AI Engineer World's Fair 202620:42
CrabRAG: Why Automated Assistants Need Graph Memory, Not More Tokens
Stephen Chin
RAG, context, and search · Safety and governance · APIs, MCP, and protocols
← Featured AI Engineer talks
The talk archive.
1,011 published talks.
AI Engineer Summit 202524:22
Creating Agents That Co-Create
Karina Nguyen
Data and model adaptation · Coding and developer tools · Enterprise
AI Engineer World's Fair 202424:21
Creating and scaling your own custom copilots with Azure AI Studio
Hanchi Wang
Coding and developer tools · RAG, context, and search · Safety and governance
AI Engineer World's Fair 202519:04
Critical AI Inference Your CIO Can Trust
Sahil Yadav · Hariharan Ganesan
Safety and governance · Leadership · Industry applications
AI Engineer World's Fair 202418:55
Customized, production ready inference with open source models: Dmytro (Dima) Dzhulgakov
Dmytro (Dima) Dzhulgakov
RAG, context, and search · Architecture · Infrastructure and deployment
AI Engineer Europe 202616:44
Dark Factory: OpenClaw Ships Faster Than You Can Read the Diff
Vincent Koc
Infrastructure and deployment · Leadership · Reasoning and models
AI Engineer World's Fair 202619:12
Data and Environment Curation for Post-training LLMs
Mahesh Sathiamoorthy
Coding and developer tools · Reasoning and models · Data and model adaptation
AI Engineer World's Fair 202520:10
Data is Your Differentiator: Building Secure and Tailored AI Systems
Mani Khanuja
Data and model adaptation · Safety and governance · RAG, context, and search
AI Engineer World's Fair 202619:05
Data Quality is the Compute Multiplier
Ari Morcos
Data and model adaptation · Infrastructure and deployment · Industry applications
AI Engineer World's Fair 202517:02
"Data readiness" is a Myth: Reliable AI with an Agentic Semantic Layer — Anushrut Gupta, PromptQL
Anushrut Gupta
Enterprise · Leadership · RAG, context, and search
AI Engineer World's Fair 202418:16
Decoding Mistral AI's Large Language Models
Devendra Chaplot · Devendra Singh Chaplot
Evals · Coding and developer tools · RAG, context, and search
AI Engineer World's Fair 202617:34
DeepSWE: A Contamination-Resistant Coding Benchmark — James Shi, Datacurve
James Shi
Evals · Developer workflows and testing · Coding and developer tools
AI Engineer World's Fair 202541:05
#define AI Engineer
Greg Brockman · swyx · Jensen Huang
Architecture · Leadership · Coding and developer tools
AI Engineer Code 202525:10
Defying Gravity
Kevin Hou
Leadership · Agent engineering · Vision and video
AI Engineer World's Fair 202519:26
Design like Karpathy is watching 😎
Zeke Sikelianos
APIs, MCP, and protocols · Creative and generative media · Coding and developer tools
AI Engineer World's Fair 202619:46
Designing Agents (The Floor Is the Frontier)
Ben Hylak
Evals · Infrastructure and deployment · Agent engineering
AI Engineer World's Fair 202513:02
Designing AI-Intensive Applications
Shawn Wang (swyx)
Enterprise · Agent engineering · APIs, MCP, and protocols
AI Engineer World's Fair 202512:24
Designing AI to Scale Human Thought
Jun Yu Tan
Agent engineering · Coding and developer tools · Other / unclassified
AI Engineer World's Fair 202632:57
Designing Voice Agents for Real Conversations
Chintan Agrawal · Daniel Wirjo
Speech and audio · Reasoning and models · Architecture
AI Engineer World's Fair 202615:28
Develop at Idea Velocity
Jeffrey Lee-Chan
Safety and governance · Reasoning and models · Agent engineering
AI Engineer Code 202518:20
Developer Experience in the Age of AI Coding Agents
Max Kanat-Alexander
RAG, context, and search · Coding and developer tools · Leadership
AI Engineer Code 202520:52
Developing Taste in Coding Agents: Applied Meta Neuro-Symbolic RL — Ahmad Awais, Command Code
Ahmad Awais
Coding and developer tools · Other / unclassified · Data and model adaptation
AI Engineer World's Fair 202516:13
Devin 2.0 and the Future of SWE
Scott Wu
Coding and developer tools · RAG, context, and search · Developer workflows and testing
AI Engineer Code 202517:58
Dispatch from the Future: building an AI-native Company – Dan Shipper, Every, AI & I
Dan Shipper
RAG, context, and search · Coding and developer tools · Leadership
AI Engineer Europe 202618:54
Does GenAI "belong" to data scientists?
Phil Hetzel
Evals · Reasoning and models · RAG, context, and search
AI Engineer Summit 202325:09
Domain adaptation and fine-tuning for domain-specific LLMs
Abi Aryan
Reasoning and models · Infrastructure and deployment · RAG, context, and search
AI Engineer World's Fair 202616:46
Don't be data poor
Anuj Iravane
Data and model adaptation · Healthcare
AI Engineer Europe 202618:52
Don't Build Slop (4 Levels of AI Agent Maturity)
Ara Khan
Agent engineering · Coding and developer tools · Infrastructure and deployment
AI Engineer World's Fair 20255:45
Don’t get one-shotted: Use AI to test, review, merge, and deploy code — Tomas Reimers, Graphite
Tomas Reimers
Coding and developer tools · Developer workflows and testing · Other / unclassified
AI Engineer Summit 20255:46
Don't just slap on a chatbot: building AI that works before you ask
Arthur Objartel
APIs, MCP, and protocols · Enterprise · RAG, context, and search
AI Engineer World's Fair 20266:08
Don't Let the LLM Drive - Ornella Bahidika & Joel Allou, Microsoft
Ornella Bahidika · Joel Allou
Agent engineering · Speech and audio · Other / unclassified
AI Engineer World's Fair 202621:46
Don't Ship Skills Without Evals
Philipp Schmid
Evals · Agent engineering · RAG, context, and search
AI Engineer World's Fair 202519:03
Dream Machine: Scaling to 1m users in 4 days — Keegan McCallum, Luma AI
Keegan McCallum
Infrastructure and deployment · Creative and generative media · Other / unclassified
AI Engineer Code 20251:13:13
DSPy: The End of Prompt Engineering
Kevin Madura
RAG, context, and search · Observability and reliability · Coding and developer tools
AI Engineer World's Fair 202428:13
E-Values: Evaluating the Values of AI
Sheila Gulati · Nischal Nadhamuni
Architecture · Evals · Finance
AI Engineer World's Fair 202515:38
Effective agent design patterns in production
Laurie Voss
Coding and developer tools · Architecture · RAG, context, and search