AI Engineering in 30 Minutes: Become an AI-Native Engineer

Hosted by Aki Wijesundara, PhD and Manu Jayawardana

Mon, Jun 29, 2026

10:00 PM UTC (30 minutes)

Virtual (Zoom)

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Practical ML Ops for Data Scientists
Akshika Wijesundara, PhD
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What you'll learn

Why your model isn't the problem — your pipeline is

Most "dumb AI" bugs are retrieval or ordering failures. Trace a bad output to the stage that broke.

How to make an AI system you can trust in production

Evals before vibes. The minimum testing setup that catches regressions before your users do.

Live build: turn a flaky prototype into something solid

Add retries, fallbacks, and guardrails so it fails safely instead of confidently making things up.

Why this topic matters

Anyone can wire up an API call and get an impressive demo. Shipping something that survives real users, weird inputs, and scale is a different job — and it's the one companies are actually hiring for. AI engineering is the layer between "it worked on my machine" and "it works for ten thousand people who'll try to break it." It's the gap between a cool weekend project and a product.

You'll learn from

Aki Wijesundara, PhD

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 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.
  • Co-Founder of Krybe — ultra-realistic voice AI platform with 1000+ users and part of the NVIDIA Inception Program.
  • 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.

Previously Students from

Google
Amazon Web Services
NVIDIA
OpenAI
Meta
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