Models & Frontiers
What the new models can actually do, how they were trained, and whether the benchmarks mean anything. Open source vs closed, and where the research is heading.
Guides and explainers
Detailed guides and practical technical analysis.
Latest analysis
Recent research, benchmark reviews and technical updates.
Practical tools
Templates for budgets and project planning
BoredTools offers practical spreadsheets for budgets, freelance work and small projects.
Browser-Use Agents After the Computer-Use Benchmarks
Browser-use agents look cleaner than desktop agents, but the benchmarks still hide drift, cost, auth, and recovery failure.
Models Training Models: The Promise and Peril of Synthetic Data
Microsoft's Phi-4 trained on more than 50% synthetic data and beat GPT-4o on graduate science benchmarks. The old rules about training data are changing fast.
Small Agent Models Need Tool Floors, Not Parameter Claims
Small language models are getting a serious agent story, but the useful question is no longer whether a 1B, 3B, or 8B model can sound capable. The useful...
Model Selection Guide: How to Pick the Right AI Model for Your Use Case
A March 2026 survey of the [Artificial Analysis leaderboard](https://artificialanalysis.ai/) counts 429 tracked models, over 200 of them open-weight....
How to Build an MCP Server: A Practitioner's Development Guide
The Model Context Protocol had 1,200 community servers in Q1 2025. By April 2026 that number hit 9,400. Ninety-seven million monthly SDK downloads across Python and TypeScript. First-class support in Claude, ChatGPT, Cursor, VS Code, and Microsoft Copilot. 78% of enterprise AI teams report at lea...
Best Open-Weight Models for Production AI Agents 2026
Your agent framework doesn't matter if the model underneath it can't call tools reliably. We tested and ranked eight open-weight models specifically for agent use cases: tool calling accuracy, multi-step reasoning, context retention, hosting economics, and licensing terms.
Open-Weight Model Tradeoffs: Llama, Qwen, and DeepSeek
Compare Llama 4, Qwen 3, and DeepSeek V4 open-weight models on benchmarks, context windows, licensing, and deployment.
Inference Optimization: A Practical Production Guide
Most inference costs hide in places engineers never check. This guide breaks down KV-cache management, speculative decoding, quantization trade-offs, and the batching strategies that cut serving costs in half.
MoE vs Dense Models: A Practical Deployment Guide
Compare model quality, resident memory, context length and concurrency before choosing a deployment.
Llama 4 vs Qwen 3 vs DeepSeek V3 vs Mistral Large: Open-Weight Models 2026
Llama 4, Qwen 3, DeepSeek V4, and Mistral Large compared. Benchmarks, pricing, licensing, and which open-weight model to pick for production agents in 2026.