engineering to modernise existing applications, improve release practices and build an operating model your teams can own.
START WITH A WORKSHOP
AI-DLC workshop
What we prepare
Choose one backlog item or modernisation need. Agree repository access, approved AI tools, data boundaries and the checks the team must satisfy.
What you leave with
A reviewed specification, a scoped implementation or prototype, a security and test plan, and a prioritised pilot backlog. Agree owners, baseline measures, testable acceptance criteria and the evidence needed to approve the pilot.
What comes next
Pilot the method with one delivery team, validate quality and risk controls, then extend it to further applications and teams. A workshop output needs separate approval before production.
WHAT WE DELIVER
A clear scope.
Something you can use.
A shared delivery method
Agree roles, approved tools and review gates in an AI-DLC workshop around real work.
A scoped engineering pilot
Build or modernise a feature with specifications, tests, security review and evidence against agreed acceptance criteria.
A secure delivery playbook
Document code review, dependency and secrets checks, AI tool boundaries, release approvals and rollback practices.
Adoption and ongoing operations
Support the next teams and applications with monitoring, vulnerability management, runbooks and named owners.
WHERE IT APPLIES
Cross-functional AI-DLC workshop
Bring a complete delivery team together around one feature, from business intent to a reviewed implementation.
Embedded delivery support
Work alongside your engineers to apply the method to a real backlog and resolve adoption friction.
Release workflow improvement
Explore AI-assisted change analysis, testing and release preparation with approval and rollback controls.
SECURITY AND SAFETY
Security by design.
Safety throughout.
Protect systems and data. Evaluate how AI behaves and the consequences of its actions. Agree controls and evidence for the risks in each engagement.
Protect code and data
Agree which repositories, data and AI tools may be used. Apply least privilege, approved environments and secrets handling from the workshop onwards.
Review and test the change
Review generated code and dependencies, test security and functional behaviour, and resolve findings against agreed release criteria.
Release with accountability
Keep human release approval, audit evidence, rollback and vulnerability ownership explicit through ongoing operations.
DEFINE SUCCESS FIRST
Measure the work.
Then the difference.
We agree a baseline, target, measurement method and accountable reviewer, alongside security and safety acceptance criteria. These are measures to consider, not promised results.
Verifiability in practice
Trace requirements to code changes, review decisions and test results. Keep versioned build and release records so the customer can inspect what changed and repeat the agreed checks.
- Lead time for comparable changes
- Review effort and escaped defects
- Test quality and release readiness
- Team adoption beyond the workshop
GOOD QUESTIONS
Before we begin.
Is this only for developers?
No. The method spans business analysis, design, architecture, development, testing and operations. We shape the participant mix around the work.
Will a workshop deliver a production release?
That depends on readiness, scope and your release gates. We agree a realistic output during preparation; a reviewed implementation is different from permission to release it.
Can you stay involved after the workshop?
Yes. We can scope an embedded engineering engagement to help your team apply the method and build on the initial work.
Can we transition an AI application to open-weight models?
Yes, where evaluation shows a good fit. We compare models on your real tasks, adapt prompts and integrations, and test quality, safety, response time and total operating cost. We check licence terms and plan a staged switch with rollback before changing production.
YOUR NEXT STEP