AI Agent Examples: 13 Small Business Jobs and What They Cost

The most useful AI agent examples are narrow jobs with visible handoffs: answering a support request, booking an appointment or preparing a code change. Marblism's bundle of AI work roles starts at $44 on monthly billing; Vida Global's business phone agents start with a $1,500 pilot. Choose the job before the vendor.

An AI agent takes a goal, picks its next steps and uses tools to complete the task. A basic chatbot only answers. The distinction is what happens after the conversation: looking up an order, writing to a calendar, preparing a customer record or running a software test. A chatbot interface can contain an agent, so judge the actions it can take rather than its appearance. Google Cloud's agent definition describes this goal-directed use of tools.

What an Agent Changes in a Small Business

The useful change is delegating a bounded task through to a reviewable result. You still define what success means, which systems the agent may use and when it must hand work back.

Consider a customer asking where a delivery is. An answer-only chatbot can explain your shipping policy. A support agent with an authorized order-lookup tool can retrieve that customer's order, interpret its status and answer the specific question. If the next step involves a refund outside your normal policy, your human check belongs before that decision.

The examples below describe available product workflows and clearly identified custom configurations. Prices and capabilities were verified against publicly accessible maker pages on 5 October 2026. Verification covered documentation and pricing; the business settings are illustrations, and the human checks are recommendations. There are no claimed deployment results or savings benchmarks.

AI Agent Examples in Real Life: Every Job, Tool, Price and Check

Start with the row whose finished result you can already inspect. Each starting price keeps its billing unit: a pilot fee, subscription, outcome or usage allowance buys a different thing.

Tidio's public Lyro card displays $32.50 per month without specifying the billing cadence on that card. Treat it as the published starting offer and confirm the chosen billing option. Its first 50 free AI conversations are a lifetime allowance; a recurring paid quota is a separate purchase. A cheaper Tidio human-helpdesk plan is a different product.

The Marblism examples share one subscription and its 50-hour monthly usage pool. The Vida rows show separate jobs the platform supports; the required pilot scope determines the quote. Do not add the repeated rows as if each requires another subscription or a separate pilot.

AI Agent Use Cases: Choose the Job You Already Understand

An agent earns a place when you can describe its input, permitted actions and finished result without relying on the vendor's demo.

For founders and buyers, the consequence is a narrower purchasing decision. A missed-call problem points to a phone workflow. A helpdesk backlog points to support. Buying a general platform before naming the job leaves you paying for a system you still have to design. Use the AI agent platform comparison after you know which workflow needs a home.

For operators, the new work is maintaining the rules and reviewing exceptions. Your return policy, calendar availability and definition of a qualified lead become working inputs. An obsolete policy can produce a consistent stream of obsolete answers. Good preparation makes the finished task easier to inspect.

For technical builders, the responsibility is connecting tools and making failures visible. If the job is specific to your business, the no-code AI agent builder comparison helps you choose the construction layer. For a wider software budget, the AI tools for small business guide puts agents alongside the other tools your firm needs.

Customer Support

Support is a sensible first agent job when your answers live in approved documentation and you already have a person handling exceptions. Begin with a well-defined question category rather than letting the agent interpret every policy dispute.

1. Tidio Lyro: Answer a Customer and Retrieve Order Information

Tidio Lyro AI Agent is a customer-service agent that answers from your support content and can use configured Actions for tasks such as order updates. A small online shop could give it shipping guidance and an approved way to retrieve an order's status. The goal is to finish the customer's question, including the information lookup, without an operator repeatedly copying information between systems. Tidio documents Smart Actions and human handoff.

What it does on its own: Interprets the support question, selects relevant knowledge, uses the Actions you have connected and responds. Its documented escalation behavior includes creating a ticket in a connected support system when a question falls outside its knowledge.

Where a person checks: Approve the knowledge before launch, inspect unanswered conversations and keep policy exceptions with an operator. For an order agent, check that the lookup identifies the right customer and that its access covers only the information needed for the answer.

