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The Unofficial Guide to Apple’s Private Cloud Compute - Jmo, CONFSEC
In October 2024, Apple released a new private AI technology onto millions of devices called “Private Cloud Compute”. It brings the same level of privacy and security a local device offers but on an...
How to Secure Agents using OAuth — Jared Hanson (Keycard, Passport.js)
We all know sharing passwords is bad (unless you want free TV), so why are we sharing API keys with AI? We shouldn't, and that’s why we need to talk about OAuth. In this talk, we will give a brie...
How we hacked YC Spring 2025 batch’s AI agents — Rene Brandel, Casco
We hacked 7 of the16 publicly-accessible YC X25 AI agents. This allowed us to leak user data, execute code remotely, and take over databases. All within 30 minutes each. In this session, we'll walk...
OpenAI on Securing Code-Executing AI Agents — Fouad Matin (Codex, Agent Robustness)
Code is the lingua franca for both software engineers and highly capable AI models. As we give agents the ability to build, test, and run code that they generate, the command line becomes their can...
Evaluating AI Search: A Practical Framework for Augmented AI Systems — Quotient AI + Tavily
AI search is becoming the front door to information, whether through Retrieval-Augmented Generation (RAG), Search-Augmented Generation (SAG), or custom agents that synthesize answers on top of inde...
Scaling Enterprise-Grade RAG: Lessons from Legal Frontier - Calvin Qi (Harvey), Chang She (Lance)
In domains like law, compliance, and tax, building enterprise-grade RAG means very large scale, spikey workloads, a focus on accuracy, and non-negotiable privacy. In this talk, we'll share war stor...
Building Alice’s Brain: an AI Sales Rep that Learns Like a Human - Sherwood & Satwik, 11x
AI agents are becoming essential tools for teams of all sizes and industries - but training them to become experts in your product, business, and customerbase remains a challenge. What if onboardi...
Layering every technique in RAG, one query at a time - David Karam, Pi Labs (fmr. Google Search)
Start with the simplest Search - in-memory embeddings with relevance ranking. End with the most complex planet-scale Search - 70+ corpus mix of token, embeddings, and knowledge graphs, all jointly ...
Building a Smarter AI Agent with Neural RAG - Will Bryk, Exa.ai
RAG quality for AI agents is critical, and traditional keyword-based search engines consistently underperform in agentic or multi-step tasks, where semantic grounding and contextual nuance matter m...
![[Full Workshop] Building Metrics that actually work — David Karam, Pi Labs (fmr Google Search)](https://i.ytimg.com/vi/jxrGodnopHo/mqdefault.jpg)
[Full Workshop] Building Metrics that actually work — David Karam, Pi Labs (fmr Google Search)
One of the biggest challenges in building evals you can trust is building metrics that reliably measure goodness in your application; metrics that are highly accurate, rapid fast, and tunable to gr...
Make your LLM app a Domain Expert: How to Build an Expert System — Christopher Lovejoy, Anterior
Vertical AI is a multi-trillion-dollar opportunity. But you can't build a domain-expert application simply by grabbing the latest LLMs off-the-shelf: you need a system for codifying latent insights...
Shipping Products When You Don't Know What they Can Do — Ben Stein, Teammates
A customer recently asked me: “Hey, can I tag your AI agent in a Google Doc comment?” The honest answer: I have no idea! We never designed our agents to handle Google Doc comments, but we tried it...
Shipping something to someone always wins — Kenneth Auchenberg (ex. Stripe, VSCode)
Learnings from building products at Stripe and applying them in an AI native word. About Kenneth Auchenberg Partner at @alley_corp, investor focused on backing founders building for developers. P...
Why your product needs an AI product manager, and why it should be you — James Lowe, i.AI
So you've built another cool demo. Now what? You have hype, but not impact. You have kudos but no users. Ultimately you have a demo, but not a product. The unique uncertainty of AI technology dema...
Everything is ugly, so go build something that isn't — Raiza Martin, Huxe (ex NotebookLM)
We're in an awkward adolescent phase of AI product (design). But what if this chaotic moment is actually our greatest opportunity? Enter the rebuilding revolution. In this talk, we'll explore how ...
Building the platform for agent coordination — Tom Moor, Linear
Learn how we're evolving Linear into an operating system for engineering teams to ship product with agents as a first class citizen. About Tom Moor Tom Moor is the Head of Engineering at Linear, a...
