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The New Application Layer - Malte Ubl, CTO Vercel
AI engineering is the legitimate successor to web development and the mainstream discipline that will define the next decade. Drawing on Vercel's own experience, Malte explores what it means to bui...
Code Mode: Let the Code do the Talking - Sunil Pai, Cloudflare
Sunil Pai from Cloudflare discusses "Code Mode," an approach to interacting with AI agents where the model generates executable code (such as JavaScript) instead of relying on traditional JSON-base...
The Future of MCP — David Soria Parra, Anthropic
In this Keynote, I will lay out what I believe will be true for agents in 2026 and how MCP plays a part in this. Let's take a look what connectivity for agents might look like. Speaker info: - htt...
How Google DeepMind is researching the next Frontier of AI for Gemini — Raia Hadsell, VP of Research
In this presentation, Raia Hadsell, VP of Research at Google DeepMind and AI Ambassador for the United Kingdom, opens AIE Europe and explores what's open in Frontier AI and the future of intelligen...
The Friction is Your Judgment — Armin Ronacher & Cristina Poncela Cubeiro, Earendil
In this talk, Armin Ronacher (creator of Flask) and Cristina Poncela Cubeiro explore the paradox of using AI coding agents: while these tools promise to "ship without friction," excessive speed oft...
State of the Claw — Peter Steinberger
Peter Steinberger gives the 5 month update on OpenClaw, the fastest growing open source project in history, and what it's like as a maintainer, from security to community. Keynote followed by audie...
Harness Engineering: How to Build Software When Humans Steer, Agents Execute — Ryan Lopopolo, OpenAI
https://openai.com/index/harness-engineering/ Speaker info: - https://x.com/_lopopolo - https://www.linkedin.com/in/ryanlopopolo/ - https://github.com/lopopolo With a special post keynote Q&A wit...
Building pi in a World of Slop — Mario Zechner
All I wanted was a shitty coding agent that is truly mine. And I’d have loved to just tell you why and how I built pi. But then Peter decided to make it the agentic core of OpenClaw. And now pi is ...
$1 AI Guardrails: The Unreasonable Effectiveness of Finetuned ModernBERTs – Diego Carpentero
LLM-based attacks are no longer the exception, they are the baseline. This talk maps the six most common attack vectors found in production AI systems: Prompt and Context Injection, Model Internals...
Paperclip: Open Source Human Control Plane for AI Labor — Dotta Bippa
Curator note: Dotta is anonymous, so we asked him to submit with just an avatar. He did amazing! Paperclip enables open source orchestration for zero-human companies. With Paperclip you can manage...
AIE Europe Keynotes & Coding Agents ft. Pi, Google Deepmind, Anthropic, Cursor, Linear, & more
April 10, 2026 - all times in GMT+1 (UK Time) Timestamps 00:10:40 - Tejas Kumar opens Day 2 of AI Engineer Europe 00:15:44 - Omar Sanseviero (Google DeepMind): Gemma 4's on device capabilities and...
One Registry to Rule them All - Sonny Merla, Mauro Luchetti, & Mattia Redaelli, Quantyca
As internal MCP servers and A2A agents explode in number, discovery and governance become critical challenges for production-grade AI systems. We'll demonstrate how we built an enterprise infrastru...
Judge the Judge: Building LLM Evaluators That Actually Work with GEPA — Mahmoud Mabrouk, Agenta AI
Miscalibrated evals are worse than no evals. They give false confidence while being, at best, useless. This workshop walks you through building a calibrated LLM-as-a-judge, from capturing ground tr...
AI Didn’t Kill the Web, It Moved in! — Olivier Leplus (AWS) & Yohan Lasorsa (Microsoft)
In 2026, AI didn't replace the web. It became part of it. Your browser now ships a built-in MCP server. Chrome DevTools debug your app with AI. Native Web APIs let you summarize, translate, and pro...
Running LLMs locally: Practical LLM Performance on DGX Spark — Mozhgan Kabiri chimeh, NVIDIA
Moving LLM workloads from the cloud to local infrastructure requires a shift in engineering strategy. In this talk, I share my journey of serving and benchmarking open-source models (1.5B to 14B) o...
AIE Europe Keynotes & OpenClaw ft Deepmind, OpenAI, Vercel, @pragmaticengineer , @mattpocockuk
Timestamps 00:13:10 - Opening remarks by Phil Hawksworth 00:21:26 - Lia McBride (AI Engineer): AIE community's 900% growth and UK gov's AI infrastructure investment. 00:24:25 - Malte Ubl (Vercel): ...
