Artificial Intelligence on Antonio Cortés (DrZippie)

Auto Memory and Auto Dream: how Claude Code learns and consolidates its memory

Mon, 30 Mar 2026 00:00:00 +0000

If you’ve been using Claude Code with Auto Memory enabled for a while, you’ve probably noticed that after several sessions, Claude’s notes about your project start accumulating contradictions. Entries saying “yesterday we decided to use Redis” without specifying which day “yesterday” was. Debugging notes referencing files that no longer exist. Three different entries about the same build quirk. What started as a useful notebook becomes noise.

Anthropic has just released Auto Dream, a feature that does exactly what its name suggests: it consolidates Claude Code’s memory the way the human brain consolidates memories during REM sleep.

Claude Code with LSP: from searching text to understanding code

Tue, 10 Mar 2026 00:00:00 +0000

I have been using Claude Code daily for months, and there is one configuration that has completely changed how it works with my code. It is not a new plugin, a more powerful model, or a magic prompt. It is something that has existed since 2016 and that most developers use without knowing it every time they open VS Code: the Language Server Protocol (LSP).

Karan Bansal published an excellent article explaining in detail how to enable LSP in Claude Code and why it matters. After trying it, I can confirm the difference is real and significant.

The Software Development Renaissance with AI Agents

Fri, 06 Feb 2026 00:00:00 +0000

Greg Brockman, President and Co-Founder of OpenAI, recently published a thread that perfectly describes the moment we’re living in software development. According to him, we’re witnessing a genuine renaissance in software development, driven by AI tools that have improved exponentially since December.

The qualitative leap

The most striking part of Brockman’s thread is how they describe the internal change at OpenAI: engineers who previously used Codex for unit tests now see the tool writing practically all code and handling a large portion of operations and debugging. This isn’t an incremental improvement, it’s a paradigm shift.

Agent Lightning: Microsoft and the Future of AI Agent Orchestration

Mon, 02 Feb 2026 00:00:00 +0000

A few days ago I discovered Agent Lightning, a Microsoft project that I believe marks a before and after in how we think about AI agent orchestration. It’s not just another library; it’s a serious attempt to standardize how we build multi-agent systems.

What is Agent Lightning?

Agent Lightning is a Microsoft framework for orchestrating AI agents. It enables composition, integration, and deployment of multi-agent systems in a modular and scalable way. The premise is simple but powerful: agents should be components that can be combined, connected, and reused.

AI Coding Agents: Rules, Commands, Skills, MCP and Hooks Explained

Sun, 01 Feb 2026 00:00:00 +0000

If you’re using tools like Claude Code, GitHub Copilot Workspace, or similar, you’ve probably noticed there’s technical jargon that goes beyond simply “chatting with AI”. I’m talking about terms like rules, commands, skills, MCP, and hooks.

These concepts are the architecture that makes AI agents truly useful for software development. They’re not just fancy marketing words — each one serves a specific function in how the agent works.

Let’s break them down one by one in a clear way.

European Open Source AI Index: Measuring True AI Openness

Sun, 01 Feb 2026 00:00:00 +0000

Lately I’m seeing more and more AI models calling themselves “open source”. Llama, Mistral, Falcon… they all claim to be “open”. But are they really? How open are they actually?

I recently discovered the European Open Source AI Index (OSAI), a European initiative doing excellent work systematically evaluating how open generative AI models really are.

Self-Improving Agents: When AI Starts Improving Itself

Sun, 01 Feb 2026 00:00:00 +0000

Recently, Addy Osmani published an article that gave me much to think about: “Self-Improving Coding Agents”. The idea is simple but powerful: agents that not only execute tasks, but improve their own performance over time.

This isn’t science fiction. It’s happening now, in 2026. And it has profound implications for the future of software development and, by extension, for all professions.

What is a Self-Improving Agent?

A self-improving agent is an AI system with the capacity to:

When Claude Plans Your Route on Mars: NASA Uses AI for Perseverance

Sat, 31 Jan 2026 00:00:00 +0000

A few days ago I read news that left me thinking for a while. It’s not the first time I’ve heard about AI in space, but it is the first time I’ve read about Claude planning routes on Mars. And the best part: it worked.

