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Carlos Gutierrez

CodeTyper CLI: Building an AI Coding Agent That Actually Learns From Your Feedback

CodeTyper CLI: Building an AI Coding Agent That Actually Learns From Your Feedback

I've been obsessed with a simple question for months: What if your AI coding assistant could actually get smarter the more you use it? Not in a vague "machine learning" way, but in a practical sense—learning which AI provider handles your refactoring tasks better, which

Vibe Coding Is Addictive, and It’s Quietly Destroying Software Quality

Vibe Coding Is Addictive, and It’s Quietly Destroying Software Quality

Recently I have been use the claude code cli to create some internal projects to myself, to get into Vibe Coding area, it is an incredible app I may say, probably I will continue use it more and more, but I still have complains and of course I have a

Human Code vs AI code

Human Code vs AI code

Recently, I read the paper Human-Written vs. AI-Generated Code: A Large-Scale Study of Defects, Vulnerabilities, and Complexity by LLMs and Humans. Perhaps the LLMs are incredibly fast, allowing you to obtain the code in minutes and develop a small application in minutes. The human code and the necessity of generating

The AI Bubble: Why I’m Getting Out Before 2026

The AI Bubble: Why I’m Getting Out Before 2026

The AI is here, and by passing the 2025 I faced, everyone is realizing that the AI is good at completing tasks such as reading emails, organizing them, writing letters, and generating images. I have created the pictures for my blog using AI, and they are impressive. If I think

How a Performance Study Changed the Way I Think About Optimization

How a Performance Study Changed the Way I Think About Optimization

I recently read a paper on high-performance computing (HPC), which reshaped my understanding of performance work. I used to think HPC was mostly about having the “fastest algorithm.” Perhaps, the more I delved into the research and my own experiments, the more I realized that HPC is fundamentally about how

Engineering Lessons From Building an LLM PoC: What I Learned Building SheepOp

Engineering Lessons From Building an LLM PoC: What I Learned Building SheepOp

Creating a full transformer implementation and RAG optimizer from scratch provides insights that typical high-level frameworks obscure. Over the past days, I've built two open-source projects—SheepOp, a transformer implementation from scratch, and the LLM RAG Data Structures Optimizer, a production-grade optimization library. The experience revealed several lessons

Retrieval Optimization for RAG: Data Structures That Make Search Fast and Reliable

Retrieval Optimization for RAG: Data Structures That Make Search Fast and Reliable

In Retrieval-Augmented Generation (RAG) systems, inference efficiency only solves half of the problem. The other half lies in retrieval. Dense retrieval models, vector search indexes, and hybrid scoring mechanisms all rely on data structures whose design significantly impacts performance. While many developers focus on model architecture and fine-tuning, the retrieval