Claire Vo

Ship more with the AI tools you already have

LaunchDarkly

3x CPTO, Founder of ChatPRD and Host of How I AI

Zach Davis

Principal Engineer at LaunchDarkly, leading AI transformation across 100+ team

We'll cover the technical investments that that turn your repo into a platform where AI tools actually work.

Set agents (and humans) up to succeed in your codebase

Decide where to keep PRDs and how to integrate vibe-coded prototypes so that ideas can make it to production.

Structure the PRD to prod pipeline

A demo of how background agents can help both engineers and non-technical teammates contribute to code.

How to talk to background agents

Ship production features 2x faster by using coding agents across research, planning, implementation, testing, and review workflows

Creator of Stanford's AI Coding Course

Amazon

Stanford University

Y Combinator

Mihail Eric

Created Stanford's first AI coding class. Former YC founder and Amazon AI lead. 

Cohort 1

Cohort 2

Today many developers use AI, but few are maximally productive with it. I created Stanford's first AI software development class, and after building a YC-backed coding company and leading AI at Amazon, I've seen how top engineers integrate AI into production workflows. My techniques have been used to train 200+ Stanford engineers and industry professionals.My goal is simple: make you dramatically more productive writing software with AI than without it.In this course, you'll learn practical, end-to-end workflows for using AI in real-world development, not toy examples.We'll cover:<ul><li>Building production features with AI agents using the research → plan → implement → test workflow</li><li>Configuring an optimal AI native dev environment for your specific tech stack (IDE, code review, tool integrations, and beyond)</li><li>Setting up review and CI processes that catch AI errors, hallucinations, and slop before production</li><li>Enabling multiple agents to work together on the same codebase without conflict, accelerating software delivery and throughput</li></ul>If you're ready to write better code, ship to production faster, and stay in control of your coding agents, let's get started.

Increase developer productivity with AI-first, production-ready workflows

Configure optimal AI-first developer environments to improve your coding output

Learn how to navigate the ecosystem of cutting-edge AI developer tools 

Exercise effective strategies for prompting and building with coding agents

Reduce hallucinations, software errors, and AI slop all while shipping faster

Become a manager of coding agents so you can keep many agents productive 

Develop a deep intuition for how AI coding platforms work under-the-hood

Engineers who want to increase their productivity with AI-generated code while making it actually production grade.

Engineering managers who want to ensure their teams aren't being left behind when it comes to the new way of developing software.

Those confused about how to develop with AI the right way (how to maintain context and manage multiple agents without compromising code)

Master proven AI frameworks to automate HR tasks, build ethical policies, and lead strategic implementation that drives measurable impact.

CPO , Advisor & Future of Work Expert

Airbnb

Deloitte

Paper

Q Hamirani

Global CPO, Advisor & Educator shaping the future of people and AI

HR Leader, AI in HR Strategist

Walmart Global Tech

Cognizant

Tata Consultancy Services

Sandhiya Thiruvengadam

HR Leader & AI Strategist transforming how people and tech work together

People Professionals - Cohort 1

People Professionals - Cohort 2

AI is transforming HR but most teams are still stuck experimenting.Over the last year, we engaged with 2,500+ HR professionals and found that while 65% are exploring AI, only 13% have integrated it into workflows, and just 2% are driving measurable transformation.This 7-week, hands-on program closes that gap. Designed by HR leaders for HR leaders, it helps you move from curiosity to capability—building real AI prototypes, mastering compliant prompt frameworks, and designing safe, scalable workflows using tools like ChatGPT, Copilot, and Claude- even within your own Microsoft or other enterprise workspace.Each week blends live workshops, peer “shark tank” sessions, and executive deep-dives with CHROs and CPOs who’ve implemented AI successfully. By the end, you’ll walk away with a working HR solution, a 90-day rollout roadmap, and the confidence to lead AI adoption in your organization.If you’re ready to save time, amplify impact, and position yourself as an AI-forward HR professional, this course is your launchpad.

From Uncertain Experimenter to Confident AI Champion

How to identify high-impact AI opportunities—and when not to use tech

How to build your first working AI solution—without coding

How to experiment safely with AI tools

How to pitch your AI use case to leaders

How to build a 90-day roadmap for scaling AI in HR - YOUR Capstone Project

No technical background required . just an open mind and a drive to explore new possibilities in HR.

Curiosity

Access to the internet for course materials , tools and readiness to move beyond traditional HR methods.

A browser

Be ready to challenge old assumptions and most importantly, bring willingness to experiment, make mistakes, and iterate as you build.

