Priya Mathew Badger

How to Prototype LLM Powered Features

Yelp

Gopuff

Google

Codeverse

eSpark

Principal PM at Yelp for Yelp's AI Assistant

Learn to simply communicate your idea to both stakeholders and prototyping tools

Outline needs for your AI feature or product

Get an overview of the tools landscape and how to select what to use

Learn the approaches for prototyping LLM powered features

Follow along as I build an LLM powered prototype live

Live demo of prototyping an LLM powered feature

Build your first AI prototype next week -- even if you have no coding skills

Build your first AI prototype next week

Colin Matthews

Sold my first SaaS in 2021. Product Manager, 8500+ students, featured by Lenny.

Cohort 8

Cohort 9

Have you seen other PMs leveraging AI to ship prototypes at lightning speed , but when you try it yourself:- Basic tutorials leave you stuck on simple examples ?- Technical obstacles slow your momentum ?- Debugging feels impossible without coding experience ?- You're unsure which AI tools actually deliver value ? You know mastering AI prototyping could transform your workflow. But the path from curiosity to confidence isn't clear. With AI, you can build functional prototypes in minutes. The challenge with AI prototyping isn't getting started — it's understanding what these tools can and can't do. That’s why this cohort is designed to expose you to essential AI prototyping tools and their unique capabilities. You'll learn to debug issues (even without coding experience) to stay productive and deliver real value. And our community will be here to give you the support, guidance, and accountability you’ll need to finally stick with it. In just 4 weeks, you'll go from zero experience to shipping multiple prototypes -- from interactive prototypes to accompany your PRD, to personalized tools that boost your productivity.

Convert your PRD to a prototype in minutes

Discover AI prototyping tools

Master debugging

Integrate with LLMs

Bring your design system

Senior Product Managers who want to leverage AI to iterate faster

Product Leaders who want to get first-hand experience with how AI is transforming product development

UX Designers who want to translate their designs into functional prototypes the same day

If you’re a software engineer or data scientist, chances are you’ve built or seen a proof of concept (POC) for a generative AI app. It’s exciting at first, an impressive demo that showcases the potential of large language models. Here’s the problem: that’s where it usually stops. These POCs often fail to scale into reliable, production-ready applications. The result? Endless iteration cycles, unreliable outputs, and frustration as teams struggle in what we call “POC purgatory.” It doesn’t have to be this way. With the right principles, processes, and workflows, you can build LLM applications that work in production, without overcomplicating pipelines or chasing trends. This course focuses on the iterative development, evaluation, and debugging practices that make AI systems production-ready. You'll learn how to build with state-of-the-art tools like RAG, fine-tuning, MCP, and agents, but the emphasis is on building scalable, robust systems, ensuring you leave with the mindset and skills to adapt as the technology evolves. You’ll not only learn how to design, test, and deploy generative AI applications, but also how to iterate and improve rapidly. This is about creating AI systems that solve real problems, deliver real value, and scale with confidence. What to ExpectThis is a highly interactive course designed to get you results. Across live workshops, discussions, and hands-on projects, you’ll build your skills while solving real-world challenges. •	Live coding sessions to design and refine LLM applications.•	Hands on exercises to explore how small changes can dramatically improve reliability.•	Discussions on user-centric development and integrating feedback loops.•	Expert-led Q&amp;As to help you tackle your toughest challenges. What You’ll Learn •	How to transform POC demos into production-grade applications.•	Strategies for managing non-determinism and optimizing outputs through prompt engineering.•	How to monitor, log, and debug AI systems to ensure reliability and performance.•	Best practices for handling structured outputs and integrating function calling into your applications.•	Building workflows for iterative development and experimentation.•	Practical skills through hands-on app development, including creating a Generative AI app to query PDFs. Bonus Perks All students receive over $500 credits to build with from top companies. We'll announce additional partner credits soon. Past cohorts have typically received $1,500+ in total credits; one cohort topped $2,500 when multiple partners stacked. (Actual amounts vary.) You will receive - $500 in Modal credits for cloud compute (confirmed).- Additional partner credits: announcing soon.- Past totals: $1,500+ typical; one cohort &gt;$2,500.- Recent partners: Google Cloud &amp; Gemini, Hugging Face Pro, Braintrust, Baseten, Chroma Cloud, Pydantic Logfire, Prodigy, Learn Prompting Plus, Replicate, and Mistral. Guest lectures Learn directly from practitioners shipping AI/LLM systems in production. This cohort's guest speakers will include We'll announce guest speakers soon. Enrollment includes on-demand access to all recorded guest talks from prior cohorts (plus slides/resources). Previous guest speakers in previous cohorts include: - Jason Liu (Instructor, 567 Labs)- Shreya Shankar (UC Berkeley, ex-Google Brain)- Zach Mueller (Hugging Face)- Paige Bailey (Google DeepMind)- Ines Montani (Explosion AI, spaCy)- Alan Nichol (Rasa)- Nathan Danielsen (Carvana)- Charles Frye (Modal)- John Berryman (Arcturus, ex-Github)- Skylar Payne (AI executive for startups. Ex-Google. Ex-LinkedIn)- Vincent Warmerdarm (marimo)- Samuel Colvin (Pydantic, Logfire)- Hamel Husain (Parlance Labs)- Samuel Colvin (Pydantic)- Jeff Huber (Chroma)- Natalia Rodnova (Eon)- Thomas Wiecki (PyMC Labs)- Ravin Kumar (DeepMind) This Course Is For •	Data scientists and machine learning engineers who are sick of unreliable POCs and want to ship reliable LLM applications.•	Software engineers who want to learn how to build generative AI systems and master the LLM software development lifecycle. This Course Is Not For Those •	Looking for an introductory course in AI: some programming knowledge is required.•	Expecting ready-made solutions for AI problems without active participation.•	Unable to commit to hands-on projects, live discussions, and iterative development exercises. Why Take This Course By the end of this course, you’ll: •	Understand the first principles of generative AI development.•	Gain hands-on experience building robust, scalable applications.•	Learn how to troubleshoot, monitor, and optimize AI systems for production.•	Develop workflows to iterate and refine AI applications effectively.•	Leave with the confidence to deploy reliable AI systems at scale.

