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Honest software development: code that lasts and stays with you.
Kubernetes 1.35 GA consolidates three releases of work: native sidecars with full lifecycle management, generalised DRA for FPGAs and NPUs, and a scheduler that cuts resource waste by 15-25% in heterogeneous clusters. An operations-side balance sheet: what to enable now, what to watch before migrating, and what path to follow from 1.30.
Skills package reusable capabilities; subagents isolate bounded-task execution. Together they form the most effective pattern for composing complex agents in 2026.
The Model Context Protocol, proposed by Anthropic in late 2024 and adopted through 2025-2026 by Anthropic, OpenAI, Google, and the open-source community, already has proven operational patterns: separating generic servers from custom ones, explicit per-tool policies, credentials kept outside the model, prefixed composition, and contract tests. This is the state of the art in 2026.
Hybrid RAG in 2026 combines dense and lexical search fused with RRF, cross-encoder reranking over the top-50 candidates, structure-aware chunking, and continuous evaluation with Ragas or TruLens. It is the pattern that survives in serious production systems three years after the initial embeddings boom.
The idea of UI generated on the fly instead of pre-built reached production in 2025. After a year of real-world use, the balance is more nuanced than the initial enthusiasm suggested.
Claude Code leads long-horizon agentic work, Cursor wins for fast daily interactive editing, Aider dominates CI-pipeline automation, and GitHub Copilot fits teams built around GitHub PRs; Windsurf competes with fresh traction. After a year using all five hard, the most productive combination for most people is still Claude Code plus Cursor.
Kubernetes won the orchestration battle, but Docker Swarm stays maintained inside Docker Engine and makes real sense for small teams without dedicated SRE, self-hosted stacks on 1-5 VPS, and edge mini-clusters. In those contexts, Swarm's minimal learning curve and low operational cost outweigh Kubernetes's advanced features.
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.
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.
The AI tool stack a developer uses in 2026 looks nothing like it did eighteen months ago. Agentic editors, review tools, terminal agents, and test assistants have settled into recognizable roles. A practical guide by category.
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.
Tres años después de que platform engineering se convirtiera en palabra de moda, el polvo ha caído. Unas pocas empresas tienen plataformas internas que de verdad aceleran al desarrollo, muchas montaron un portal Backstage vacío y algunas volvieron a DevOps clásico. Análisis de qué distingue a las que ganaron.
Four and a half years after Rust officially entered Linux 6.1, with real Apple GPU and NVMe drivers in production and several public conflicts between maintainers, it is time for a sober technical balance. What works, what still costs, and where the next phase is heading.
After the 2023-2024 hype cycle led by Apple Vision Pro, the 2025 valley of disillusionment, and the quiet but real consolidation of Meta Quest 3S and the WebXR stack, it is time to assess honestly where extended reality stands. What works, what has died, what is still alive.
WASI preview 3 llegó como estándar estable a finales de 2025 y ha tenido unos meses para demostrar si realmente desbloquea los casos que preview 2 se quedaba cortos. Recorrido honesto por adopciones reales, bibliotecas maduras y patrones que empiezan a funcionar en producción.
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.
Six months after A2A landed at the Linux Foundation, and after several implementation cycles from Google, Microsoft, and open projects, what version 1 of the protocol means and whether it is safe to build on yet.
Con 1.34 liberado en agosto de 2025 y el ciclo de 1.35 en su última fase de congelación de funciones, qué llegará estable, qué quedará en beta, qué nos interesa a quienes mantenemos clústeres pequeños o medianos y qué podemos ignorar sin culpa hasta el siguiente ciclo.
La integración de WebAssembly dentro de containerd como tiempo de ejecución alternativo ha madurado. Ya es posible desplegar cargas mixtas Linux y Wasm en el mismo clúster de Kubernetes con argumentos operativos sólidos. Cuándo compensa y cuándo no.
La obligación del EAA entró en vigor el 28 de junio de 2025. Seis meses después tenemos ya primeros expedientes sancionadores, criterios de enforcement y lecciones operativas para equipos que aún corren detrás del calendario. Lo que sí se audita y lo que todavía no.
With MCP solving the agent-to-tool layer, a parallel problem surfaces: how do two agents from different vendors communicate with each other. Google's Agent2Agent protocol, donated to the Linux Foundation in June 2025, tries to fill that gap with an open standard.
Neural processing units have stopped being a marketing label on Snapdragon, Apple Silicon and AMD Ryzen AI laptops. Here is what you can actually do from code today, which tools are mature, and when it pays off to target the NPU instead of the CPU or GPU.
gVisor interpone un kernel en espacio de usuario entre el contenedor y el anfitrión. Después de años en producción en Google y adopción creciente en plataformas serverless, merece una lectura honesta sobre cuándo compensa frente a microVMs y runtimes clásicos.
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.
