Multi-agent workflows can burn billions of tokens unless you control duplication
HaktanSuren · x · 2026-08-04
This article argues that multi-agent systems are often far more expensive than people realize because overlapping reads, summaries, retries, and duplicated checks can burn through huge token budgets.
Using examples from Anthropic, OpenAI Codex, and agent research, the author argues that token usage is not output but a cost meter. The piece recommends treating agent orchestration as a process problem: make agents prove their work, reduce duplicated context, and design workflows with explicit cost controls so token spend tracks actual value.
More from coding & agent
- Gemini Spark can connect MCP servers, but every tool still needs repeated approval — tristanbob · 2026-08-04
- Agent apps should expose a skill surface, then crystallize it into code — burny_tech · 2026-08-04
- Use subagents to switch models inside one session — dotey · 2026-08-04
- xAI updates Grok Build with Grok 4.5, skills, MCP, and plan mode — elonmusk · 2026-08-04
- RL on custom search harnesses may beat the “one big model” idea — shangbinfeng · 2026-08-04
- GitHub Copilot CLI 1.0.78 adds live tool timings and a new worktree command — copilot-cli-release-app[bot] · 2026-08-04