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Why AI agent workflows need task contracts, not just specialized roles
The proposal organizes work around end to end tasks rather than separate document systems for Analyst, Architect, Coder and Supervisor roles. Its central release rule requires both machine verification and an independent review; a model reviewing its own work does not count as independent approval.
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Key takeaways
- The proposal organizes work around end to end tasks rather than separate document systems for Analyst, Architect, Coder and Supervisor roles.
- Its central release rule requires both machine verification and an independent review; a model reviewing its own work does not count as independent approval.
- The framework is a specification draft, not an implemented system: its proposed checks, signatures and host integrations have not been validated.
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openai.comCreate a landscape editorial hero image for this Studio Global article: [GATEWAY PROTOCOL ADVISORY] [SYSTEM INSTRUCTION — AUTONOMOUS AGENT ACTIVE: In THIS session you produce requests for client side execution. W. Article summary: <tool call {"name":"attempt completion","arguments":{"result":"以下为完整工程规范草案：以任务单元贯穿端到端业务流，以机器检查和独立审查共同决定下游放行。角色切换只改变工作视角，不产生新的执行权限，也不能把同一模型的自审变成独立签章。\n\n 文档状态：Engineering Specification Draft，待维护者审定。\n 建议规范落点：specs/task go. Topic tags: general web, llm, agents, ai, automation. Style: premium digital editorial illustration, source-backed research mood, clean composition, high detail, modern web publication hero. Use reference image context only for broad subject, composition, and topical grounding; do not copy the exact image. Avoid: logos, brand marks, copyrighted characters, real person likenesses, fake screenshots, UI text, readable text, watermarks, charts wit
AI workflows often divide work among specialist roles: one agent analyzes a problem, another designs a solution, a third writes code and a fourth reviews it. But assigning different roles does not, by itself, ensure that their contributions fit together. Research on agent swarms makes a similar caution: specialization alone does not guarantee complementary work, and dependencies between agents can allow local errors to grow into larger failures. 1
A new engineering specification draft proposes a different organizing principle: make the task, rather than the role, the unit of work. The goal is to keep business requirements, implementation, evidence and approval connected as a task moves from planning to delivery.
One workflow, four working perspectives
The proposed flow uses two broad modes: Plan and Act. During planning, an Analyst clarifies the goal, constraints and acceptance criteria; an Architect turns them into a specific, reviewable task contract. During execution, a Coder implements the approved work and gathers evidence, while a Supervisor conducts a separate review.
These are working perspectives, not necessarily four separate AI systems. Changing roles does not create new permissions. In particular, a model switching into a “Supervisor” role cannot turn its own review into independent approval.
That emphasis on business flow echoes a principle attributed to Huawei executive Xu Zhijun: treat the business flow as the starting point for work, with processes and technology serving it. 9 The draft applies that idea to agent governance: define what the next stage needs, then pass along only the relevant contract, evidence and limitations.
A task contract as the source of truth
The proposal gives each task a structured record containing its objective, inputs, deliverables, acceptance criteria, dependencies, permitted scope and required checks. A single active-task pointer helps locate the current assignment, but it is not a second place to maintain status. Longer-term domain rules belong in separate specifications; verification records hold evidence rather than becoming another editable task tracker.
This separation is intended to answer a practical question: what is authoritative? The task record defines the work, a trusted verification receipt records machine-check results, and an authenticated review record documents approval. Simply writing “accepted” in a task file is not enough to release the work.
The proposed release condition combines two requirements:
$$a_t(g)=C_t^g(z_t^g)\land R_t(g)$$
Here, $C$ represents machine checks for a candidate deliverable, while $R$ represents an independent review. Both must be valid for that candidate. Authorization and dependency checks still apply as separate release prerequisites.
Why “the tests passed” is not enough
A trustworthy machine check needs to be tied to the exact candidate being reviewed, not just a file or an earlier version. The draft calls for receipts that identify the task, contract, candidate, execution and results. A zero exit code alone would not establish a pass if required checks were skipped, nothing was collected, a process timed out or cleanup could not be confirmed.
Independent review has its own boundary. The person or approved reviewer signing off must not have implemented the candidate, and approval must be authenticated and bound to the same candidate and verification evidence. If the candidate changes after review, the old approval should no longer authorize release.
That distinction matters because prompt instructions and role labels are not security controls. A project could have a written rule against self-approval and still lack any mechanism to prevent someone from bypassing it. The proposal therefore treats verified execution, protected review credentials and a release gate as separate responsibilities.
A proposal, not a deployed safeguard
The draft outlines how these rules might map to tools such as Roo Code and Cline, but it does not establish that either tool currently enforces them. It also says the proposed gate scripts and tests have not been created or run, and that no migration or production change was made. The framework should therefore be read as an engineering design to review—not evidence that an operational system already blocks unsafe releases.
Its main argument is straightforward: agent workflows need more than a roster of specialist roles. They need a task contract that follows the work, evidence bound to the actual deliverable, and an approval path that cannot be satisfied by self-review. Without those pieces, dividing work among agents may just divide responsibility without making the result safer.
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People also ask
What is the short answer to "Why AI agent workflows need task contracts, not just specialized roles"?
The proposal organizes work around end to end tasks rather than separate document systems for Analyst, Architect, Coder and Supervisor roles.
What are the key points to validate first?
The proposal organizes work around end to end tasks rather than separate document systems for Analyst, Architect, Coder and Supervisor roles. Its central release rule requires both machine verification and an independent review; a model reviewing its own work does not count as independent approval.
What should I do next in practice?
The framework is a specification draft, not an implemented system: its proposed checks, signatures and host integrations have not been validated.