Willingness to Unlearn

For early to mid-career HR pros (0-15 years): HRBPs, TA Specialists, Directors, People Ops Leaders.

You have a demonstrated interest in HR innovation; ready to be an AI innovator.

You're experimenting with AI but feel overwhelmed or unsure how to scale for real impact.

Stop no-code hacks. Start from zero. In 3 weeks, build with AI agents and ship on your domain.

AI Superpower Cohort 2

Built 16 AI Agents in 16 Weeks | Apple

Apple

LinkedIn

Udemy

Nathan Wang

AI Builder Shipping 1 AI Agent / Week | PhD Engineer/TPM @ Apple and Meta

AI Super Individual Cohort 1

You've seen AI demos. Maybe you've even vibe-coded one. But shipping a real AI Agent—with auth, a database, and actual users? That's where everyone gets stuck.This 3-week sprint, condensed from my <a target="_blank" rel="noopener noreferrer nofollow" href="https://ai-nate.com/mentoring.html">$9,800 private program</a>, takes you from zero to a live, deployed AI Agent on your own domain. No 6 months of syntax. No "no-code" ceilings.By the end, you will:<ul><li>🚀 Ship a live AI Agent—deployed for real users, not a localhost demo</li><li>🏗️ Understand the full stack—so you can evaluate and fix what AI generates</li><li>🤖 Work with the latest models—Claude, Gemini, and autonomous agent frameworks</li><li>🛠️ Skip the setup hell—using battle-tested auth, API, and deployment boilerplate</li></ul>We build together. You leave with a link, not a tutorial.

Demos Are Easy. Production Is Hard. Ship Your AI Agent in 3 Weeks.

Ship a Production AI Agent to Your Own Domain

Understand Full-Stack Architecture (Without Writing It From Scratch)

Build Autonomous AI Agents That Work While You Sleep

Conquer Auth, APIs, and Deployment in Hours (Not Months)

Evaluate and Fix AI-Generated Code With Confidence

Product &amp; Program ManagersStop waiting for engineers. Build high-fidelity prototypes yourself to validate ideas and unblock your roadmap.

Software &amp; Hardware EngineersYou know logic but hate the Web Stack. Use AI to bridge the gap and translate your rigor into shipping apps.

Founders &amp; EntrepreneursStop paying agencies $20k. Escape the "No-Code" trap. Build, deploy, and own your production stack in just 3 weeks.

Lead AI initiatives with clear goals, defensible evaluation, explicit risk decisions, and exec updates that drive alignment and investment.

CPO, GM xBraintrust, Nextdoor, OpenTable

Braintrust 🧠

Nextdoor

LiquidSpace I Work from where it works.

OpenTable

BlackRock

Elena Luneva

f-CPO. Product executive (Braintrust, Nextdoor, OpenTable, LiquidSpace)

Ex-Alexa AI Principal PM

Elsevier

Schneider Electric

Polly Allen

Ex-Alexa AI PM turned founder at AI Career Boost

Magic

AI increases IC leverage, but it also breaks the management systems most teams rely on.Prototypes multiply. “Quality” becomes subjective. Risk can ship quietly. Leadership gets pulled into every review because no one is sure what good looks like, or who is accountable for evaluation, failure modes, and rollout decisions.If you’re a Director, Head of Product/Eng/Data, or VP with multiple AI initiatives in flight, you’re likely seeing the same pattern: lots of demos, uneven production outcomes, rising cost and reliability questions, and execs asking, “How do we know it’s good?” “What can go wrong?” “What’s the ROI?”This workshop gives you a practical operating system for leading AI-native work without slowing teams down.You’ll leave with:<ul><li>a portfolio and cadence that prevents orphan prototypes and experiments, </li><li>repeatable review process to assess risk and evaluation throughout projects, and</li><li>a new 'operating system' for AI-forward teams so that AI progress translates into ROI</li></ul>The result: faster alignment, fewer surprises, and AI work that ships to production with confidence.

Lead AI-heavy teams with new playbooks for prototypes, risk assessment, and eval

Install an AI-native operating cadence that keeps speed and alignment

Run AI risk reviews that drive decisions and confidence

Own and drive evaluation metrics and process, before and after launch

Reclaim 5 hours a week using new AI-first playbooks

Director/Head of Product: Leads AI initiatives; turns prototypes into production with clear quality, gates, and exec updates.

Eng leader (Sr Mgr/Dir/VP): Ships AI fast while managing reliability, security, and cost with consistent eval + risk reviews.

Data/ML leader (Dir/Head): Owns evals and performance; aligns product and execs with shared language and decision-ready tradeoffs.