Select one real task, clarify authorized materials, deliverables, what's included and excluded, and validate one piece of work first.
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Get one real piece of work running first, then decide on AI Agent investment
Start with a real piece of work already in progress: first agree on scope, inputs and outputs, human confirmation points and acceptance criteria. Use authorized materials to complete a limited-scope trial run, check whether the results are useful and which steps still require humans, then decide whether to continue building.
First determine whether it's worth starting
Agree on three conditions so the pilot can be evaluated and stopped when needed.
The business owner agrees on facts, completeness and usage requirements, and clarifies which judgments and external actions must be confirmed by a person.
Agree on the trial scope and checkpoints first; if permissions are insufficient, results fall short of standards, or the scope changes, you can pause, retain materials and records, and hand back to a human.
If you can't articulate it clearly yet, there's no need to rush into building; describing the work itself is often the most valuable first step.
First look: which scenario should an enterprise AI Agent start with?Four ways to work together
Start with business analysis, and you can go all the way to ongoing operations.
Each approach starts with a specific task and a clear business outcome. Produce a result that can be checked first, then decide whether to expand scope, avoiding unnecessary system complexity from the start.
Produce a work statement that supports a go/no-go decision on a pilot
Break down the most recent real work clearly: who provides what input, what result must be delivered, where human judgment is required, and whether materials and permissions are available. Form a verifiable scope statement, acceptance requirements and items to be confirmed, then decide whether to proceed to trial operation.
- Clarify inputs, outputs, and scope exclusions
- Agree on who will review the results and the acceptance criteria
- List dependencies, stop conditions and an executable first step
Run one scenario end to end in real work
Suitable for individuals or teams that already have specific tasks but need to break them down together and run a trial. Complete one round of work with real materials, and adjust the rules, processes, review and handover methods.
- Scoped scenario pilot run
- Reviewable results and revision records
- A working method the team can take over
Turn confirmed processes into a usable system
Suited to teams with clear objectives, boundaries and owners. Complete the design and implementation of Agents, knowledge, tools, permissions, interfaces or automation flows, with acceptance testing.
- Design system boundaries around business processes
- Connect existing materials and work entry points
- Establish human confirmation and exception handling
Keep the system effective as the business evolves
Suited to teams already live but facing continuous changes in materials, rules, team and business. Continuously handle feedback, assess usage, update content and optimize processes.
- Materials and rules maintenance
- Usage feedback and quality review
- Adjust working methods as the business changes
Actual delivery process
Every step centers on a result that a business owner can check.
Put a recent real task on the table
Look at what the input is, who is involved, where the materials are, which step takes the most time, where judgment is needed, and what counts as a useful result.
Decide what to hand off to Agents and what must remain human responsibility
Clearly define data scope, permissions, tools, prompts, approvals, exceptions and fallback methods; do not hand high-risk decisions to unverified automation.
Check the first version against the agreed criteria, then decide whether to continue or stop
Run a trial with authorized real materials within the agreed scope, checking facts, format, omissions and human confirmation against pre-confirmed criteria. Record the results and any failed items; if materials, permissions or quality do not meet the conditions, pause or hand back to a human, adjust the scope, then decide whether to continue.
Keep what has been validated
Form reusable processes, material structures, review checklists and maintenance responsibilities; when it's worth expanding, continue building more scenarios.
Suitable starting points for collaboration
You're not required to first write your requirements as a technical solution.
Suitable to start now
A task has already happened repeatedly; the team is willing to provide anonymized materials; someone can judge business results; you want to validate value first, then decide how deep to invest.
Don't rush to do it for now
There's no clear work objective yet; you're just chasing a trending tool; no one is responsible for acceptance; or you hope AI will directly replace all key judgments.
Let's talk first
Bring one real piece of work, and start by clarifying scope and acceptance criteria.
Describe the most recent task, the redacted materials you can provide, the results you want delivered, and who can confirm the results. If you can't cover everything yet, describe the work first; clarify inputs and outputs, human confirmation and acceptance requirements, then decide on the pilot run and build investment.
After adding WeChat, you can say directly:
"Hi, I came from the website and want to talk about a piece of work."
You can add: input materials, expected output, confirming person, and the steps you want to improve.
AI practitioner exchange
If you want to keep in touch, you can also learn about the practitioner group.
If you'd rather discuss AI practice experience, you can separately learn about the content, boundaries and joining method of the 199 RMB AI Practice Exchange Group; for pilot runs and build collaborations, please use the contact entry above.