Master the patterns and processes that underpin successful GenAI app development

Course syllabus

Mondays and Wednesdays

To ensure hands-on practical time, there will be project work to complete throughout the course.

Weekly projects

Course schedule

Data scientists, machine learning engineers who are sick &amp; tired of seeing and building prototypes &amp; want to ship reliable LLM applications

Software engineers who want to learn how to build Generative AI systems and learn the LLM software development lifecycle.

Who is this course for

What you’ll get out of this course

You’ve seen impressive generative AI demos, but how do you take them to production? In this course, you’ll learn the exact workflows, tools, and engineering practices needed to turn concepts into reliable, scalable applications that deliver real value.

Move beyond POCs and build production-ready AI systems

Struggling with inconsistent outputs? Through interactive exercises, you’ll explore proven techniques for optimizing prompts and ensuring your AI delivers actionable results in production settings.

Master prompt engineering for reliable results

When your AI application breaks, you’ll know exactly how to fix it. We’ll walk you through real-world debugging sessions, monitoring techniques, and tools to ensure your systems stay reliable at scale.

 Learn to debug and monitor AI systems like a pro

Learn everything you need to build robust and reliable agentic systems, from incorporating tool-calling, memory and retrieval to augmented LLM workflows and beyond.

Build State-Of-The-Art AI Agents

Stop wasting time in endless iteration cycles. Through guided projects, you’ll discover how to set up workflows that refine your applications faster and with less frustration, and how to use "Evals" and LLM Judges to guide your software development lifecycle.

Accelerate your development process with iterative workflows, best-in-class "Evals", and LLMs-as-Jduge

Tired of theoretical knowledge? You’ll build a fully functional app that uses text and image models to query PDFs, giving you practical experience solving complex real-world problems.

Develop hands-on expertise by building GenAI and LLM apps

Whether you’re looking to lead AI projects, impress stakeholders, or level up your technical expertise, this course gives you the tools to stand out as an AI/ML practitioner.

Advance your career with practical, proven techniques

Leave the course with a project you can add to your portfolio, demonstrate to your boss, or use to showcase your ability to deploy reliable AI systems.