What Is a Humanoid Foundation Model? An Introduction to GR00T N1 - Annika & Aastha
Foundation models don’t just write or draw anymore—they’re starting to move. GR00T N1 is NVIDIA’s open Vision-Language-Action (VLA) foundation model for humanoid robots. Built with a dual-system a...
Real-time Experiments with an AI Co-Scientist - Stefania Druga, fmr. Google Deepmind
The sheer volume of data and complexity of modern scientific challenges necessitate tools that go beyond mere analysis. The vision of an "AI Co-scientist" – a true collaborative partner in the lab ...
Scaling AI Agents Without Breaking Reliability — Preeti Somal, Temporal
As AI agents move from prototypes to production, developers are running into new challenges with orchestration, failure handling, and infrastructure. This session will unpack lessons from teams alr...
Government Agents: AI Agents vs Tough Regulations — Mark Myshatyn, Los Alamos National Laboratory
https://www.linkedin.com/in/markmyshatyn/
Ship Agents that Ship: A Hands-On Workshop - Kyle Penfound, Jeremy Adams, Dagger
Coding agents are transforming how software gets built, tested, and deployed, but engineering teams face a critical challenge: how to embrace this automation wave without sacrificing trust, control...
The AI Engineer’s Guide to Raising VC — Dani Grant (Jam), Chelcie Taylor (Notable)
A no fluff, all tactics discussion. More AI engineers should build startups, the world needs more software. But there’s a way to raise VC and it’s hard to do it if you’ve never seen it done. We are...
Strategies for LLM Evals (GuideLLM, lm-eval-harness, OpenAI Evals Workshop) — Taylor Jordan Smith
Accuracy scores and leaderboard metrics look impressive—but production-grade AI requires evals that reflect real-world performance, reliability, and user happiness. Traditional benchmarks rarely he...
Why you should care about AI interpretability - Mark Bissell, Goodfire AI
The goal of mechanistic interpretability is to reverse engineer neural networks. Having direct, programmable access to the internal neurons of models unlocks new ways for developers and users to in...
Information Retrieval from the Ground Up - Philipp Krenn, Elastic
Vector search is only a feature. Search engines and information retrieval have retaken their position as the foundation of RAG. This workshop takes you through decades of research, what has been wo...
Introduction to LLM serving with SGLang - Philip Kiely and Yineng Zhang, Baseten
Do you want to learn how to serve models like DeepSeek and Qwen with SOTA speeds on launch day? SGLang is an open-source fast serving framework for LLMs and VLMs that generates trillions of tokens ...
Robotics: why now? - Quan Vuong and Jost Tobias Springberg, Physical Intelligence
Sharing recent progress from Physical Intelligence and why it is an exciting time to push the frontier in general purpose robotics About Quan Vuong Quan Vuong is co-founder at Physical Intelligenc...
Waymo's EMMA: Teaching Cars to Think - Jyh Jing Hwang, Waymo
This session explores Waymo's latest research on the End-to-End Multimodal Model for Autonomous Driving (EMMA) and advanced sensor simulation techniques. Jyh-Jing Hwang will demonstrate how multimo...
A2A & MCP Workshop: Automating Business Processes with LLMs — Damien Murphy, Bench
Ever wished your webhooks could think for themselves? Join us to discover how A2A agents can transform passive webhook endpoints into intelligent workflow processors. In this session, we'll show y...
Piloting agents in GitHub Copilot - Christopher Harrison, Microsoft
The agent capabilities added to GitHub Copilot have enhanced its ability to act as a peer programmer. Copilot can now discover and generate code based on existing standards, run tests, recover from...
Ship Production Software in Minutes, Not Months — Eno Reyes, Factory
Planning, coding, testing, monitoring—the endless cycle that spans 10+ tools that fragment our focus and slows delivery to a crawl. Vibe coding doesn't work when you've got 10TB of code. If you jus...
Beyond the Prototype: Using AI to Write High-Quality Code - Josh Albrecht, Imbue
In this case study-based keynote, Josh Albrecht, CTO of Imbue, examines the critical engineering challenges in building AI coding systems that create more than just prototypes. Drawing from Imbue's...
Software Development Agents: What Works and What Doesn't - Robert Brennan, AllHands/OpenHands
The adoption of AI into software development has been bumpy. While autocomplete tools like Copilot have gone mainstream, autonomous agents like Devin and OpenHands have generated both enthusiasm an...