NASA has been using Anthropic’s Claude to plan the Perseverance rover’s routes on Mars. Yes, you read that right: a generative language model generating navigation routes for a rover that’s 225 million kilometers away.

When Curiosity Meets Go: TinyEMU-Go and the Art of Porting an Emulator with AI

Sat, 31 Jan 2026 00:00:00 +0000

A few days ago I came across an article that literally left me with my mouth open. It’s about TinyEMU-Go: a RISC-V emulator written entirely in Go, ported from C using Claude. And the best part: you can run a complete Linux with a single command.

The Command Line That Gave Me Envy

go run github.com/jtolio/tinyemu-go/temubox/example@2c8151233c2d

And boom, you have a complete Linux running. No special permissions, no containers, no weird dependencies. A pure static Go binary.

MCPHero: The Bridge Between MCP and Traditional AI Libraries

Fri, 30 Jan 2026 00:00:00 +0000

Lately I’ve been closely following everything around the MCP protocol (Model Context Protocol), and recently I found a project that makes a lot of sense: MCPHero.

The reality is that although MCP is taking off, many “traditional” AI libraries like openai or google-genai still don’t have native MCP support. They only support tool/function calls. MCPHero comes to solve exactly this: make a bridge between MCP servers and these libraries.

What is MCPHero?

MCPHero is a Python library that lets you use MCP servers as tools/functions in native AI libraries. Basically, it lets you connect to any MCP server and use its tools as if they were native OpenAI or Google Gemini tools.

When AI Disempowers Us: Worrying Patterns in Real Claude Usage

Fri, 30 Jan 2026 00:00:00 +0000

A few days ago Anthropic published a paper that gave me much to think about. It’s titled “Disempowerment patterns in real-world AI usage” and analyzes, for the first time at scale, how AI interactions may be diminishing our capacity for autonomous judgment.

And no, we’re not talking about science fiction scenarios like “Skynet taking control.” We’re talking about something much more subtle and, perhaps for that reason, more dangerous: the voluntary cession of our critical judgment to an AI system.

Advanced Claude Code: Tips, tricks, and custom commands to maximize your productivity

Sun, 13 Jul 2025 00:00:00 +0000

After my previous article about agent-centric programming, I’ve been researching more advanced techniques for using Claude Code really productively. As a programmer with 30 years of experience, I’ve seen many promising tools that ultimately didn’t deliver on their promises. But Claude Code, when used correctly, is becoming a real game-changer.

Beyond the basics: The difference between playing and working seriously

One thing is using Claude Code for experiments or personal projects, and another very different thing is integrating it into a professional workflow. For serious projects, you need a different approach:

Agentic Programming with Claude: My Practical Experience Developing with AI

Sun, 13 Jul 2025 00:00:00 +0000

A few days ago I came across a very interesting stream where someone showed their setup for agentic programming using Claude Code. After years developing “the old-fashioned way,” I have to admit that I’ve found this revealing.

What is Agentic Programming?

For those not familiar with the term, agentic programming is basically letting an AI agent (in this case Claude) write code for you. But I’m not talking about asking it to generate a snippet, but giving it full access to your system so it can read, write, execute, and debug code autonomously.

How to build an agent: from idea to reality

Thu, 10 Jul 2025 00:00:00 +0000

Lately, there’s been talk of AI agents everywhere. Every company has their roadmap full of “agents that will revolutionize this and that,” but when you scratch a little, you realize few have actually managed to build something useful that works in production.

Recently I read a very interesting article by LangChain about how to build agents in a practical way, and it seems to me a very sensible approach I wanted to share with you. I’ve adapted it with my own reflections after having banged my head more than once trying to implement “intelligent” systems that weren’t really that intelligent.

A2A vs MCP: Tools or Agents? The difference that will change how we build AI systems

Wed, 09 Jul 2025 00:00:00 +0000

Two protocols, two philosophies

In recent months, two protocols have emerged that will change how we build AI systems: Agent2Agent Protocol (A2A) from Google and Model Context Protocol (MCP) from Anthropic. But here’s the thing: they don’t compete with each other.