Showcase Tangible Results

Build AI-powered software reliably & from first principles. Learn the GenAI software development lifecycle: agents, evals, iteration & more

Hugo Bowne-Anderson

Host of Vanishing Gradients podcast; ex-Outerbounds; expert in DS/ML.

Stefan Krawczyk

Agentforce; Ex-Stitch Fix; 13+ Years building / productionizing data, ML, Agents

Cohort 4

Cohort 5

Build, evaluate, and ship successful AI products with real-world frameworks and hands-on experience to become an advanced AI product leader

AI PM Leader | ex Spotify, Apple, Cruise

Apple

Spotify

Arize AI

Cruise

Aman Khan

Product leader at Arize AI, Spotify, Cruise, and Apple

Cohort 3

This is not a theoretical course about AI concepts. We'll of course teach you about the fundamentals of Agents, RAG and other AI concepts, but the purpose of this course is to get hands on. You’ll build real agents, evals and develop implementation plans!This course is a practical roadmap for PMs who want to go from "I understand what RAG is" to "I shipped an AI product that customers love." This is best suited for PMs who have at least played around with prototyping tools like Replit, Bolt but are looking to bring AI features from prototype to production inside their companies.- 4 week live sprint: 8 interactive live sessions and 3 office hours per week packed with vibe-coding labs, eval workshops, and peer feedback loops.- Built by and led by a current practitioner – I’m sharing the playbook I use as Head of Product at Arize AI (supports companies like Uber, Instacart, Discord, Reddit) and Spotify to help hundreds of engineers launch AI-powered products.- I'll also host a dedicated Slack community where you can communicate with me and other participants.- All sessions will be recorded and available to students asynchronously.

Design, prototype, and ship AI-powered products that delight customers

Build and deploy functional AI agents for your personal and team workflows

Evaluate AI product performance

Become proficient at using coding agents

Define Your H1/H2 AI Roadmap

Go from prototype to production

We'll help you get Cursor set up, but some familiarity with coding/debugging will go a long way here (i.e. being able to read python code)

Familiarity with code recommended (but not required)

Product Managers familiar with AI terms and concepts (LLMs, RAG, etc.) that wants to move beyond prompting to building actual AI products

PMs transitioning to AI-focused roles who see AI product leadership as their career differentiator in the next 1-2 years

Product Leaders and Executives responsible for AI strategy who need practical frameworks for evaluating and implementing AI initiatives

Two related skills in one course: master tech to speak the same language with your team. Use it to AI-prototype features or a side project.

Lead PM @ Booking.com, PhD

Vladimir Kalmykov 

PhD Computer Science, first Tech PM in Booking.com, author at ProductDo.io 

Oct'25

Jan'25

✅ Why invest in learning with me?I’m a Lead PM at Booking.com, and one of the first tech PMs there, with over 10 years in the field.Before moving into product, I was a Software Developer and earned a PhD in Computer Science. I’ve worked on both sides and know exactly what technical understanding PMs need - and don't.I'll teach you exactly what matters (and why) for driving products forward. You'll get the technical and AI-building fluency needed to drive your team, no coding, no database internals, no load balancers.✅ What can better technical understanding do for your career?From a survey of 650 PMs, 56% want to speak the same language as their engineers to communicate effectively, and build trust.61% want to estimate features on their own, so they can plan better and deliver on time.And today, technical understanding also lets you quickly AI-prototype features (43%) to show it to real users. In return, AI-building allows you to better understand Tech.Finally, if you want to land a Big Tech PM role, tech skills are critical.✅ What makes this course different?The course is 20% theory and 80% hands-on:&nbsp;you’ll do over 200 exercises / 8 projects, because that’s how real skills stick.

The technical understanding a successful PM needs - nothing more.

Gain tech fluency to lead your team effectively

Gauge feature complexity without devs and write solid PRDs

Prepare to handle technical interviews

Turn ideas into clickable full-stack prototypes or even start a side-project

The course is designed to explain the tech foundations and AI-building from the first (intuitive) principles.

No prior tech or AI experience needed

Senior Product Managers who want to level up their technical acumen

Jr/Middle Product Managers who want to lead with confidence and accelerate their growth

Program/Project Managers, Producers, Designers, Data Analysts, because tech foundations are the same for everyone