Devin 2.0 and the Future of SWE - Scott Wu, Cognition
A talk on the future of software engineering with Scott Wu of Cognition AI, the makers of Devin. About Scott Wu Scott is the co-founder and CEO of Cognition AI. He previously competed in internati...
Your Coding Agent Just Got Cloned And Your Brain Isn't Ready - Rustin Banks, Google Jules
Will the future engineer code alongside a single coding agent, or will they spend their day orchestrating many agents? Traditional development rewards synchronous focus. This session dives into the...
Latent Space Paper Club: AIEWF Special Edition (Test of Time, DeepSeek R1/V3) — VIbhu Sapra
Recorded at the AI Engineer World's Fair in San Francisco. Stay up to date on our upcoming events and content by joining our newsletter here: https://www.ai.engineer/newsletter Timestamps: 00:00:...
Human seeded Evals — Samuel Colvin, Pydantic
In this talk I'll introduce the concept of Human-seeded Evals, explain the principle and demo them with Pydantic Logfire. ---related links--- https://x.com/samuel_colvin https://www.linkedin.com/...
Building AI Products That Actually Work — Ben Hylak (Raindrop), Sid Bendre (Oleve)
You've made the demo. How do you make the product? A lot of AI products don't actually work. Even worse, a lot of the techniques being advertised for making AI products better don't work either. We...
Rise of the AI Architect — Clay Bavor, Cofounder, Sierra w/ Alessio Fanelli
As the amount of consumer facing AI products grows, the most forward leaning enterprises have created a new role: the AI Architect. These leaders are responsible for helping define, manage, and evo...
AI That Pays: Lessons from Revenue Cycle — Nathan Wan, Ensemble Health
While much of the AI innovation in healthcare has centered on clinical and patient-facing applications, Revenue Cycle Management (RCM) remains an underexplored yet critical domain. Given the growin...
Structuring a modern AI team — Denys Linkov, Wisedocs
You've been given an AI mandate but don't have additional headcount, what next? Re-skilling, up-skilling and team augmentation become essential to delivering on a new mandate. In this talk we'll co...
The Rise of Open Models in the Enterprise — Amir Haghighat, Baseten
This year kicked off with the DeepSeek-R1 news cycle breaking out of our AI Engineering bubble into the mainstream tech and business world. Leaders at the highest levels of the largest enterprises ...
Mentoring the Machine — Eric Hou, Augment Code
You’d never let a swarm of fresh interns ship to prod on day one—same deal with AI agents. Mentoring the Machine dives into how acting like a tech lead (not just a user) turns those bots into real ...
Building Applications with AI Agents — Michael Albada, Microsoft
Generative AI has dramatically shortened the distance between ideas and implementation, enabling faster prototyping and deployment than ever before. But while language models can streamline individ...
AX is the only Experience that Matters - Ivan Burazin, Daytona
If you’re building devtools for humans, you’re building for the past. Already a quarter of Y Combinator’s latest batch used AI to write 95% or more of their code. AI agents are scaling at an expo...
How to build Enterprise Aware Agents - Chau Tran, Glean
While LLMs demonstrated impressive reasoning capabilities, their out-of-the-box reasoning is akin to hiring a brilliant but brand-new employee who doesn’t have the enterprise context of “how things...
Monetizing AI — Alvaro Morales, Orb
As AI continues to transform industries, companies are faced with the critical challenge of effectively monetizing AI-driven products in a way that captures value, ensures customer adoption, and sc...
Does AI Actually Boost Developer Productivity? (100k Devs Study) - Yegor Denisov-Blanch, Stanford
Forget vendor hype: Is AI actually boosting developer productivity, or just shifting bottlenecks? Stop guessing. Our study at Stanford cuts through the noise, analyzing real-world productivity dat...
How agents will unlock the $500B promise of AI - Donald Hruska, Retool
AI agents are on the cusp of revolutionizing work as we know it. The number of use cases software can tackle is set to explode as AI handles tasks requiring real judgment. But to cross the gap betw...
How Intuit uses LLMs to explain taxes to millions of taxpayers - Jaspreet Singh, Intuit
I will talk about how Intuit uses LLMs to explain tax situations to Turbotax users. Users want explanations of their tax situations - this drives confidence in the product. Over the course of last...