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Fenseg Web Desarrollo Web

05/11/2026

Tailwind CSS Grid Classes guide 🔥

12/10/2026

Java vs JavaScript 🔥

05/10/2026

Client vs Server 🔥

01/10/2026

Rest API 🔥

27/08/2026

Every RAG stack I audit has a vector database in it. Maybe a third of them need one.

That's not a knock on RAG. It's an observation about how the conversation got shaped.

Retrieval had an ecosystem behind it: vector databases, embedding providers, reranker models, chunking libraries, evaluation tooling. All of it fundable, all of it demoable, all of it conference friendly. Cache Augmented Generation had none of that, because there's nothing to sell. You load the knowledge into context, you cache it, you're done.

So the default became "add a retrieval layer," and a lot of teams built one for a corpus that would have fit in the window with room to spare.

𝗪𝗵𝗮𝘁 𝗖𝗔𝗚 𝗾𝘂𝗶𝗲𝘁𝗹𝘆 𝗲𝗹𝗶𝗺𝗶𝗻𝗮𝘁𝗲𝘀

No chunking strategy, which means no clause getting split across a boundary and half of it never surfacing.

No embedding drift, which means no silent recall degradation six months after launch when nobody is watching retrieval metrics anymore.

No top k tuning, no reranker to maintain, no retrieval latency in the critical path.

The model sees the full document, in order, with structure intact. For a policy manual or a coding standard, that ordering carries meaning that chunking destroys.

𝗧𝗵𝗲 𝗮𝗰𝗰𝘂𝗿𝗮𝗰𝘆 𝗮𝗿𝗴𝘂𝗺𝗲𝗻𝘁 𝗽𝗲𝗼𝗽𝗹𝗲 𝘀𝗸𝗶𝗽

RAG has a ceiling that generation quality can't lift: if retrieval misses the passage, the answer is wrong no matter how good the model is. Recall becomes your real accuracy number, and most teams measure it once during evaluation and never again.

CAG has no retrieval step, so it has no retrieval miss. On a bounded corpus, that's not a minor convenience. That's a whole class of production failure that simply doesn't exist.

𝗪𝗵𝘆 𝗶𝘁 𝘀𝘁𝗮𝘆𝗲𝗱 𝘂𝗻𝗱𝗲𝗿𝗿𝗮𝘁𝗲𝗱

Context windows were small when the RAG playbook got written. Retrieval wasn't a design choice back then, it was the only option, and the reasoning behind it hardened into architecture diagrams that outlived the constraint.

Windows are an order of magnitude larger now and prompt caching made repeated context economically boring. The constraint moved. The default didn't.

𝗪𝗵𝗲𝗿𝗲 𝗜'𝗱 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝘂𝘀𝗲 𝗶𝘁

Bounded corpus, slow moving content, high accuracy requirement. Benefits handbooks. Product documentation. Regulatory guidance. Internal engineering standards. Content that changes quarterly and where missing a clause is expensive.

RAG still owns everything that's large, volatile, or per user. That doesn't change. The point is that the two should be a per source decision, and right now one side gets evaluated seriously and the other doesn't get evaluated at all.

Curious where people land on this: has cheap prompt caching and a million token window changed your default architecture, or is retrieval still the right first move regardless of corpus size?

26/05/2026

¿Qué es Virtual DOM?

El Virtual DOM es una representación virtual del DOM real que React utiliza para optimizar las actualizaciones de la interfaz de usuario.

¿Para qué sirve?

- Mejorar el rendimiento de la aplicación
- Reducir manipulaciones directas del DOM real
- Hacer renderizados más eficientes
- Actualizar únicamente los elementos necesarios

¿Cómo funciona?

1. React crea una copia virtual del DOM
Genera una representación ligera en memoria.

2. Detecta cambios
Compara el estado anterior con el nuevo.

3. Aplica un proceso de comparación (Diffing)
Identifica exactamente qué elementos cambiaron.

4. Actualiza solo lo necesario
Modifica únicamente las partes afectadas del DOM real.

Características principales

1. Actualizaciones eficientes
Reduce cambios innecesarios en la interfaz.

2. Mejor rendimiento
Optimiza la velocidad de renderizado.

3. Diffing Algorithm
Sistema inteligente para detectar diferencias.

4. Re-render optimizado
Actualiza componentes específicos y no toda la página.

¿Dónde se utiliza?

