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NewsMaterial3 min readDisconfirmAI Editorial

Amazon Quick Team Proposes Four-Question Classification for Agentic Primitives: Distinguishing Skills from Workflows via Confidence Contracts

The Amazon Quick team has introduced a primitive vocabulary that decomposes agentic work into four questions: When, What, Who, and How. Their core argument is that a single user request can have multiple valid implementation paths, distinguished by the 'confidence contract'—the degree of autonomy retained by the agent. This framework aims to resolve the recurring classification ambiguities encountered when building agent systems.

2026-11-07 01:34 GMT+8

When building agent systems, a persistent question arises: how should a given user request be classified? In a blog post published in November 2026, the Amazon Quick team offered their answer—not by providing a single definitive solution, but by introducing a shared vocabulary that allows different interpretations to coexist and switch seamlessly.

They break down agentic work into four fundamental questions: When (what triggers the work), What (the task content), Who (who performs it), and How (how it is executed). Triggers address both When and What; agents answer Who; and capabilities answer How. While this decomposition is straightforward, its value lies in enabling different implementation paths for the same request to exist not as mutually exclusive competitors, but as varying degrees of confidence within the same framework.

A 'confidence contract' defines the balance between the autonomy an agent retains and the extent to which the user pre-defines the process. The Amazon Quick team illustrated this with a concrete example: a user says, 'Monitor my Slack channel and send me a daily summary.' This request can be implemented in at least three ways: first, a scheduled task with a one-line instruction letting the agent decide how to proceed; second, a skill packaging explicit formatting rules and channel priorities; third, a workflow declaring deterministic steps and error handling. All three produce a daily summary; the difference lies solely in the latitude granted to the agent.

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This distinction yields a practical inference: a user request like 'I want an agent that monitors Slack and sends a daily summary' usually does not require creating a new agent or workflow, but rather adding a trigger to an existing agent. Based on this, the Amazon Quick team merges chat, scheduled, and so-called 'autonomous' agents into a single actor—one you can converse with, schedule, and which can orchestrate and inspect its own past work.

Regarding the relationship between skills and workflows, they propose two dynamic concepts: crystallization and dissolution. A well-understood skill can tighten into a workflow; a workflow frequently encountering edge cases can loosen back into a skill. This transition is driven by their continuous learning framework, with specific mechanisms detailed in subsequent articles.

Important caveats apply: this is an internal vendor-specific vocabulary designed to unify architectural discussions across their own product line. The article provides no evidence of independent adoption, nor controlled experiments demonstrating that this classification actually reduces builder confusion. Its current value remains at the level of 'a clear attribution argument'—the authors explain why a shared vocabulary is needed, how it is structured, and how it changes the classification of specific requests. For readers building agent systems, this four-question decomposition and the concept of confidence contracts offer a directly usable thinking framework, but treating it as an industry standard is premature.

Sources

  • aws.amazon.comAmazon Web Services↗
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