Why Most AI Products Fail Quietly and What PMs Don’t Measure

Hosted by Dr. Aki Wijesundara and Manu Jayawardana

Sun, Feb 22, 2026

10:00 PM UTC (30 minutes)

Virtual (Zoom)

Free to join

77 students

Invite your network

Go deeper with a course

AI Evaluations for Product Managers
Aki Wijesundara, PhD and Manu Jayawardana
View syllabus

What you'll learn

What AI product failures look like in practice

Understand the quiet failure modes that don’t show up in dashboards.

Which metrics PMs commonly miss

Learn what teams fail to measure around quality, cost, and user trust.

How to design signals that surface real issues early

Track indicators that reveal degradation, misuse, or silent breakage.

How to turn metrics into product decisions

Use measurements to decide when to iterate, pause, or rethink a feature.

Why this topic matters

Many AI products don’t fail loudly. They slowly degrade, cost more than expected, or lose user trust without obvious errors. This session focuses on the metrics PMs need to detect these issues early, avoid shipping blind, and make informed decisions about AI features before problems compound.

You'll learn from

Dr. Aki Wijesundara

AI Founder | Educator | Google AI Accelerator Alum

Aki Wijesundara is an AI leader with a PhD in Machine Learning and extensive experience mentoring startups at Google’s AI Accelerator. With a career spanning both research and applied AI, Aki has taught 5,000+ students worldwide how to design and deploy production-ready AI systems.

He has worked across cutting-edge areas of applied AI, from LangChain and RAG pipelines to observability and large-scale deployment. As a researcher and educator, Aki bridges the gap between theory and practice, making complex systems approachable and actionable for engineers, founders, and product leaders.

Aki is also a frequent speaker and advisor to organizations adopting AI, helping them transition from experimentation to production at scale.


Career highlights

  • Ex–Google AI Accelerator researcher focused on responsible AI and applied ML.
  • PhD in AI & Cognitive Systems with published research across top universities.
  • Former researcher with teams affiliated with MIT, University of Oxford, & King’s College London.
  • Co-founder of Snapdrum — delivered AI systems for finance, education, and healthcare.
  • Built and deployed AI product pipelines used by PMs, startups, and enterprise teams.
  • Instructor for multiple AI builder programs, helping 500+ professionals ship AI features fast.


Manu Jayawardana

AI Advisor | Co-Founder & CEO at Krybe | Co-Founder of Snapdrum

Manu Jayawardana is a serial entrepreneur with multiple AI startup successes. He exited Rise AI, a fintech app with over 35,000 users, to a private investor, demonstrating his ability to build and scale impactful products.

He is also the Co-Founder of Snapdrum, an AI consultancy helping companies integrate and automate their businesses using AI. Through Snapdrum, Manu has worked with top startups and enterprises across the U.S., Europe, and Asia, advising on automation, product development, and AI strategy.

Currently, Manu is the Co-Founder & CEO of Krybe, an AI voice agent startup in London transforming how businesses automate customer interactions. His experience spans fundraising, scaling products, and leading teams to deliver production-grade AI solutions adopted globally.


Career highlights

  • Co-Founder of Snapdrum — builds production-ready AI systems for Fortune 500s, YC startups, and global Series A–C companies.
  • Exited Founder of Rise AI — created an AI investment copilot used by 35,000+ users worldwide.
  • Co-Founder of Krybe — ultra-realistic voice AI platform with 1000+ users and part of the NVIDIA Inception Program.
  • Creator of the #1 ranked Investment GPT on the OpenAI Store with 30,000+ users.
  • Built and scaled 10+ companies across AI, SaaS, analytics, and EdTech, including a B2B analytics product that grew 10× in one year.
  • Former Entrepreneur First Unlock Fellow, selected for high-potential AI founders.


Previous Students from

Google
Meta
OpenAI
NVIDIA
Amazon Web Services

Sign up to join this lesson

By continuing, you agree to Maven's Terms and Privacy Policy.