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Running AI agents in a local script is straightforward. Running them reliably in production across teams, across restarts, with isolated environments per context is a different problem entirely. BerriAI, the company behind the LiteLLM AI Gateway, is now open-sourcing a purpose-built answer to that problem: the LiteLLM Agent Platform. The platform is described as a simple, self-hosted infrastructure platform for running multiple agents in production. What Problem Does it Solve? It helps to understand what happens when you […]

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A single prompt can only take you so far. The real power unlocks when you connect outputs to inputs — building pipelines that tackle work no single prompt could ever handle alone. There is a hard limit to what a single prompt can accomplish. Not a context-window limit — a cognitive limit. When you ask an AI to simultaneously research a topic, synthesise findings, draft a document, adjust the tone, extract key points, and format everything for three different audiences, none of those […]

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Roles, context, format, and constraints — the four building blocks that separate a mediocre AI interaction from a truly powerful one. Most people hand the AI a task and wonder why the result feels generic. The reason is almost always the same: the task alone is not enough. A task tells the AI what to do. The four layers tell it how to do it — from whose perspective, with what background, in what form, and within what guardrails. Think of it like […]

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The critical first steps that determine whether your AI agent succeeds or fails in production — with real examples from banking, retail, and healthcare A healthcare startup spent six months building an AI agent for patient triage. They used the latest GPT-4 model. They hired experienced ML engineers. They built a beautiful interface. The demo impressed investors. Then they launched to real clinics. Within days, nurses stopped using it. The agent asked irrelevant questions. It missed critical symptoms. It provided inconsistent […]

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Hay empresas que no caen cuando dejan de ganar dinero, sino cuando dejan de poder explicarse moralmente. Meta parece estar entrando en esa fase. No porque sus beneficios hayan desaparecido, sino precisamente porque siguen ahí: una compañía con beneficios récord y una moral interna por los suelos, preparando nuevos despidos, con empleados que hablan de miedo, hartazgo, desigualdades salariales demenciales, vigilancia y una sensación creciente de haber perdido toda conexión con la supuesta «misión». La pregunta incómoda no […]

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