Contact Center Voice AI: Low-Latency Intelligence Extraction from Messy Audio Streams — Dippu Singh
"Processing real-time voice data is an engineering minefield of latency, accents, and interruptions. This session explores the architecture of a Real-Time Voice Intelligence Pipeline deployed in a ...
OpenRAG: An open-source stack for RAG — Phil Nash
There are many variables in building RAG applications, from document parsing to the language model you pick for generation and everything in between. Combining Docling for document parsing, OpenSea...
From Chaos to Choreography: Multi-Agent Orchestration Patterns That Actually Work — Sandipan Bhaumik
One AI agent is a feature. Fifty agents is a distributed systems problem nobody's discussing. I've seen this pattern: teams build one agent, then five, then drown in coordination problems unrelated...
Cognitive Exhaust Fumes, or: Read-Only AI Is Underrated — Šimon Podhajský, Head of AI, Waypoint
Every other personal AI demo has agents sending emails and managing calendars. I built the opposite: a read-only system that queries my data sources (email, journal, tasks, CRM, browser sessions, n...
Platforms for Humans and Machines: Engineering for the Age of Agents — Juan Herreros Elorza
As AI coding agents become first-class users of internal developer platforms, the practices that make platforms accessible to humans turn out to be the same ones that enable AI to thrive. Self-ser...
Why, and how you need to sandbox AI-Generated Code? — Harshil Agrawal, Cloudflare
We are using AI to write code. Moreover, we are using it to be more productive. However, giving AI access to our machine and let them run on their own is dangerous. Imagine, giving AI access to the...
Your Insecure MCP Server Won't Survive Production — Tun Shwe, Lenses
Tun Shwe and Jeremy Frenay from Lenses.io address the critical security and design challenges involved in moving Model Context Protocol (MCP) servers from local development to enterprise production...
Let LLMs Wander: Engineering RL Environments — Stefano Fiorucci
Reasoning models like DeepSeek R1 have demonstrated that learning from interaction is just as critical as learning from examples. To build these capabilities ourselves, we need to move beyond stati...
Bending a Public MCP Server Without Breaking It — Nimrod Hauser, Baz
Public MCP servers often look ready-to-use, until the reality of production hits. You might find your agents ignoring perfectly good tools, unwanted side-effects exhausting your container's disk sp...
Agentic Engineering: Working With AI, Not Just Using It — Brendan O'Leary
Coding agents are quickly moving from novelty to necessity, but most teams are still stuck between demos that feel magical and systems that break down in real-world engineering environments. In thi...
How METR measures Long Tasks and Experienced Open Source Dev Productivity - Joel Becker, METR
AI models are crushing benchmarks. SWE-bench scores are climbing, and METR's measured time horizons are rising rapidly. Yet when we deployed these same models in a field study with experienced deve...
Build a Real-Time AI Sales Agent - Sarah Chieng & Zhenwei Gao, Cerebras
Learn how to build a sophisticated real-time voice sales agent that can have natural conversations with potential customers. You'll create both single-agent and multi-agent systems where specialize...
Identity for AI Agents - Patrick Riley & Carlos Galan, Auth0
Implementing secure identity and access management for AI agents with Okta! https://www.linkedin.com/in/patmriley/ https://www.linkedin.com/posts/cgcladera_auth0-for-ai-agents-secure-agentic-apps-...
OpenAI + @Temporalio : Building Durable, Production Ready Agents - Cornelia Davis, Temporal
Everyone is building AI Agents, and everyone is looking for ways to build them more easily. Earlier this year, OpenAI released the OpenAI Agents SDK to bring the patterns they have found to work fo...
Your MCP Server is Bad (and you should feel bad) - Jeremiah Lowin, Prefect
Too many MCP servers are simply glorified REST wrappers, regurgitating APIs that were designed for SDKs, not agents. This leads to confused LLMs, wasted tokens, and demonstrably poor performance. I...
Spec-Driven Development: Agentic Coding at FAANG Scale and Quality — Al Harris, Amazon Kiro
In the AI coding era, we have powerful tools, but tools still require honing to work effectively. Spec-Driven Development allows for reproducible and reliable delivery, but spending time up-front t...
DSPy: The End of Prompt Engineering - Kevin Madura, AlixPartners
Applications developed for the enterprise need to be rigorous, testable, and robust. The same is true for applications that use AI, but LLMs can make this challenging. In other words, you need to b...
