How large organizations will be transformed by AI?
What people and organizations are scared of because of AI?
What people do not know about AI Agents?
What enterprises need?
Why we might be wrong about Agents and LLMs impact all together?

Workflows optimization.…

A dive into the Blender MCP to see how it was made, what use cases for creators it unlocks, and how the future might look for creators.

In a world where AI is revolutionizing API documentation, many wonder: “Why can’t we just use AI to write the docs?” At Twilio, we’ve explored this question deeply. Our Developer Education team found that while generative AI is powerful, it still carries…

In this video, we walk through how our team built production-ready support agents using the Effect TypeScript library. The video includes a demo of the agent in action, along with a breakdown of the architecture and design decisions behind it.

We cover what…

There are typically two approaches to working with graphs: property graphs and RDF. These systems are often thought of as different knowledge graph paradigms optimized for different workflows. This talk examines how combining property graph interfaces with…

Why AI engineers must rethink what intelligence means in the age of large language models.

LLMs aren’t thinking.
No awareness. No reasoning. No plan.
And yet—they feel smart. Shockingly so.

This talk introduces coherence reconstruction, a mental model that…

Ever had an AI-generated tweak unexpectedly break your entire project? Agentic software development has impressive promise, but the reality still falls short. In this talk we introduce SM-100, a groundbreaking benchmark designed specifically to evaluate autonomous…

Evaluations are the single most reliable indicator of the health and long term viability of any gen AI project. As a Principal Applied AI Architect for AWS, I've had the opportunity to look at over 100 different attempts at evaluation frameworks over the…

Arrakis (https://github.com/abshkbh/arrakis) provides MicroVM-based secure sandboxes for code execution and full computer use. It features first-class support for backtracking, a Python SDK, and a Model Context Protocol (MCP) server.

In this talk, we go…

This talk introduces the concept of the 'Voice-First AI Overlay': an AI agent assisting conversations directly within the communication interface, operating either single-sidedly or mediating between participants.

I dive into the engineering and design of…

Are you just using AI—or are you building a company around it?

In this talk, I break down what it means to be an agent-native company—a business designed from the ground up with AI agents at the core of operations, culture, and product. Drawing from my own…

As LLMs move into enterprise workflows, developers face a new kind of architecture challenge: how do you build reliable, interpretable systems powered by agents and reasoning?

This talk unpacks how we designed and implemented an AI orchestration framework…

What happens when private AI models or sensitive data need to run in the public cloud?

Can we still maintain control – without relying on blind trust?
Can we eliminate that blind trust and make infrastructure verifiable by design?

In this talk, you’ll discover…

Cursor, v0, chai.new, lovable, bolt — what do they all have in common? They weren’t built on AI frameworks—they're built using primitives optimized for speed, scale, and flexibility.

LLMs are evolving fast—like, literally every week. New standards pop up…

AI agents are becoming smarter but lack the broad capability to take action in practice. At Smithery, we believe the missing link is an AI orchestration layer—a unified interface that gives agents context, action, and a way to learn from real interactions.…

Bem-vindo à Real Academy – O Caminho para a Soberania Total! 🚀

Chegou o serviço de assinatura da Educação Real 🥳

A Real Academy não é só uma plataforma de cursos. É um portal para sua liberdade. Aqui, você terá acesso a um ecossistema completo de aprendizado…

AI agents are powerful—but brittle. Once an agent chain starts, you either let it run or you tear it down and lose state. Agent Continuations change that contract. Borrowing from programming‑language continuations, we capture an agent’s entire call stack—tools…

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Leveraging automation and parallelism to scale out experiments

Monitoring is easy; what to monitor is not. In the field of machine learning, data drift is just noise until you know what it means.