- React
- React Native
- Librerías modernas basadas en componentes

Buenas prácticas

- Utilizar correctamente las "keys" en listas
- Evitar renders innecesarios
- Memorizar componentes costosos cuando sea necesario
- Mantener componentes pequeños y reutilizables

Ventajas

- Interfaces más rápidas
- Mejor experiencia de usuario
- Aplicaciones más escalables
- Menor carga sobre el navegador

Resumen

Virtual DOM = renderizado optimizado + mejor rendimiento

Conclusión

El Virtual DOM es una de las tecnologías clave detrás del rendimiento de React, permitiendo crear interfaces modernas, rápidas y eficientes mediante actualizaciones inteligentes del DOM real.

14/05/2026

Building an AI app in 2026 isn't just about choosing an LLM.

It's about orchestrating an entire stack, from the user's first click to the model's final response.

Most people see ChatGPT and think "AI." But behind every modern AI product, there are 9 layers working together.

Here's the complete tech stack powering modern AI apps:

𝗙𝗿𝗼𝗻𝘁𝗲𝗻𝗱 (𝗨𝘀𝗲𝗿 𝗜𝗻𝘁𝗲𝗿𝗮𝗰𝘁𝗶𝗼𝗻)
React, Next.js, Angular, Swift, Kotlin, Flutter, Tailwind

𝗕𝗮𝗰𝗸𝗲𝗻𝗱 (𝗔𝗣𝗜𝘀 & 𝗦𝗲𝗿𝘃𝗶𝗰𝗲𝘀)
Node.js, Django, FastAPI, Express, Spring Boot, GraphQL, REST APIs

𝗗𝗮𝘁𝗮𝗯𝗮𝘀𝗲𝘀 (𝗦𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝗱 & 𝗨𝗻𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝗱)
PostgreSQL, MySQL, MongoDB, Firebase, DynamoDB, Redis

𝗩𝗲𝗰𝘁𝗼𝗿 𝗗𝗮𝘁𝗮𝗯𝗮𝘀𝗲𝘀 (𝗔𝗜 𝗠𝗲𝗺𝗼𝗿𝘆 𝗟𝗮𝘆𝗲𝗿)
Pinecone, Milvus, Weaviate, FAISS, ChromaDB

𝗠𝗼𝗱𝗲𝗹 𝗟𝗮𝘆𝗲𝗿 (𝗟𝗟𝗠𝘀 & 𝗚𝗲𝗻𝗔𝗜)
OpenAI GPT, Claude, Mistral, Hugging Face, LLaMA, GPT-NeoX

𝗢𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻 & 𝗔𝗴𝗲𝗻𝘁𝘀
LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel

𝗖𝗹𝗼𝘂𝗱 & 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁
AWS Bedrock, Azure AI, GCP Vertex AI, Kubernetes, Docker

𝗠𝗼𝗻𝗶𝘁𝗼𝗿𝗶𝗻𝗴 & 𝗚𝘂𝗮𝗿𝗱𝗿𝗮𝗶𝗹𝘀
Trulens, Guardrails AI, LlamaGuard, Human-in-the-Loop feedback

𝗖𝗜/𝗖𝗗 & 𝗗𝗮𝘁𝗮 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲
GitHub Actions, Jenkins, Terraform, Airflow, Spark, Snowflake, Databricks

The takeaway?

Great AI products aren't built on hype. They're built on architecture.

If you're a founder, engineer, or PM building in AI, master the layers, not just the buzzwords.

Save this for your next AI project.

13/02/2026

Architecture of Netflix 👇🏻

28/01/2026

URL vs URI vs URN Explained 🔥 3D Visual Guide for Beginners

23/12/2025

Web Development Made Simple — A Clear Roadmap 🧠💻

Web development looks complex from the outside, but the fundamentals are surprisingly structured.

Front-end builds what users see and feel.
Back-end powers logic, data, and scale.
APIs connect everything into one system.

You don’t need to learn everything at once.
You need the right order, right clarity, and consistent ex*****on.

Master the basics.
Respect the fundamentals.
Frameworks change, concepts don’t.

Save this if you’re starting your web dev journey — or revisiting the foundations.

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