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Practical tactics to build reliable AI apps — Dmitry Kuchin, Multinear
[last round of Attendee-Led 10min lightning talks] Practical tactics to build reliable AI apps. Reverse engineering real-world evals with o3. Nobody does it this way. Companies pay me $500/h for th...
How to Improve your Vibe Coding — Ian Butler
[last round of Attendee-Led 10min lightning talks] Are your vibes immaculate? - Vibe coding is the new hotness but everyone has a story of AI making really dumb choices. Let's talk about how you ca...
Vibes won't cut it — Chris Kelly, Augment Code
What's the role of vibe coding in a production-grade applications? Join Augment Code's Chris Kelly as he talks about the role of context in software engineering, not code. About Chris Kelly Chris ...
Real World Development with GitHub Copilot and VS Code — Harald Kirschner, Christopher Harrison
Join us to see how VS Code and GitHub Copilot's expanding suite of AI features can match or even surpasses the benefits of other popular AI developer tools. We'll focus on practical scenarios to e...
Building Agents at Cloud Scale — Antje Barth, AWS
Let's explore practical strategies for building and scaling agents in production. Discover how to move from local MCP implementations to cloud-scale architectures and how engineering teams lever...
State of Startups and AI 2025 - Sarah Guo, Conviction
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
Useful General Intelligence — Danielle Perszyk, Amazon AGI
We’re all hearing that AI agents will enable AGI, but they can’t yet reliably perform even basic computer tasks. It turns out that getting AI to click, type, and scroll is more challenging than get...
The 2025 AI Engineering Report — Barr Yaron, Amplify
Come hear the results of the 2025 State of AI Engineering: https://www.amplifypartners.com/blog-posts/the-2025-ai-engineering-report About Barr Yaon Barr is a data scientist turned investment part...
Agents vs Workflows: Why Not Both? — Sam Bhagwat, Mastra.ai
One current hot debate is should you make your top-level abstraction a ReAct type agent running in a loop? or should you make it a structured workflow graph? OpenAI is launching their new framewor...
Why We Don’t Need More Data Centers - Dr. Jasper Zhang, Hyperbolic
AI infrastructure today is caught in an endless cycle: build more data centers, deploy more GPUs, repeat. But this approach is fundamentally flawed—expensive, inefficient, and environmentally unsu...
Infrastructure for the Singularity — Jesse Han, Morph
We're at an inflection point where AI agents are transitioning from experimental tools to practical coworkers. This new world will demand new infrastructure for RL training, test-time scaling, and ...
Hacking the Inference Pareto Frontier - Kyle Kranen, NVIDIA
Your model works! It aces the evals! It even passes the vibe check! All that’s required is inference, right? Oops, you’ve just stepped into a minefield: -Not low-latency enough? Choppy experience....
Pipecat Cloud: Enterprise Voice Agents Built On Open Source - Kwindla Hultman Kramer, Daily
Voice AI agents today can conduct natural, human-like conversations and perform a wide variety of tasks: customer support, lead qualification, healthcare patient intake, market research, and more. ...
![[Full Workshop] Building Conversational AI Agents - Thor Schaeff, ElevenLabs](https://i.ytimg.com/vi/MPtCBaZn84A/mqdefault.jpg)
[Full Workshop] Building Conversational AI Agents - Thor Schaeff, ElevenLabs
In this workshop you will learn how to build multilingual Conversational AI agents that can automatically detect your user's spoken language and can seamlessly switch to their preferred language. ...
From Self-driving to Autonomous Voice Agents — Brooke Hopkins, Coval
The reliability challenges facing voice & chat AI deployment today mirror those that the autonomous vehicle industry confronted years ago. This talk explores how evaluation methodologies developed ...
Your realtime AI is ngmi — Sean DuBois (OpenAI), Kwindla Kramer (Daily)
Sean DuBois of OpenAI and Pion, and Kwindla Hultman Kramer of Daily and Pipecat, will talk about why you have to design realtime AI systems from the network layer up. Most people who build realtim...
Why ChatGPT Keeps Interrupting You — Dr. Tom Shapland, LiveKit
ChatGPT Advanced Voice Mode isn’t interrupting just you. Interruptions, and turn-taking in general, are unsolved problems for all Voice AI agents. Nobody likes being cut short – and people have muc...
Serving Voice AI at $1/hr: Open-source, LoRAs, Latency, Load Balancing - Neil Dwyer, Gabber
This is a talk that goes over our experience deploying Orpheus (Emotive, Realtime TTS) to production. It will cover topics: - Latency and optimizations - High fidelity voice clones w/ examples - L...
How to defend your sites from AI bots — David Mytton, Arcjet
Constantly seeing CAPTCHAs? It used to be easy to detect the humans from the droids, but what else can we do when synthetic clients make up nearly half of all web requests. Rotating IPs, spoofed br...
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 ...
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...
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...
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...