Cost and limit: The Lyro pricing card starts at $32.50 per month, from 50 AI conversations. The first 50 free conversations do not renew. Full Actions access requires a paid Lyro quota; the introductory allowance is for evaluating the workflow.

The call: Choose Lyro when your main job is repeated support grounded in a maintained knowledge base. Wait if your policy exists mostly in the owner's head; write the policy before delegating it.

2. Intercom Fin: Resolve Email and Chat With a Clear Escalation Route

Intercom Fin AI Agent is an agent for customer-service conversations that can answer across email and chat, act on connected systems and hand an exception to a person. A small software company could use it for account and product questions while routing ambiguous billing issues to its support operator. Intercom's pricing page lists these capabilities and the option to use Fin with an existing helpdesk.

What it does on its own: Handles the conversation and performs actions you have configured in external systems. Its useful autonomy is getting the customer to a supported outcome, then passing work to your preferred inbox when human handling is needed.

Where a person checks: Review the approved knowledge, escalation rules and any action that changes an account. Inspect both the answer and the handoff: a tidy response is little help if the follow-up lands somewhere nobody watches.

Cost and limit: Fin starts at $0.99 per outcome. Using the full Intercom helpdesk adds seat pricing. Fin for an existing helpdesk has minimum commitments, and its voice pricing requires Sales; Intercom explains those commercial terms. An outcome price alone is an incomplete monthly budget.

The call: Fin fits a business with an established support queue and an owner for escalations. Ask how your exact workflow is billed before using the starting outcome rate in a forecast.

Phone Calls

Phone agents are useful when a conversation needs to create a record, route a caller or reserve a genuine appointment. Their weakest starting point is an undefined promise: “take care of whatever the caller wants.”

3. Vida Global: Capture Intake and Route the Caller

Vida Global is a business-agent platform that supports voice calls alongside messaging and other channels. A service company could configure an intake agent to collect the caller's request, write the relevant information into its customer relationship management system, or CRM, and route the call appropriately. Vida's official FAQ names intake, lead qualification, after-hours support and structured call data sent to external systems.

What it does on its own: Runs the configured intake conversation, gathers the required information and uses connected systems or call routing to move the request forward. The platform also provides transcripts and recordings, giving you something concrete to review.

Where a person checks: Approve the intake script and destinations before connecting a live number. Review missed fields, incorrectly routed calls and cases that require a promise about availability or service scope. For a local service business, a useful finished result is a request ready for dispatch to inspect.

Cost and limit: Vida's pricing page starts with a pilot investment from $1,500. The pilot cost credits toward the first production month. Enterprise and production deployment need a quote; the page provides no universal recurring price to copy into your operating budget.

The call: Vida fits a business that needs a scoped phone workflow with connected records and routing. For a very small call volume, decide whether you need that custom deployment before committing to the pilot.

4. Vida Global: Book an Appointment From the Call

Vida Global also supports appointment scheduling and calendar connections. A consultancy or repair business could configure a phone agent to collect the service requested, inspect the connected calendar and book within approved availability. This is a distinct job from taking a message: a usable calendar event is the finished result. Vida documents scheduling and system connections.

What it does on its own: Conducts the scheduling conversation and uses the connected calendar workflow you have configured. The caller does not need to wait for someone to turn their request into an appointment manually.

Where a person checks: Define the service types, acceptable times, booking buffers and circumstances requiring a callback. Review booked appointments against the caller's request. If staff availability is inaccurate in the calendar, fixing that source is part of running the agent.

Cost and limit: This uses Vida's pilot-led pricing, starting at $1,500, with production pricing by quote. Ask the pilot proposal to name appointment handling, calendar access and escalation explicitly. A price for your intake workflow does not automatically establish the scope of every additional job.

The call: Choose this when appointment handling is repetitive and the calendar is dependable. Keep unusual bookings with a person until you can express their rules clearly enough to enforce them.