Automating Large Scale Refactors with Parallel Agents - Robert Brennan, OpenHands
Today's agents are best at small, atomic coding tasks. Much larger tasks--like major refactors and breaking dependency updates--are highly automatable but hard to one-shot. In this session, we'll ...
Build a Prompt Learning Loop - SallyAnn DeLucia & Fuad Ali, Arize
Following from Aparna's talk: https://www.youtube.com/watch?v=pP_dSNz_EdQ Learn how to create a feedback loop to continuously improve your AI prompts and responses. https://www.linkedin.com/in/sa...
Building durable Agents with Workflow DevKit & AI SDK - Peter Wielander, Vercel
Learn to build and deploy AI agents using Vercel's new open source Workflows platform. https://twitter.com/vaguelyserious https://www.linkedin.com/in/peter-wielander
![Claude Agent SDK [Full Workshop] — Thariq Shihipar, Anthropic](https://i.ytimg.com/vi/TqC1qOfiVcQ/mqdefault.jpg)
Claude Agent SDK [Full Workshop] — Thariq Shihipar, Anthropic
Learn to use Anthropic's Claude Agent SDK (formerly Claude Code SDK) for AI-powered development workflows! https://platform.claude.com/docs/en/agent-sdk/overview https://x.com/trq212 **AI Summary...
Welcome to AIE CODE - Jed Borovik, Google DeepMind
Day 2 emcee Jed Borovik opens the day for coding agents and labs.
Building Intelligent Research Agents with Manus - Ivan Leo, Manus AI (now Meta Superintelligence)
AI agents are no longer confined to chat interfaces. From our original Manus app for powerful conversations, to Mail Manus for transforming your inbox into an organized command center, we've progre...
Jack Morris: Stuffing Context is not Memory, Updating Weights is
Understanding how memory works in large language models through the lens of weights and activations. This workshop will explore the internal mechanisms of how LLMs store and retrieve information du...
AGI: The Path Forward – Jason Warner & Eiso Kant, Poolside
In Poolside's first ever public conference demo, Poolside's CEOs present their vision and roadmap towards achieving AGI-level capabilities for knowledge work.
Shipping AI That Works: An Evaluation Framework for PMs – Aman Khan, Arize
GenAI is reshaping the product landscape, creating huge opportunities (along with new expectations) for product managers. Yet while prompt engineering and model tuning get the spotlight, one critic...
How Claude Code Works - Jared Zoneraich, PromptLayer
Deep dive into what we have independently figured out about the architecture and implementation of Claude's code generation capabilities. Not officially endorsed by Anthropic. Speaker: Jared Zoner...
Why Agent Hype can fall short of reality – Joel Becker, METR
AI models are crushing benchmarks. SWE-bench scores are climbing, and METR's measured time horizons are rising rapidly. Yet when we deployed these same models in a field study with experienced deve...
Small Bets, Big Impact Building GenBI at a Fortune 100 – Asaf Bord, Northwestern Mutual
Enterprises don’t usually make moonshots, especially in GenAI. Governance, budgets, and risk aversion make it almost impossible to justify a huge, uncertain investment. At Northwestern Mutual, we’...
Developer Experience in the Age of AI Coding Agents – Max Kanat-Alexander, Capital One
It feels like every two weeks, the world of software engineering is being turned on its head. Are there any principles we can rely on that will continue to hold true, and that can help us prepare f...
The Unreasonable Effectiveness of Prompt Learning – Aparna Dhinakaran, Arize
Your coding agent writes code—but not like your team. RL has boosted base models, but it’s opaque and hard to scale across enterprises. Most agents still rely on brittle, hand-edited system prompts...
Amp Code: Next Generation AI Coding – Beyang Liu, Amp Code
Introduction to Amp Code and its approach to AI-powered software development. Speaker: Beyang Liu | Co-founder & CTO, Amp Code https://x.com/beyang https://www.linkedin.com/in/beyang-liu/ https:...
Making Codebases Agent Ready – Eno Reyes, Factory AI
Agents are eating software engineering. Yet teams deploying these tools face mixed results. Agents work great in demos but fail unreliably in production, frustrating engineering teams who expected ...
The 3 Pillars of Autonomy – Michele Catasta, Replit
AI agents exhibit vastly different degrees of autonomy. Yet, the ability to accomplish objectives without supervision is the critical north star for agent progress, especially in software creation....