External tools
Execution tooling is separate
Swarm Signal keeps the analysis layer. Use BoredTools for reusable templates and trackers.
Red Teams Found Agents Leak More Than Models
Red teams found agents are far more vulnerable than standalone models. Mixed attack strategies hit 84.3% success rates. Memory poisoning persists across sessions. Every tool is a potential exfiltration path.
Red Teaming AI Agents: A Practitioner's Guide
Red teaming AI agents is fundamentally different from red teaming standalone models. Agents have tools, memory, and credentials — each a new attack surface. This guide covers the OWASP agentic framework and a structured testing methodology.
MCP Server Architecture in Practice: Tools, Resources, Prompts, and Safe Invocation
Implement MCP servers with robust tool/resource contracts, safe invocation flows, and versioning strategies for production agent systems.
AI Agents in Insurance: Claims, Underwriting, and Fraud Detection
Allianz's seven-agent system cut claim processing time by 80%. Lemonade automates 55% of claims. Meanwhile, 23 states enforce AI governance rules. Where AI agents are working in insurance, and where they're not.
Agent Reliability Scores Are Getting Worse, Not Better
SWE-Bench scores tick up every quarter, but production failure rates aren't dropping. A METR study found half of test-passing PRs wouldn't be merged. The more capable we make agents, the less reliably they behave.
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.
When AI Agent Swarms Actually Help
Compare single-agent and multi-agent architectures on complexity, cost, debugging, and when orchestration helps.
EU AI Act vs US vs UK: Global AI Regulation Compared
Compare EU AI Act, US, and UK AI regulation on compliance, penalties, timelines, and impact on developers.
Choosing Between RAG, Long Context, and Fine-Tuning
Compare RAG, long-context windows, and fine-tuning on accuracy, cost, latency, and production readiness.
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.