Field notes on agentic AI
Practical, opinionated writing on building agents and RAG systems that hold up in production — the failure modes, the fixes, and the things the tutorials skip. Written by the AgentSwarms Authors.
7 Failure Modes That Kill Multi-Agent Systems
Most multi-agent systems don't fail loudly. They drift, loop, and quietly degrade. We walk the seven failure modes that kill swarms in production — hallucination snowballs, runaway loops, goal drift, silent quality decay — and the concrete fix for each, with broken swarms you can repair.
LangGraph vs CrewAI vs AutoGen: 2026 Benchmark
We ran the same researcher → writer → reviewer pipeline through LangGraph, CrewAI, and AutoGen and looked at the two numbers that matter: did it finish the task, and what did it cost? A builder's benchmark with an opinionated verdict and a decision flowchart — not another feature table.
Agentic RAG vs Traditional RAG: Key Differences
Vanilla RAG is a straight line: embed, retrieve, stuff, generate. Agentic RAG adds a brain that can route, grade its own retrieval, and self-correct. We compare the three architectures with working code, show when NOT to upgrade, and cover the RAG-poisoning attack that should keep you up at night.
The MCP Server You Actually Ship: 2026 Playbook
MCP solves the n×m integration mess that was strangling agent tooling. We cover what it actually is (and isn't), how the JSON-RPC handshake works, why it wraps but doesn't replace REST — and the security work that separates a demo MCP server from one you'd put in production, including the confused-deputy attack.
50 Agentic AI Interview Questions Asked in 2026
A tiered bank of the agentic AI interview questions actually being asked in 2026 — junior (ReAct, tool calling, RAG), mid (orchestration, MCP, evaluation), and senior/staff (observability for non-deterministic systems, injection defense, knowing when NOT to use agents). With the answers interviewers are listening for.
Keeping RAG Honest When Your Documents Change
RAG is only as fresh as its index. Why retrieval rots as docs change, how to detect drift with content hashing, and re-indexing strategies that scale.