Two days
AI SDLC
for leaders
Design the move from individual AI use to a shared development process: roles, knowledge, infrastructure and an implementation plan. Work with agents on your team’s challenges.
From €8,000 · excl. VAT and applicable taxes
Heads of engineering, engineering managers and technical leads
Developers already use AI, often with different tools, prompts, context and checks. Useful discoveries stay with individuals, making it difficult to assess the effect on the team’s work.
Over two days, work with agents and the authors of the SDLC Playbook to integrate AI into your software development lifecycle (AI SDLC). Agree how to manage knowledge, assign roles and check results, then plan the first changes.
You do not need to know how to program agents. You do need to understand your team and the problems you want to solve.
A design for your team’s AI SDLC
Process and roles
A path from requirements to release, with clear ownership and checks. Record the decisions and the reasons behind them.
Knowledge and infrastructure
Requirements for tools, knowledge and access, with decisions to resolve alongside security and platform owners.
An implementation roadmap
Where to start, who owns the work and how to assess the first pilot. Use it to discuss the changes with your team.
Two days to plan your team’s development process
Before the programme, choose a team workflow to focus on. Each block builds on the previous one: investigate the current process, design the changes and assemble a practical transition plan.
1. Assess how the team works todayDay one · Design the process
Follow a real task through the team’s workflow. Find where context is lost, work waits or tasks return for rework. Identify who already uses AI, which practices help and what the team could share.
Output: A process map and a priority task for improvement.
2. Choose the next step for your development processDay one
Apply the SDLC Playbook to your situation. Decide which practices the team needs now, what the next step requires and under what conditions agents can work more independently.
Output: A target state and the conditions for moving towards it.
3. Divide work between people and AIDay one
Design the path from requirements to release. Decide how the change specification develops, who makes decisions, what AI does and how the team checks the result.
Output: A target process with roles, responsibilities and checks.
4. Plan how to manage knowledge and infrastructureDay two · Prepare the transition
Identify the context agents need and how to store and update it. Define access requirements for models and tools. Prepare for discussions with security and platform owners.
Output: Environment requirements and a list of decisions to agree with the relevant teams.
5. Organise how the team works with AIDay two
Turn useful individual practices into shared working rules. Plan how to involve colleagues, assign ownership and maintain the environment. Consider how to adapt the process as requirements and conditions change.
Output: A team transition plan and a way to support the new practices.
6. Build the implementation planDay two
Choose the first pilot, participants and resources. Decide how to assess impact, what to do first and what evidence would justify expanding the approach.
Output: A roadmap with a first pilot and criteria for assessing its results.
Training for your team
Two days
A practical two-day programme built around your team’s workflow
From €8,000 · excl. VAT and applicable taxes
Facilitators explain the approaches, help apply them to your context and review your decisions. In the agent environment, AI helps investigate the team’s situation, organise materials, compare options and assemble the plan. You check its conclusions and choose the next steps.
We agree who will attend, the dates and the delivery arrangements with you.
Need help putting the plan into practice? Explore AI SDLC implementation →
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Discuss AI SDLC for leaders
Tell us what your team needs. We’ll reply to arrange a 30-minute call and talk through the options.
