Course

AI Experimentation to Enterprise Confidence

Su Belagodu

Responsible AI Adoption

A Practical Guide to Designing Human Oversight for Production AI

AI systems are moving into production, taking on more tasks, supporting more decisions, and operating with greater autonomy. But as adoption grows, so does a question many organizations haven't fully addressed: Who is responsible for oversight, and how does it work when AI operates at scale?

I've audited 40+ production AI deployments, and the pattern is consistent. Human oversight often depends on individual effort rather than deliberate design.

This course focuses on designing human oversight that can hold up in production. Bring one AI workflow. Over two weeks, you'll score it using the HITL Health Index™, assess its maturity using the HITL Maturity Model™, and work through the decisions that matter: confidence-based routing, escalation thresholds, reviewer capacity, and checkpoints for autonomous agents.

You'll leave with a scored baseline, a documented oversight design, and a practical 90-day plan to strengthen human oversight as your AI systems scale.

The goal is knowing where human judgment is necessary, who is accountable, and how to make oversight work at scale.

What you’ll learn

Go from hoping your AI pilot survives production to knowing it will, with a score and a plan you can show your leaders and the board

  • Baseline one live workflow on the HITL Health Index™ and place it on the five-level HITL Maturity Model™.

  • Find the gaps that low volume and hand-picked reviewers hid, including the warm body problem: reviewers present, no longer catching errors.

  • Send high-risk cases to a human, let low-risk outputs move on their own, and set the thresholds before deployment while changing them is che

  • Cap review load, protect domain judgment from erosion, and treat human attention as a budgeted resource in your rollout plan.

  • Decide which agent actions need human approval before execution, which must be reversible, and how sub-agents stay visible.

  • Map your design to EU AI Act and NIST AI RMF requirements and walk out with a ranked plan to move up one maturity level.

Learn directly from Su

Su Belagodu

Su Belagodu

Contact

AI Native CPO| Creator of the HITL Maturity Model™ | 40+ AI Deployments Audited.

See all products from Su

Who this course is for

  • Product leaders whose AI feature is moving from one team to the whole company, and who will own every error it makes at that scale.

  • Founders heading into an enterprise deal or funding round where someone will ask how oversight works, and a slide will not satisfy them.

  • AI and operations owners running reviewers who approve more each week and catch less, with no way to measure if oversight still works.

What's included

Su Belagodu

Live sessions

Learn directly from Su Belagodu in a real-time, interactive format.

Lifetime access

Go back to course content and recordings whenever you need to.

Community of peers

Stay accountable and share insights with like-minded professionals.

Certificate of completion

Share your new skills with your employer or on LinkedIn.

Maven Guarantee

Your purchase is backed by the Maven Guarantee.

Course syllabus

Live sessions

1 hr / week

Live sessions with varying themes each week

Async content

2 hrs / week

Independent work, Free resources and async conversations

Week 1

Feb 1—Feb 7

    Diagnose

    1 item

Week 2

Feb 8—Feb 14

    Design

    1 item

Frequently asked questions

Maven for Teams

Reimbursement

Get your company to pay

Everything L&D needs: email template, receipts, and certificate of completion.

Get reimbursed

Team discount

Learn with your teammates

Save 20%+ when 2 or more teammates enroll in the same cohort.

Save 20%+ with a team

Private cohort

Run a cohort for your org

A dedicated cohort with a custom schedule and curriculum, tailored to your team.

Book a private cohort

$650

USD

Feb 1—Feb 15
Enroll