Roberto Carratalá

One AI API to Power Them All

Stop wrestling with fragmented AI tools. Go from local development to a production cluster with one unified API for inference, RAG, and agents.

One AI API to Power Them All
#1about 5 minutes

The challenge of building production-ready AI applications

The current AI landscape is fragmented with many tools, making it complex to build, scale, and maintain applications with features like RAG and agents.

#2about 3 minutes

Introducing Llama Stack for a unified AI API

Llama Stack, an open-source project from Meta, provides a standardized, modular framework to simplify AI development with a single API for various components.

#3about 3 minutes

Standardizing model inference and safety guardrails

Llama Stack abstracts away differences between local and remote LLMs and integrates safety shields to filter harmful inputs and outputs.

#4about 2 minutes

Simplifying retrieval-augmented generation (RAG) pipelines

Llama Stack organizes the complex RAG process into three distinct, swappable layers for vector embeddings, retrieval, and agentic workflows.

#5about 4 minutes

Building AI agents using the Model Context Protocol

Llama Stack simplifies agent creation by integrating tools, orchestration, and reasoning models through the standardized Model Context Protocol (MCP).

#6about 3 minutes

Gaining application observability with built-in telemetry

Llama Stack provides out-of-the-box telemetry using OpenTelemetry, enabling developers to trace multi-step agent workflows with tools like Jaeger.

#7about 4 minutes

A local demo of inference, safety, and agents

This live demo showcases running Llama Stack locally to perform inference, block unsafe prompts, use an agent to check the weather, and inspect traces in Jaeger.

#8about 1 minute

Transitioning AI applications from local to production

Llama Stack enables a seamless transition from a local development setup to a scalable production environment on Kubernetes by maintaining a consistent API.

#9about 5 minutes

A production demo of a multi-agent business workflow

A complex agent interacts with multiple MCP servers to query a CRM, analyze customer data, send Slack notifications, and generate a PDF report.

Related jobs
Jobs that call for the skills explored in this talk.

Matching moments

Increasing the value of talk recordings post-event
04:57 MIN

Increasing the value of talk recordings post-event

Cat Herding with Lions and Tigers - Christian Heilmann

Organizing a developer conference for 15,000 attendees
01:32 MIN

Organizing a developer conference for 15,000 attendees

Cat Herding with Lions and Tigers - Christian Heilmann

Selecting strategic partners and essential event tools
03:17 MIN

Selecting strategic partners and essential event tools

Cat Herding with Lions and Tigers - Christian Heilmann

Automating video post-production with local scripts
02:54 MIN

Automating video post-production with local scripts

Cat Herding with Lions and Tigers - Christian Heilmann

Establishing a single source of truth for all data
02:39 MIN

Establishing a single source of truth for all data

Cat Herding with Lions and Tigers - Christian Heilmann

Why corporate AI adoption lags behind the hype
03:28 MIN

Why corporate AI adoption lags behind the hype

What 2025 Taught Us: A Year-End Special with Hung Lee

The future of recruiting beyond talent acquisition
03:15 MIN

The future of recruiting beyond talent acquisition

What 2025 Taught Us: A Year-End Special with Hung Lee

Breaking down silos between HR, tech, and business
03:39 MIN

Breaking down silos between HR, tech, and business

What 2025 Taught Us: A Year-End Special with Hung Lee

Featured Partners

Related Videos

See all videos
Self-Hosted LLMs: From Zero to Inference30:04

Self-Hosted LLMs: From Zero to Inference

Roberto Carratalá & Cedric Clyburn

The State of GenAI & Machine Learning in 202526:47

The State of GenAI & Machine Learning in 2025

Alejandro Saucedo

Agentic AI Systems for Critical Workloads30:01

Agentic AI Systems for Critical Workloads

Mario Fusco

DevOps for AI: running LLMs in production with Kubernetes and KubeFlow34:21

DevOps for AI: running LLMs in production with Kubernetes and KubeFlow

Aarno Aukia

Enterprise Integration Is Dead! Long Live AI-Driven Integration with Apache Camel32:24

Enterprise Integration Is Dead! Long Live AI-Driven Integration with Apache Camel

Bruno Meseguer & Markus Eisele

Azure AI Foundry for Developers: Open Tools, Scalable Agents, Real Impact23:33

Azure AI Foundry for Developers: Open Tools, Scalable Agents, Real Impact

Oliver Will

New AI-Centric SDLC: Rethinking Software Development with Knowledge Graphs15:26

New AI-Centric SDLC: Rethinking Software Development with Knowledge Graphs

Gregor Schumacher, Sujay Joshy & Marcel Gocke

Java Meets AI: Empowering Spring Developers to Build Intelligent Apps31:53

Java Meets AI: Empowering Spring Developers to Build Intelligent Apps

Timo Salm

Related Articles

View all articles
CH
Chris Heilmann
With AIs wide open - WeAreDevelopers at All Things Open 2025
Last week our VP of Developer Relations, Chris Heilmann, flew to Raleigh, North Carolina to present at All Things Open . An excellent event he had spoken at a few times in the past and this being the “Lucky 13” edition, he didn’t hesitate to come and...
With AIs wide open - WeAreDevelopers at All Things Open 2025

From learning to earning

Jobs that call for the skills explored in this talk.