Agent Design
How you actually build AI agents that work. Architectures, tool use, memory patterns, and the frameworks worth paying attention to.
Key Guides
Latest Signals
- Anthropic's 186-Deal Experiment Shows What the Agent Economy Actually Looks Like
- When NOT to Use an Agent: The Production Data That Should Change Your Default
- Why Multi-Agent Papers Don't Replicate in Production
- Multimodal Agents Score 40% Where Humans Score 72%
- 2026 Is the Year of the Agent. Here's What the Data Actually Says
From the team behind Swarm Signal
Track Your Finances While You Build AI
BoredTools makes the boring stuff easy — budget dashboards, freelance trackers, and business planners. Download free or grab the full collection.
Best AI Agent Monitoring and Observability Tools 2026
Your agent passed evals. Then it spent $400 in one afternoon on a retry loop. We tested 8 observability tools in production agent workflows during Q1 2026.
Your Multi-Agent System's Biggest Problem Is Its Org Chart
Static multi-agent topologies leave massive performance on the table. New research shows agents that rewire their own communication graphs outperform fixed architectures by double-digit margins.
Best AI Agent Frameworks 2026: Ranked by Production Readiness
There are now over 20 agent frameworks competing for your stack. Most won't survive the year. We ranked eight that actually matter in 2026, using one filter: can you ship this to production and sleep at night?
MCP vs A2A vs ACP: Which Agent Protocol Wins in 2026
MCP, A2A, and ACP compared on architecture, adoption, and real trade-offs. Covers the ACP-A2A merger and when to use each protocol.
LangGraph vs CrewAI vs OpenAI Agents SDK: Agent Framework Comparison 2026
LangGraph, CrewAI, and OpenAI Agents SDK compared on architecture, pricing, and production readiness. Includes honorable mentions and migration guidance.
Multi-Agent Orchestration: The Illusion of Cooperation
A new benchmark from Tsinghua and Microsoft tests 16 multi-agent frameworks on tasks requiring genuine coordination. The median system spends 74% of its inter-agent messages on redundant state synchronization, and adding a third agent makes most pipelines slower, not faster.
Your Agent's System Prompt Is Fighting Itself
A framework called Arbiter treats agent system prompts as auditable code. Applied to Claude Code, Codex CLI, and Gemini CLI, it found 152 interference patterns — including critical contradictions and a structural data loss bug — for a total cost of $0.27.
Agent Benchmarks Won't Sit Still
Static agent benchmarks assume frozen environments. ProEvolve evolved one environment into 200 with 3,000 task sandboxes. Every frontier model failed in structurally different ways when familiar tools disappeared.
Most AI Agents Don't Know When They're Wrong
A 4B parameter model just matched GPT-4o on tool-use tasks by learning to verify its own actions. The CoVe paper shows verification-first training beats the retry-and-pray approach plaguing production
From Clawdbot to OpenAI in 90 Days
OpenClaw hit 100,000 GitHub stars in 48 hours, survived three name changes, a supply chain attack, and three critical CVEs. Then its creator Peter Steinberger joined OpenAI.