Cofundador de ClickBalance y PacoElChato, me gusta la tecnología sin olvidar la naturaleza, el regalo de la vida, la belleza, la música y la esencia del amor.
AI engineering is no longer just about knowing how to use an LLM.
The model is only one piece of the system.
Once you start building AI applications that actually need to work in production, the stack gets much bigger:
→ LLMs for reasoning and generation
→ RAG for grounding responses in your data
→ Embeddings + Vector DBs for semantic search
→ Agent frameworks for tool use and orchestration
→ MCP for connecting agents with external systems
→ Memory for maintaining context across interactions
→ Observability for understanding what went wrong
→ Security for protecting models, data and tools
→ Automation for turning workflows into actual actions
And then there are dozens of tools competing within each layer.
That's probably the most confusing part of learning AI engineering today.
You don't need to learn every tool in this ecosystem.
You need to understand what problem each layer solves - and then go deep on the tools that fit the systems you're building.
The shift from experimenting with an AI model to building a production-ready AI system is much bigger than most tutorials make it look.
This ecosystem map is a pretty useful reference for understanding what's happening beyond the LLM itself.
📌 Save this if you're exploring AI Engineering.
Today we're launching Gemini 3.7 Flash - our latest workhorse model for coding and agentic workflows, with an introductory price at half the original cost of 3.6 Flash. ⚡️
We have been iterating rapidly with the Flash series, going from 3.5 to 3.7 in just 3 months, making it more helpful across a wide range of tasks:
• Software Engineering (DeepSWE v1.1): 37.0% ➔ 65.3%
• Web Development (Code Arena Elo): 1506 ➔ 1588
• Enterprise Automation (AutomationBench): 13.4% ➔ 30.4%
En este año 2026 que es de 1 de inicios
Hay que saber resolver lo mejor para nostros en esta nueva era.
¿Y tú ya lo hiciste?...
Te leo en comentarios👇👇✨️
Delete negative people.
Forget the past.👇
Accept your mistakes.💪
Learn your lessons.✌️
Focus on your future.🫶🏻
Work hard in silence, and let your success tell the story.😇🔥
#Dailymotivationtofuelyourmind.
We’ve designed and built our first AI chip: Jalapeño.
Designed from the ground up by OpenAI and brought to production with @Broadcom, Jalapeño is purpose-built for the LLM workloads powering ChatGPT, Codex, the API, and future agentic products.
Chips are foundational to the AI economy. Building our own expands our full-stack platform from products to models to infrastructure, and will help us scale intelligence, serve more people, and expand access to AI.
Unreal Engine 5.8 has AI integration with Claude and Codex.
Runs in terminal beside the engine, connected via MCP to fully control the Editor.
Place props, generate cities procedurally, and even art direct the lighting.
Unreal Engine 5.8 available today.
Pretty much any Unreal game from now on is gonna need an AI label.