Programmes
Help your team make stronger agentic-system decisions.
Live, project-based learning with Sunil Mathew for engineering teams that need to design, build or review AI agents. Enterprise learning is scoped for the group; an employer can also sponsor an individual place in a public programme.
What kind of organisation are you?
- Product company
Your team is shipping AI agent features and needs them to hold up in production.
- Global capability centre
Your centre is taking on AI work for the wider organisation and needs to own it, not just deliver it.
- IT services or consulting company
Your delivery teams need to scope, build and review AI agents on client projects.
Start with the capability your team needs
Perhaps your engineers are building a first agent workflow. Your architects need a shared way to examine permissions and recovery. Or your managers need to ask better questions when a team presents its design.
Begin with those responsibilities. An enterprise programme connects the learning to the decisions the group needs to handle, using practical work, evaluation and review.
What the group can work on
- Engineers
connect a use case to a working workflow, inspect results and investigate failures.
- Architects and technical leads
explain system boundaries, review trade-offs and establish evidence for design decisions.
- Engineering managers and leaders
guide reviews, identify unresolved assumptions and clarify who owns approvals, exceptions and follow-up.
The mix depends on the group's starting point and agreed learning scope.
Learning that gives a review something concrete to examine
A working system makes the discussion specific. The group can trace an action, question the evidence behind it and revise the design together. That practice develops both technical understanding and a shared approach to review.
Company-specific work needs appropriate scope, permission and data access. You can begin with an industry example; confidential project material is unnecessary for an initial enquiry.
Led by Sunil Mathew
Sunil has 26 years of engineering experience, including past leadership roles at Google, Amazon and Walmart Labs. He has hired, developed and assessed senior technical professionals and now combines agentic-AI product work with consulting and teaching.
The programme draws on that background to connect implementation with the reasoning a team must explain.
How a team programme is agreed
An enterprise programme normally brings 8–10 participants together. The group's experience and learning objective shape the scope.
- Describe the group, its current work and the capability you want to develop.
- Discuss technical starting points, suitable practice and the learning scope.
- Agree live hours, independent work, group size, schedule and fee in a separate proposal.
A separate proposal sets the team fee alongside its scope, group size and schedule.
If your employer is funding one person's place, compare individual Agentic AI programmes. Their fees and live hours apply to the selected individual offer; team arrangements need a separate proposal.
Is the need learning, or outside expertise on a live decision?
Choose enterprise learning when the group needs to develop capability. Choose bounded advisory when a current use case or architecture needs an external review. An organisation-wide AI diagnostic belongs in the AI Readiness Assessment.
Discuss your team
Tell us what your team needs to handle more effectively.