AI Agents

Multi-Agent Systems Without the Hype 2026

Многоагентная система как распределённый workflow: контракты, бюджеты, независимая проверка

When several agents actually pay off and when they just burn budget. Router, supervisor, agents-as-tools, and handoff; context and write isolation, limits, failure resilience, trust boundaries, and proving usefulness on your own tasks - across the OpenAI Agents SDK, LangGraph, AutoGen, and CrewAI.

A multi-agent system is a way to spend more compute and complicate coordination, and it's needed only when it measurably solves a problem a simpler variant couldn't. The most common mistake starts not in the prompt but in the architecture diagram: the developer draws supervisor, planner, researcher, critic, and reviewer up front, though the task is solved by one model call with two tools. Role names create the feeling of a system but don't prove the split is useful.

The book's backbone is one companion project in strict, dependency-free TypeScript. In it a multi-agent system is assembled as a distributed workflow: typed agent contracts, a validated task DAG, a DAG scheduler over the ready set, an artifact store with write scopes and optimistic concurrency, a budget ledger, an append-only event log, traces, and an independent evidence-gated review - 17 automated tests and an end-to-end demo with no API keys. The official mechanisms (OpenAI Agents SDK, Claude Code subagents and agent teams, LangGraph, AutoGen, CrewAI, Temporal, MCP, and A2A) are covered as tools inside this engineering model, not as a ready answer.

The architectural and product claims are verified against the official documentation, specifications, and engineering publications as of August 1, 2026; third-party tutorials, framework rankings, and marketing retellings were not used as a source of facts. From here we walk the whole path - from a single-agent baseline and a task graph to topologies (router, supervisor, agents-as-tools, handoff), context isolation, durable orchestration, trust boundaries, tracing, metrics, and a staged rollout of autonomy. This book closes the series on agents; surfaces change faster than the engineering model, so the title carries the year.