{"schemaVersion":"1.0","canonicalUrl":"https://www.iamgeorgekelly.com/field-guide/agentic-commerce","markdownUrl":"https://www.iamgeorgekelly.com/field-guide/agentic-commerce/index.md","editorialNote":"AI-assisted research and drafting. Provider-specific claims link to primary sources. Frameworks are editorial proposals; worked examples are illustrative and are not employer performance results.","slug":"agentic-commerce","title":"Agentic commerce starts with an operating model.","description":"A practical framework for choosing agent-assisted commerce work, setting decision rights, and proving that the result is worth the cost.","category":"Strategy","status":"published","published":"2026-09-05","updated":"2026-09-05","author":"George Kelly","answer":"Agentic commerce is the use of software agents to interpret commercial goals, work with business information, and select or perform actions. A useful implementation connects four things: a trustworthy source, a bounded decision, an authorized action, and evidence of the result.","sections":[{"id":"what-counts","title":"What counts as agentic commerce?","paragraphs":["A shopping assistant is one expression of agentic commerce. The operating work behind a store is another: reconciling a product record, preparing a merchandising change, investigating a conversion problem, or assembling a campaign brief. The commercial question is the same: which decision becomes better, faster, or less expensive?","Use a fixed workflow when the steps are predictable. Consider an agent when the next useful step depends on what it finds. Anthropic makes this architectural distinction between predefined workflows and agents that choose their own process and tools. That distinction is more useful for implementation than treating every automated task as an autonomous agent.","This guide proposes an operating framework for commerce leaders. It is an editorial decision aid, not a maturity benchmark or a claim that a particular employer uses this architecture."],"sources":["anthropic"]},{"id":"four-part-contract","title":"The four-part operating contract","paragraphs":["Before selecting a model, write one sentence for each part of the contract below. If the team cannot name a source owner or define a successful result, the missing work is operational. A more capable model does not resolve that ambiguity."],"table":{"headers":["Part","Decision to make","Concrete example"],"rows":[["Source","Which record is authoritative, and how current must it be?","Read the approved variant record and the current sellable availability."],["Decision","What judgment can the system make?","Flag conflicting dimensions and propose a corrected description."],["Action","What may it change, for whom, and within which limits?","Create a draft; route publication to the named owner."],["Evidence","What proves the result and where is it recorded?","Compare the approved draft with the rendered product page and retain the difference."]]}},{"id":"choose-first","title":"Choose the first workflow by its failure mode","paragraphs":["Start with a task that happens often enough to evaluate, has an accessible source, and produces an artifact a person can inspect. Product-data reconciliation, a sourced campaign brief, or a draft landing-page review are useful candidates. A task involving unbounded spend or customer commitments needs a much more explicit operating contract.","Take a product-description refresh. The input is a list of variant identifiers and approved facts. The output is a proposed change with citations to those facts. The first version ends at a preview. The acceptance check compares identifiers, units, included components, and links. Missing facts become exceptions, rather than plausible additions to the copy.","A deterministic rule may be enough to detect a missing unit. An agent may be useful when it must reconcile a specification sheet with a structured record and explain the conflict. Keep the rule for the predictable part and reserve the model for the interpretation."]},{"id":"score-work","title":"Use a decision record instead of a single readiness score","paragraphs":["A blended score can conceal the one condition that should stop a release. Record each condition separately. A high-volume task with no reliable source is still a poor candidate for unattended execution.","For each candidate, capture frequency, baseline handling time, source quality, reversibility, reviewer effort, and the cost of an incorrect result. Then choose the smallest trial that can disprove the proposed benefit. Twenty representative cases can be a useful starting experiment; it is not a statistically sufficient sample for every workflow."],"list":["Name the task owner and the current process before proposing the replacement.","Collect ordinary cases and difficult exceptions; keep both in the evaluation set.","Define acceptance criteria before looking at the agent’s output.","Count review, correction, tool calls, and failed runs in the cost comparison.","Expand the action boundary only after the narrower workflow produces repeatable evidence."]},{"id":"measure","title":"Measure accepted work, not generated output","paragraphs":["A completed run is not necessarily completed work. A useful operational measure is accepted artifacts per unit of total handling time. Include the person who reviewed the result and the person who repaired the mistake. Track exception rate separately so a faster average does not hide a worse customer outcome.","For an illustrative trial, suppose ten briefs previously required 300 minutes. The assisted process takes 70 minutes to generate, 130 to review, and 40 to correct: 240 minutes total, or 60 minutes saved. Claiming 230 minutes saved by counting generation alone would overstate the improvement. These are synthetic figures, not portfolio results.","The next decision is whether those 60 minutes are worth the operating cost and whether the briefs meet the same quality bar. A profit calculation and a workflow acceptance record make that discussion concrete."]},{"id":"first-memo","title":"A one-page brief for the first pilot","paragraphs":["Write the goal as an observable outcome: prepare an accurate draft for a defined product family within a specified review budget. List the approved inputs, allowed tools, forbidden assumptions, review owner, and stopping conditions. Attach the evaluation cases and the artifact that will be compared with the baseline.","Finish with a decision date and three possible outcomes: stop, revise the narrow workflow, or expand a specific permission. Avoid treating a successful demo as permission to automate the adjacent business process. The operating model should travel with the implementation."]}],"sources":[{"id":"anthropic","title":"Anthropic: Building effective agents","url":"https://www.anthropic.com/engineering/building-effective-agents","note":"Supports the workflow-versus-agent distinction. The commerce operating contract and examples here are original editorial frameworks.","checked":"2026-09-05"}],"related":["supervised-commerce-workflows","product-data-for-agents","roas-poas-profit"],"project":"american-standard-bathing"}