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LLM & Generative AI · Artificial Intelligence
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Make Your Coding Agent Answers Easier to Scan with i-have-adhd
Table of Contents Introduction What Is the i-have-adhd Plugin? Success Conditions for Using the Plugin Setup How I Tested It Test Results Should You Install It? Run the Test Yourself References Related Tutorials Introduction Have you ever received an answ
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Quick Tips: Quack - From Separate DuckDB Files to One Shared Server CodeCut Newsletter
Plus scope agent memory with mem0
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Quick Tips: kotaemon - Build Private Document QA with Citations CodeCut Newsletter
Plus test HTTP code without live API calls
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Graphify - Query a Codebase as a Knowledge Graph
Grab your coffee. Here are this week's highlights. Today's Picks kotaemon - Build Private Document QA with Citations Problem ChatGPT's file upload is useful for quick questions, but it is not built for shared document workflows. Teams often need page-leve
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Stop Treating Your RAG Grounding Score as a Safety Net
Table of Contents Introduction Why this matters to you right now The hypothesis The setup The scoring mechanism The benchmark score Flip one negation Change one number What the results show What to change in your system Running the code yourself Key takea
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Quick Tips: Codon - Mix Compiled Speed with Python Libraries CodeCut Newsletter
Plus share agent memory across Claude and Codex
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Codon - Mix Compiled Speed with Python Libraries
Grab your coffee. Here are this week's highlights. Today's Picks Codon - Mix Compiled Speed with Python Libraries Problem Compiled languages can make Python workloads faster, but they often come with a tradeoff. You need to learn new syntax and give up ea
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Automate Model Tuning with an Agentic Training Loop
Table of Contents The Problem with Hand-Tuning a Model What We're Building Define the Evaluation Code Define the Editable Training Script Define the Agent Interface Define the Safety Checks Final Thoughts Related Tutorials The Problem with Hand-Tuning a M
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Before You Upgrade the Model, Try Thinking Mode
Table of Contents Introduction What Is Thinking Mode? Setup Multi-Step Problems: Where Thinking Helps Single-Step Problems: When Plain Mode Is Enough Final Thoughts Introduction When a local model gets a simple task wrong, the natural reaction is to reach
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llama.cpp - Run local LLMs on any hardware with one binary
Grab your coffee. Here are this week's highlights. Today's Picks Headroom - Cut agent tokens without touching your prompts Problem AI agents can waste tokens on context they do not fully need. Long logs, full files, API responses, and retrieved documents
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