I replaced chaotic solo Claude coding with a simple 3-agent team (Architect + Builder + Reviewer) — it's stupidly effective and token-efficient
TL;DR Highlight
This post shares the experience of adopting a 3-agent structure separating the roles of Architect, Builder, and Reviewer, instead of relying on a single Claude, to simultaneously improve coding quality and token efficiency.
Who Should Read
Developers utilizing the Claude API to automate coding tasks or design AI agent workflows. It is particularly useful for those who have experienced quality degradation or token waste when handling complex tasks with a single LLM call.
Core Mechanics
- Access to the original article is blocked, so we can only summarize based on the title.
- The 3-agent structure separates Claude into three roles: Architect (design), Builder (implementation), and Reviewer (review).
- It claims to solve the problem of tangled context and token waste that occurs when entrusting all tasks to a single Claude session.
- The logic is that focusing each agent on its assigned role reduces the context window for each call, increasing token efficiency.
- The structure overcomes the limitations of self-review by having the Reviewer agent separately review the Builder's output.
Evidence
- "(No comment information)"
How to Apply
- When developing a new feature, assign only the Architect role to the first Claude call and have it perform only 'requirement analysis → component separation → interface design', and then pass the results to the prompt of the next call to have the Builder write the actual code, configuring a pipeline.
- Instead of using the code generated by the Builder as is, automate the review stage by creating a third Claude call with a separate Reviewer role prompt ('Find bugs, security vulnerabilities, and performance issues in this code').
- Design prompts to minimize unnecessary token usage by passing only minimal context between agents (e.g., Architect → Builder only the design document, Builder → Reviewer only the code).
Code Example
snippet
# handoff/brief.md 예시 (Architect → Builder)
## Task Brief
**Goal:** 사용자 프로필 수정 API 엔드포인트 추가
**Scope (이것만 구현):**
- `PATCH /api/users/:id` 엔드포인트
- 수정 가능 필드: name, bio (email 제외)
- 입력 유효성 검사 포함
**Out of Scope (절대 추가 금지):**
- 인증 미들웨어 변경
- 다른 엔드포인트 수정
- 리팩토링
**완료 기준:**
- 위 두 필드만 업데이트됨
- 잘못된 입력 시 400 반환
- 기존 테스트 통과
---
# Builder 시스템 프롬프트 예시
"brief.md에 명시된 것만 구현하라.
범위 밖 기능 추가, 리팩토링, 스타일 변경 금지.
완료 후 handoff/review-request.md에 변경 파일 목록 작성."Terminology
컨텍스트 윈도우(Context Window)The maximum number of tokens (text units) that an LLM can process in a single call. As the conversation gets longer, this space takes up more space, increasing costs and degrading performance.
멀티-에이전트(Multi-Agent)An architecture in which multiple AI instances with different roles cooperate to perform tasks, rather than a single AI model handling everything.
토큰(Token)The basic unit that LLMs process text with. Approximately equivalent to 0.75 English words, and API usage costs are calculated based on the number of tokens consumed.