Articles
In-depth research, comprehensive guides, and long-form thoughts on modern technology.
Using Local Coding Agents
A guide to setting up local coding agents with open weight models, offering a private, free alternative to cloud services like Claude Code and OpenAI's Codex.
Controlling Reasoning Effort in LLMs
How modern AI models manage reasoning tasks. We explore how systems like GPT-5.6 and DeepSeek V4 toggle between low, medium, and high effort compute modes.
Proposed Framework Sets Red Lines for AI in Government Contracts
A proposed governance framework sets red lines against autonomous weapons and untargeted AI surveillance in government contracts, backed by an oversight body.
Researchers Find 'Meta-Tokens' That Reveal a Model's Hidden Algorithms
A new interpretability technique called J-lens finds tokens in a model's internal activations that hint at the actual algorithm it's using to reason.
Building a Tool-Using AI Agent in Python with LangGraph
A hands-on LangGraph tutorial covers state, nodes, edges, tool calling, and persistent memory for building a conversational AI agent in Python.
How Agentic AI Architecture Has Changed by Mid-2026
By mid-2026, agentic AI has shifted from monolithic orchestration loops to specialized multi-agent swarms connected through standardized tool protocols.
Inkling: Thinking Machines Lab's First Open-Weight AI Model Explained
Thinking Machines Lab's first model, Inkling, is a 975-billion-parameter open-weight multimodal system built for customization rather than benchmark supremacy.
Agentic AI vs AI Automation: What Actually Separates Them
Agentic AI and automation solve different problems: automation follows fixed rules, while agentic AI plans, decides, and adapts toward a goal.
How to Run the Mythos-Enhanced Qwythos Coding Model Locally
A step-by-step guide shows how to run the Mythos-enhanced Qwythos-9B model locally with llama.cpp and connect it to the Pi coding agent.
Why Most RAG Hallucinations Start Upstream of the Prompt
A four-part breakdown shows RAG systems hallucinate not from bad prompts but from broken parsing, vocabulary mismatches, and weak retrieval upstream.
ByteDance's Astra Splits Robot Navigation Into Two Specialized Models
ByteDance's Astra uses a dual-model architecture to give mobile robots reliable self-localization, target finding, and real-time path planning indoors.
New Benchmark Tackles Debugging Failures in LLM Multi-Agent Systems
Researchers from Penn State, Duke, and partner labs built the first benchmark for automatically pinpointing which AI agent caused a multi-agent task failure.