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.
Field Guides and Frameworks
Implementation playbooks, operator patterns, and deployment methods.
Signals, Maps, and Watch Lists
Production-oriented analysis, benchmarks, and market/system intelligence.
External tools
Execution tooling is separate
Swarm Signal keeps the analysis layer. Use BoredTools for reusable production templates and trackers.
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.
Inference Optimization: From 10x Cost to 10x Speed
In late 2022, running a query against GPT-3-class performance cost roughly $20 per million tokens. By March 2026, multiple models exceed that same...
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....
Scaling Laws Explained for Practitioners: What Actually Matters in 2026
Scaling laws promised a simple deal: spend more compute, get better models. For three years, that deal held. Kaplan et al. drew the first power-law curves...
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 Practitioner's Decision Guide for 2026
Mixture of Experts models are cheaper per token. That's the headline every vendor leads with. But 'cheaper per token' and 'better for your workload' aren't the same thing.
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.