Outcome
The team leaves the training with shared practices for tool use, context preparation, reviews and data boundaries.
Enablement
Training
AI and Agentic Engineering training for development teams that want shared practices, clear review standards and reliable data boundaries for their use of coding agents.
At a glance
- Working mode
- Enablement
- Typical stakeholders
- Engineering teams, Technical leads, IT service providers
- Outcome
- The team leaves the training with shared practices for tool use, context preparation, reviews and data boundaries.
Mandate
The technical focus.
The training uses tasks from day-to-day software development. The team develops practices for context, tool use and reviews that fit its own codebase.
Suitable for
- Engineering teams
- Technical leads
- IT service providers
Process
How the collaboration works.
The exact shape depends on your request - the frame remains transparent in every case.
Process
Step 1
Clarify team & tools
Step 2
Practice on real code
Step 3
Document conventions
Step 1
Before the training, we clarify team size, experience, current tools and typical tasks. This allows us to adapt the training to your actual codebase and working practices.
Step 2
The team works through realistic engineering tasks: preparing context, directing coding agents, reviewing changes and assessing results.
Step 3
At the end of the training, the team documents its own practices for tool use, context and reviews, then plans the next steps for the following weeks.
Results
What is delivered.
A shared understanding of where coding agents should be used and which quality standards apply.
Documented practices for tool use, context preparation, data boundaries and reviews, developed by the team itself.
A prioritised plan for the following weeks: what the team will test, develop further or deliberately stop pursuing.
Boundaries
What we clarify upfront.
Vendor-independent working practices The practices focus on tasks, context and reviews and can be applied with different coding agents.
Work based on realistic tasks The team applies the material directly to typical engineering tasks from its day-to-day work.
Reviewable expectations Together, we define how the team can assess the benefits and limitations of the new working practices.
Related topics
Typical starting points.
Agentic Engineering
How engineering teams can use coding agents consistently and establish shared practices for tasks, context, data and reviews.
View topicAI-Assisted Software Delivery
Identify appropriate uses of AI in software development and adapt reviews, tests and technical responsibility accordingly.
View topicHow does your team currently work with coding agents?
Tell us the team size, current experience and training objective. We will suggest a format that fits your working practices and codebase.