Media Summary: At this workshop, Eda Zhou & Mahdi Ghodsi from AMD explored building personal This talk by Cline's Ara Khan explains why they went from "evals are useless" to using them as a core part of my agent ... Paige Bailey gave us an overview of the latest model releases from Google DeepMind, especially in the multimodal space ...

Ai Dev 26 X Sf - Detailed Analysis & Overview

At this workshop, Eda Zhou & Mahdi Ghodsi from AMD explored building personal This talk by Cline's Ara Khan explains why they went from "evals are useless" to using them as a core part of my agent ... Paige Bailey gave us an overview of the latest model releases from Google DeepMind, especially in the multimodal space ... Building your first agent is exciting. Building a platform that can evolve into an office where dozens of teams can safely deploy ... In this talk, Ankit Mathur from Databricks, discussed the governance and security challenges of rolling out coding tools at ... In this talk by Zencoder's Andrew Filev, attendees learned how decomposing tasks into pipelines and dynamically routing them ...

As MCP systems scale from local setups to shared infrastructure, From centralized to distributed: In the old world, organizations relied on one centralized data and

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AI Dev 26 x SF: Andrew Ng: The Future of Software Engineering
AI Dev 26 x SF | Eda Zhou & Mahdi Ghodsi: Building Personal AI Agents with Open Source Models
AI Dev 26 x SF | Marc Brooker: It's Time to Be Right
AI Dev 26 x SF | Ara Khan: Evals Are Broken Use Them Anyway
AI Dev 26 x SF | Paige Bailey: What's New and What's Next in AI
AI Dev 26 x SF | Diamond Bishop: The Next 100 Agents. Building the Agent Native Office
AI Dev 26 x SF | Ankit Mathur: The Coding Agent Multiverse of Madness
AI Dev 26 x SF | Andrew K.  Davies: Deterministic Memory: How to Build an AI That Cannot Lie
AI Dev 26 x SF | Andrew Filev: Multi Model Pipelines—How to Get Better AI Results for Less
AI Dev 26 x SF | Matthew Xu: The 4-Legged Identity Challenge
AI Dev 26 x SF | Barun Singh & Kennith Jackson; The Hidden Cost of AI Velocity and AI Agents
AI Dev 26 x SF | Luke Kim: The Agent Data Stack—Why Every AI Agent Needs Its Own Data Stack
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AI Dev 26 x SF: Andrew Ng: The Future of Software Engineering

AI Dev 26 x SF: Andrew Ng: The Future of Software Engineering

At

AI Dev 26 x SF | Eda Zhou & Mahdi Ghodsi: Building Personal AI Agents with Open Source Models

AI Dev 26 x SF | Eda Zhou & Mahdi Ghodsi: Building Personal AI Agents with Open Source Models

At this workshop, Eda Zhou & Mahdi Ghodsi from AMD explored building personal

AI Dev 26 x SF | Marc Brooker: It's Time to Be Right

AI Dev 26 x SF | Marc Brooker: It's Time to Be Right

At

AI Dev 26 x SF | Ara Khan: Evals Are Broken Use Them Anyway

AI Dev 26 x SF | Ara Khan: Evals Are Broken Use Them Anyway

This talk by Cline's Ara Khan explains why they went from "evals are useless" to using them as a core part of my agent ...

AI Dev 26 x SF | Paige Bailey: What's New and What's Next in AI

AI Dev 26 x SF | Paige Bailey: What's New and What's Next in AI

Paige Bailey gave us an overview of the latest model releases from Google DeepMind, especially in the multimodal space ...

AI Dev 26 x SF | Diamond Bishop: The Next 100 Agents. Building the Agent Native Office

AI Dev 26 x SF | Diamond Bishop: The Next 100 Agents. Building the Agent Native Office

Building your first agent is exciting. Building a platform that can evolve into an office where dozens of teams can safely deploy ...

AI Dev 26 x SF | Ankit Mathur: The Coding Agent Multiverse of Madness

AI Dev 26 x SF | Ankit Mathur: The Coding Agent Multiverse of Madness

In this talk, Ankit Mathur from Databricks, discussed the governance and security challenges of rolling out coding tools at ...

AI Dev 26 x SF | Andrew K.  Davies: Deterministic Memory: How to Build an AI That Cannot Lie

AI Dev 26 x SF | Andrew K. Davies: Deterministic Memory: How to Build an AI That Cannot Lie

What if your

AI Dev 26 x SF | Andrew Filev: Multi Model Pipelines—How to Get Better AI Results for Less

AI Dev 26 x SF | Andrew Filev: Multi Model Pipelines—How to Get Better AI Results for Less

In this talk by Zencoder's Andrew Filev, attendees learned how decomposing tasks into pipelines and dynamically routing them ...

AI Dev 26 x SF | Matthew Xu: The 4-Legged Identity Challenge

AI Dev 26 x SF | Matthew Xu: The 4-Legged Identity Challenge

As MCP systems scale from local setups to shared infrastructure,

AI Dev 26 x SF | Barun Singh & Kennith Jackson; The Hidden Cost of AI Velocity and AI Agents

AI Dev 26 x SF | Barun Singh & Kennith Jackson; The Hidden Cost of AI Velocity and AI Agents

AI

AI Dev 26 x SF | Luke Kim: The Agent Data Stack—Why Every AI Agent Needs Its Own Data Stack

AI Dev 26 x SF | Luke Kim: The Agent Data Stack—Why Every AI Agent Needs Its Own Data Stack

From centralized to distributed: In the old world, organizations relied on one centralized data and

AI Dev 26 x SF | Melissa Herrera: Your Agents Should Be Durable

AI Dev 26 x SF | Melissa Herrera: Your Agents Should Be Durable

Building