Scope an AI agent that can work in production
A production AI agent brief defines a job, the systems it may use, the decisions it may make, and the evidence required to trust the result. Start with one bounded workflow and a measurable baseline. Expand autonomy only when evaluations and real operating evidence support it.
Put the guide to work.
Leave with a build scope, an initial evaluation set, and a clear boundary between a useful prototype and a system ready to operate.
No signup required. Open Markdown in a text editor or document tool; open CSV in your spreadsheet app. Adapt either for your business or client work.
Describe one job from trigger to finished result
Replace ‘we need an AI agent’ with a workflow someone can demonstrate. For example: when a client brief arrives, extract requirements, find approved inventory information, and draft a plan for a media planner to review. Define where the workflow starts, where it ends, and what the reviewer receives.
Record the current volume, handling time, quality standard, and recurring exceptions. Separate observed baseline data from estimates. A useful first build should make one job easier to complete and easier to check. A broad promise to automate a department does not tell a builder what done means.
Choose the simplest system that fits the work
Some jobs need a fixed workflow with a model handling one step. Others need an agent to choose tools and steps as it learns more. Anthropic distinguishes these patterns and recommends increasing complexity only when it improves the outcome. Ask a prospective builder to explain why the workflow needs agentic decisions.
Write down the ordinary path, the ambiguous path, and the failure path. Consider a copilot that drafts for a person when the action requires judgment or carries a meaningful cost. Consider multiple agents only when separate responsibilities create a measurable benefit after accounting for coordination, latency, and cost.
Specify data access and action boundaries
List each system, the records the agent needs, the authoritative source, and the permission owner. Separate reading, drafting, and changing records. Define which actions can happen automatically and which require a person to review the exact proposed change. Approval should attach to an understandable action such as sending a client email or changing a budget.
Include stale records, contradictory instructions, unavailable tools, and untrusted text in the scope. Ask how the system checks permissions outside the model, prevents duplicate actions when work retries, and records what changed. A model’s confident answer does not verify that an external update succeeded.
- Inputs, authoritative records, and permitted uses
- Read, draft, and write permissions for each integration
- Human approval points and prohibited actions
- Timeouts, retry limits, duplicate protection, and a stop control
Turn acceptance criteria into evaluation cases
Collect representative examples with permission to use them. Include routine work, ambiguity, missing data, permission failures, and cases where the correct result is to stop. Describe the expected business outcome and any unacceptable action for every case. The CSV template provides a blank structure and clearly labeled illustrative cases.
Anthropic’s evaluation guidance distinguishes a run’s conversation and tool activity from the resulting state. Apply that distinction when reviewing a build: a convincing explanation is weaker than a correctly updated record or a draft that satisfies the brief. Combine automated checks with human review where quality requires judgment, and repeat trials when behavior varies.
Choose launch thresholds for task success, unacceptable errors, human rework, latency, and cost with the business owner. Keep a separate evaluation set for the release decision, and record the system version tested. A demo using three handpicked examples cannot establish reliability across a working queue.
Include the cost of operating the system
Request separate estimates for discovery, implementation, integrations, evaluation, and ongoing support. Recurring cost should include model use, tools, hosting, human review, monitoring, and maintenance. Ask what happens to unit cost when a case needs several attempts or a provider changes behavior.
Estimate cost per accepted task, including rework, and compare it with the current process. Treat time saved as capacity until you can show how the business uses it. Document who handles failures, who can change the system, and who owns the code, data, accounts, and operating instructions at handoff.
Make the launch a sequence of evidence checks
Begin with representative data in a controlled environment. Move to draft-only or shadow operation where appropriate, then a limited live scope with a named owner. Review the results before expanding volume, integrations, or write permissions. Each expansion changes the job the system is trusted to do.
The worksheet ends with a release decision, rollback route, support owner, and review date. Those are part of the product you are commissioning. They give your team something concrete to operate when the build team finishes.
Questions before you start
Do we need an autonomous agent?
Possibly, but a fixed workflow or a copilot may solve the job with less complexity. Start with the decisions the system must make and compare options against the same acceptance criteria.
What should we bring to the first development conversation?
Bring a workflow example, current handling time and volume, sample inputs you are permitted to share, the systems involved, and the actions that require approval. Include a few failures as well as ideal examples.
How do we tell whether a prototype is production-ready?
Check representative evaluation results, integration behavior, access controls, failure recovery, ongoing cost, and operational ownership. The agreed release criteria should cover the complete workflow and resulting system state.
This guide and its worksheets are original Revenue Arc planning tools. They do not represent a benchmark study or guarantee an outcome. Use your own inputs, document assumptions, and confirm the scope with the people responsible for delivery.
Turn the workflow into a build brief.
Tell us where work gets stuck, what a useful result looks like, and which systems need to connect. We can help define the first useful release.
Discuss an AI build