Artificial Intelligence
RAG with Postgres and pgvector in production: from PoC to SLO
Embeddings, HNSW indexing, reranking, evaluation, context window, latency under load. Full stack with code and measurable SLOs.
Category
Artificial Intelligence
AI without the hype: models, agents and use cases that work in production.
Artificial Intelligence
Agent observability with OpenTelemetry GenAI semconv in 2026
The OTel GenAI spec stabilizes attributes for LLMs, tools, and agents. Practical Python implementation with Anthropic + Grafana Tempo.
Artificial Intelligence
How to install and tune oMLX on M5 Max 128 GB
Tested May 2026 recipe: oMLX 0.3.8 on Mac M5 Max with 128 GB, TurboQuant at 3.5-bit, Qwen 3.6 35B-A3B model stack, Claude Code wiring and real benchmarks.
Artificial Intelligence
Multi-agent systems: LangGraph vs CrewAI vs Autogen in 2026
Three frameworks, three mental models. When to use each and why — with a real orchestration case.
Artificial Intelligence
How to build a production-ready agent with the Anthropic SDK, step by step
This guide shows how to build a production-ready agent with the Anthropic SDK in Python: the tool-use loop with the Messages API, streaming with backpressure via a bounded queue, prompt caching with cache_control, your own MCP server registered with the Claude Agent SDK, OTel GenAI traces, and a non-root Docker container ready for production.
Artificial Intelligence
MCP (Model Context Protocol) in 2026: the complete guide for engineering teams
After eighteen months of multi-vendor adoption, MCP is the de facto standard for connecting models to tools. The complete guide: architecture, servers, policies, authentication, composition, and the antipatterns we’ve already seen in production.
Artificial Intelligence
LLM red teaming: a practical playbook
LLM red teaming has gone from an esoteric activity to a mandatory practice. With the OWASP Agentic Top 10 and the CSA Agentic AI Red Teaming Guide converging on shared vocabulary, this is the operational playbook any team deploying agents needs to have.
Artificial Intelligence
Production-grade agent evaluations: the framework that works
Después de año y medio llenando tableros con agentes en producción, la pregunta que separa equipos que envían fiable de los que van a ciegas sigue siendo la misma: ¿cómo mides que el agente está funcionando?
Architecture
Agent OS in production: real cases without the marketing
El concepto de Agent OS pasó del slide al despliegue en 2025. Seis meses en producción dejan patrones visibles: qué arquitecturas funcionan, dónde se rompe el modelo y qué aporta frente a correr agentes sobre pila existente.
Architecture
Enterprise GraphRAG: patterns after a year of adoption
A year after GraphRAG left the lab, one statistic holds: it works where corporate information has dense relational structure, fails where there are only loose documents. Patterns, ingestion costs, and architectural decisions that have survived a year of real deployment.
Artificial Intelligence
How to install a local MCP server for your editor
The Model Context Protocol has gone from proposal to de facto standard for connecting editors with external tools. This practical guide walks through standing up a local MCP server, wiring it into VS Code or your client of choice, and understanding exactly what you are exposing.
Artificial Intelligence
Enterprise agent governance: the controls that are no longer optional
After two years of pilots and a year of agents in production, governance has moved from an aspirational committee to an operational control. What audits ask for, what broke in 2025, and which guardrails absorb most incidents.
Artificial Intelligence
Lessons from agents in production in 2025: summary for 2026
Durante 2025 cientos de equipos pusieron agentes IA en producción real. A principios de 2026, con datos suficientes, emergen lecciones consistentes sobre qué falla, qué funciona, cuánto cuesta y qué tareas no encajan. Repaso ordenado para equipos que empiezan ahora.
Architecture
Consolidated MCP ecosystem: a quick map for 2026
Twenty months after the initial announcement, Model Context Protocol went from curiosity to de-facto standard among agent clients and servers. What is available, which servers are worth it, which problems remain open, and how it compares to earlier protocol maps.
Artificial Intelligence
Agents that drive the computer: patterns that work
Sixteen months after Anthropic first shipped computer use, with browser-use, OpenAI Operator and Gemini Computer Use all pushing in parallel, agents that drive the browser and desktop have moved from demo to real workflows. Time to review which patterns survive when you run them daily in production.
Artificial Intelligence
AI incident postmortems: what they have taught us
A selection of postmortems published between 2025 and 2026 by teams running AI systems in production reveals repeated patterns: guardrail failures, silent model drift, hidden vendor dependency, and a collection of near-misses worth distilling.
Artificial Intelligence
AI startup market correction in 2026
Tres años de valoraciones vertiginosas han empezado a corregirse sin estrépito pero con firmeza: rondas abajo, despidos selectivos y consolidación en torno a propuestas con ingresos reales. Una lectura ordenada de qué sobrevive, qué se quema y qué aprende el ecosistema.
Artificial Intelligence
Claude Haiku 4.5: lightweight power for massive agent fleets
Anthropic publicó Haiku 4.5 en octubre de 2025 y el modelo ha madurado rápido: rendimiento cercano a Sonnet 4 en tareas estructuradas a un tercio del coste, ventana amplia y latencia baja. Es la pieza que faltaba para desplegar agentes a escala sin quemar presupuesto.
Artificial Intelligence
Knowledge graph renaissance with LLMs
Knowledge graphs spent two decades waiting for their moment. With LLMs now bridging free text and formal ontology, and the GraphRAG pattern already mature, the technology is back in the spotlight. Time to look at why it finally fits and where it actually pays off.
Artificial Intelligence
UX for agents: first design consensus
After two years watching every product invent its own interface for talking to an agent, by January 2026 a stable design consensus is emerging about which patterns work, which do not, and what the average user already expects. Time to write down what has settled.
Artificial Intelligence
Sovereign AI in Europe: practical status
European sovereign AI discourse has spent three years fueling headlines, public investment, and interstate agreements. We are starting to see which part of the promise has real technical substance and what a technical team expecting alternatives outside the US ecosystem can actually count on.
Artificial Intelligence
LLM-generated documentation: when it helps and when it gets in the way
Large language models have spent two years promising effortless documentation for code, APIs and architecture. After watching dozens of projects try it, clear patterns emerge for where it works and where it just becomes more debt.
Artificial Intelligence
AI agent observability: what to instrument first
Agents that chain calls to models, tools and memory are hard to debug without instrumentation designed for them. After a long year running agents in production, I cover what to measure first, which standards are consolidating, and which costly mistakes are avoided by getting the traces right from the start.
Architecture
LLM caches: saving tokens without dropping quality
A caching proxy in front of a language model can cut the token bill significantly, but it introduces subtle risks if the design is not careful. Which cache types work in production, where the usual traps sit, and how to add them without degrading the experience.