In fact, after analyzing both for weeks, I’ve realized that understanding the difference between A2A and MCP is crucial for anyone building AI systems beyond simple chatbots.

The key lies in one question: Are you connecting an AI with tools, or are you coordinating multiple intelligences?

LM Studio Removes Barriers: Now Free for Work Too

Wed, 09 Jul 2025 00:00:00 +0000

In my years developing software, I’ve learned that the best tools are those that eliminate unnecessary friction. And LM Studio has just taken a huge step in that direction: it’s now completely free for enterprise use.

This may sound like “just another AI news item,” but for those of us who have been experimenting with local models for a while, this is an important paradigm shift.

The problem that existed before

Since its launch in May 2023, LM Studio was always free for personal use. But if you wanted to use it in your company, you had to contact them to obtain a commercial license. This created exactly the type of friction that kills team experimentation.

Context Engineering: Prompt Engineering Has Grown Up

Sat, 05 Jul 2025 00:00:00 +0000

A few years ago, many AI researchers (even the most reputable) predicted that prompt engineering would be a temporary skill that would quickly disappear. They were completely wrong. Not only has it not disappeared, but it has evolved into something much more sophisticated: Context Engineering.

And no, it’s not just another buzzword. It’s a natural evolution that reflects the real complexity of working with LLMs in production applications.

From prompt engineering to context engineering

The problem with the term “prompt engineering” is that many people confuse it with blind prompting - simply writing a question in ChatGPT and expecting a result. That’s not engineering, that’s using a tool.

Agent Communication Protocol (ACP): The HTTP of AI Agents

Wed, 02 Jul 2025 00:00:00 +0000

Yet another protocol promising to change everything

When IBM Research announced the Agent Communication Protocol (ACP) as part of the BeeAI project, my first reaction was the usual one: “Oh, just another universal protocol”. With nearly 30 years in this field, I’ve seen too many “definitive standards” that ended up forgotten.

But there’s something different about ACP that made me pay attention: it doesn’t promise to solve all the world’s problems. It simply focuses on one very specific thing: making AI agents from different frameworks talk to each other. And it does it in a way that really makes sense.

MCP for Skeptics: Why the Model Context Protocol is Worth It (even if it doesn't seem like it)

Wed, 02 Jul 2025 00:00:00 +0000

Confession of a converted skeptic

When Anthropic announced the Model Context Protocol (MCP) in November 2024, my first reaction was: “Ah, another protocol promising to solve all integration problems”. As a DevOps Manager who has seen dozens of “universal standards” born and die, I have reasons to be skeptical.

But after several months watching MCP be massively adopted - OpenAI integrated it in March 2025, Google DeepMind in April - I decided to investigate beyond the hype. And I have to admit something: I was wrong.

Walmart and the Agentic Future: How the Retail Giant is Revolutionizing Shopping with Autonomous AI Agents

Tue, 01 Jul 2025 00:00:00 +0000

The future of shopping is here, and Walmart is leading a quiet revolution that will forever change how we interact with retail. While many companies are still experimenting with ChatGPT and basic generative AI tools, the Arkansas giant has taken a quantum leap toward Agentic AI, developing autonomous systems that not only recommend products but act, decide, and execute complete tasks on their own.

In this deep analysis, we’ll explore how Walmart is building a future where AI agents don’t just assist humans but operate as true autonomous collaborators, transforming from the shopping experience to the most complex internal operations.

STORM: The AI System Revolutionizing Long-Form Article Writing by Simulating Human Research Process

Sun, 18 May 2025 00:00:00 +0000

Creating long, well-founded articles has traditionally been a complex task requiring advanced research and writing skills. Recently, researchers from Stanford presented STORM (Synthesis of Topic Outlines through Retrieval and Multi-perspective Question Asking), a revolutionary system that automates the Wikipedia-style article writing process from scratch, and the results are truly impressive.

In this detailed analysis, we’ll explore how STORM is transforming the way we think about AI-assisted writing and why this approach could forever change the way we create informative content.