Agent Design
Key Guides
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.
When to Build vs Buy Your Agent Orchestration Layer
A team picks an agent framework in January, ships a demo in February, and by July they're ripping it out to build something custom. The autonomous agent market will hit $8.5 billion this year.
Agent Tool-Use Patterns: How LLMs Actually Wield APIs
tags: guides, agent-design category: agent-design slug: agent-tool-use-patterns-guide meta_description: "A practical guide to how LLM agents select, call, and chain tools in production. Covers function calling patterns, failure modes, benchmarks, and the MCP standard." Every major model provider now supports function calling. OpenAI, Anthropic, Google, and a dozen
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.