5. Marblism Rachel: Answer Calls and Send a Useful Message Summary

Marblism Rachel is the receptionist role in Marblism's bundle of AI employees. Its public pricing page lists answering calls, booking appointments, taking messages and texting summaries. A solo agency owner could use Rachel to capture a request while they are in a client meeting, then review the summary afterward.

What it does on its own: Answers the configured phone workflow, captures a message and performs supported appointment handling. That gives the owner a recorded request to act on rather than another unanswered call.

Where a person checks: Confirm the service description and calendar rules, inspect summaries and define when a caller should be transferred. A message can sound convincing while missing the location, deadline or contact detail you need to do the work.

Cost and limit: The bundle costs $44 per month on monthly billing or $24 per month on yearly billing, with a shared 50-hour monthly allowance. Rachel consumes that allowance alongside the other roles. The billing documentation says her line pauses when hours run out, or transfers callers if transfer is enabled.

The call: Rachel is a practical packaged option for routine calls when the shared budget covers your workload. Watch the balance as part of operating the phone line.

Sales Follow-Up

Sales agents are easiest to judge when they prepare or execute a defined next step. You still own the target customer, the offer and the truth of every claim made in your name.

6. Marblism Stan: Find Prospects and Continue Follow-Up

Marblism Stan is the sales role in the same AI employee bundle. Its documented capabilities include automatic email outreach, follow-up sequences and meeting booking. An agency could configure a prospect profile, approve the message and have Stan work through the resulting outreach process. Those capabilities appear on Marblism's own pricing page.

What it does on its own: Works on prospect sourcing and the supported outreach sequence, including follow-up rather than stopping after the first draft. The goal should be an observable next step, such as a prospect response or a meeting request ready for the owner.

Where a person checks: Inspect the prospect list and approve claims, offers and message tone before outreach. A person should handle negotiation and replies that change the offer. Sending more messages to the wrong audience expands the wrong workflow.

Cost and limit: Stan is included in the $44 monthly or $24 annual-equivalent base offer. Its tasks draw from the same 50-hour pool as Rachel and Eva; there is no separate starting subscription to add for each role. When the balance runs out, new daily outreach pauses, according to the maker's billing documentation.

The call: Stan fits a business that already knows its customer and can judge the outreach. Wait if you are still discovering the market; keep learning from conversations before automating them.

7. Zapier Agents: Enrich an Inbound Lead Before Follow-Up

Zapier Agents is an agent builder for work across connected business apps. Its published templates include researching and enriching leads, plus alerting on qualified form submissions. A small B2B company could configure an agent to research a new inquiry, attach relevant company details to the approved record and prepare the context a salesperson needs.

What it does on its own: Researches the lead and uses the apps and actions you have connected. A trigger starts the work; the agent can choose its tool calls within that configuration.

Where a person checks: Verify important contact details and the qualification rule before treating enriched information as fact. Keep pricing concessions and outbound promises behind your review. An inferred company attribute should remain visibly uncertain in the record.

Cost and limit: Agents Free includes 400 activities per month. Pro lists $33.33 per month with $400 billed annually and 1,500 activities. Browsing, knowledge lookups and app actions count as activities, so a lead can consume several.

The current complication: Zapier is migrating Agents into AI by Zapier. Its guidance, updated on 1 October 2026, describes keeping the reasoning and tool calls inside an AI step. It has not announced an Agents shutdown date. For a new build, check the migration path and its billing before choosing the standalone setup.

Back Office

Back-office agents fit tasks where a person can inspect a draft or exception queue before a consequential action. The workflow needs a defined destination for the unfinished cases.

8. Marblism Eva: Sort the Inbox and Draft Replies

Marblism Eva is the bundle's executive-assistant role. The maker lists email drafting, meeting notes, calendar management, follow-ups and a morning briefing. An owner could delegate routine inbox preparation so messages needing a decision are easier to find. Marblism's pricing page describes the role.

What it does on its own: Processes the configured inbox work, prepares replies and performs supported assistant tasks. The useful result is a reviewed queue or draft that preserves enough context for you to make the decision.

