Learn Loop Engineering in 30 Minutes

Hosted by Aki Wijesundara, PhD and Manisha Arora

Fri, Aug 21, 2026

5:00 PM UTC (30 minutes)

Virtual (Zoom)

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Go deeper with a course

Agentic AI Engineering Bootcamp and Certificate: Early Bird Discounted
Dr. Aki Wijesundara and Manu Jayawardana
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What you'll learn

From Prompts to Loops

Understand the shift from manually prompting an AI one exchange at a time.

Build Reliable Agent Loops

A 5-step framework every dependable AI agent is built on, mapped to real, working code.

Ship a Loop, Not Just a Demo

Walk a real example end to end, then leave with a practical checklist before you ship.

Why this topic matters

AI agents are moving from single-prompt assistants to systems that run on their own for minutes, hours, or even days. The gap between an agent that reliably finishes and one that quietly drifts, stalls, or burns through budget comes down to how well its loop is engineered. Loop engineering is quickly becoming a core skill for anyone building with AI.

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.

Manisha Arora

Data Science Lead at Google

I'm a data science and AI practitioner with 13+ years of experience leading teams and building systems that turn AI capability into real business impact - from ML models and experimentation to, more recently, agentic AI systems. In my current role at Google, I build

agentic AI systems that power insights for some of the company's largest advertisers. I'm passionate about democratising AI knowledge and helping others build the skills to keep pace as the field moves fast. I've taught 350+ professionals through my courses at Maven & PrepVector, and I'm committed to giving people the practical, hands-on skills needed to thrive as AI reshapes how products get built.

Works At

Google
PrepVector
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