Dec 25, 2025 · 10 min read · How I identified a critical gap in one of Python's most popular LLM libraries and built two features to solve it. Introduction When I started exploring ways to contribute to open source, I wanted to find a project where I could make a real impact - ...
Join discussionDec 14, 2025 · 6 min read · You have probably encountered it already. A system that is brittle, poorly understood, and quietly dangerous. Then someone runs it through an AI assistant and suddenly there is a clean architecture diagram, a confident explanation, a tidy folder stru...
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Dec 14, 2025 · 4 min read · Why does ChatGPT sound confident even when it is wrong?More importantly, how do we fix that? In this blog, you will build your first Retrieval-Augmented Generation (RAG) system in Python, step by step, with real code and no machine learning backgroun...
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Dec 4, 2025 · 2 min read · También conocido como “Lavado de información en AI”, aka: “information laundering through AI”, Cómo una noticia falsa en un periódico acaba convertida en “verdad” por Grok, Claude y ChatGPT. Information laundering: cuando la IA convierte mierda en ...
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Dec 2, 2025 · 4 min read · We’ve all been there. Faced with a technical question, you turn to a Large Language Model (LLM) for a quick, authoritative-sounding answer. But what happens when that answer is not just slightly off, but confidently and completely wrong? As someone w...
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Nov 21, 2025 · 4 min read · How I Fought LLM Hallucinations in My RAG Chatbot When I built my RAG-based portfolio chatbot, I quickly discovered a harsh truth: giving an LLM access to a knowledge base doesn't automatically mean it'll stay truthful. It'll confidently invent detai...
Join discussionNov 20, 2025 · 4 min read · How I Fought LLM Hallucinations in My RAG Chatbot When I built my RAG-based portfolio chatbot, I quickly discovered a harsh truth: giving an LLM access to a knowledge base doesn't automatically mean it'll stay truthful. It'll confidently invent detai...
Join discussionOct 5, 2025 · 9 min read · How inference-time reasoning — Chain-of-Thought, ReAct, and Tree-of-Thoughts — is helping AI overcome its intuition and truly think. First thing First 🤔 Do LLMs Really Have “Intuition”? Strictly speaking — no, LLMs don’t have intuition or logic in t...
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Aug 22, 2025 · 6 min read · Common Failure Cases and Quick Mitigations Retrieval-Augmented Generation (RAG) has revolutionized how Large Language Models (LLMs) access and utilize external knowledge, enabling them to generate more accurate, relevant, and up-to-date responses. Ho...
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