Where a person checks: Inspect recipients, dates and commitments before sending important replies or changing the calendar. A polite draft that accepts a deadline you cannot meet is still a bad result. Keep your instruction specific about which messages need your attention.

Cost and limit: Eva shares the same $44 monthly base subscription and 50-hour pool. The maker assigns fixed allowance values to processing mail and drafting replies; reviewing work itself is free. This means using Eva heavily changes the budget available to Rachel and Stan.

The call: Eva fits an owner with repeated inbox work and clear priorities. If almost every message needs the owner's judgment, delegate sorting and drafting first, then retain the decisions.

9. n8n: Build an Invoice-Exception Reviewer With Approval Before Actions

n8n is a workflow builder whose AI Agent node connects a model to tools and lets the agent choose which tool to call. An invoice-exception reviewer is a custom configuration you could build: provide invoice fields, connect a purchase-order lookup tool and allow creation of a draft record for the operator. The documented agent mechanism supports that construction; it does not supply an already-configured invoice system. n8n explains its tool-using Agent node.

What it does on its own: In your configured workflow, selects the lookup tool, compares the returned information with the supplied invoice data and prepares the result. A fixed workflow carries the input and destinations; the agent handles the part requiring judgment.

Where a person checks: Confirm supplier, amount and supporting order information. Put actions that write or change business records behind an explicit approval step. n8n supports human review of selected tool calls, including approving or denying the exact proposed inputs.

Cost and limit: Cloud Starter currently lists €20 per month billed annually for 2,500 workflow executions with unlimited steps. The pricing page defines an execution as a full workflow run. Your configured models, connected services and operating effort also need a budget.

The call: Choose n8n when someone can own connections, exceptions and workflow maintenance. A fixed-rule invoice check may be enough when every decision is deterministic; add an agent only to the judgment step.

Research

Research agents help when the work involves collecting evidence and turning it into a useful artifact. The final check is whether the artifact's claims are supported by its sources.

10. MindStudio: Build a Daily Competitor-Change Researcher

MindStudio is a builder for custom agents with tools, schedules and review checkpoints. Its own site gives daily monitoring of competitor websites and changes to product offerings or terms as an example. A founder could configure a researcher to watch named public pages and prepare a change brief for review. MindStudio documents that example and its deployment options.

What it does on its own: Uses your configured schedule and URL or web-research tools to gather information, analyze changes and produce the brief. The maker supports notifications and human approval checkpoints, allowing the review to be part of the workflow.

Where a person checks: Read the original page before changing your own positioning or prices. A rewritten marketing sentence may be a meaningful launch or merely editorial cleanup. Ask for links and enough source context to make that judgment.

Cost and limit: Free is $0 platform fee plus model usage, with one agent and 1,000 runs per month. Individual is $20 monthly plus usage, or $16 per month billed yearly, with unlimited agents and runs. MindStudio says model usage is charged at provider rates without markup and supports spend limits.

The call: MindStudio fits a specific research job that packaged tools do not express well. You own the workflow definition and source selection, even when its builder creates the initial scaffold.

Create Your Own AI Agent for Free

You can begin building this workflow on MindStudio's free platform plan, but model usage remains a cost. Write the goal as “report meaningful changes on these approved pages,” specify a reviewable brief with source links, and limit its tools to gathering information and delivering the draft.

A complete definition also names what to do when a page cannot be read. The agent should report missing evidence rather than quietly turn yesterday's data into today's finding. That is a workflow rule you supply, not a performance guarantee from the free tier.

11. ChatGPT Work: Prepare a Supplier Comparison Spreadsheet

ChatGPT Work is OpenAI's task-completion mode for creating reviewable files and carrying work through connected tools. Its current documentation illustrates making a comparison spreadsheet from notes, files and research. A small business could give it approved supplier materials and a clear set of criteria, then request a spreadsheet with evidence, missing information and a recommendation. OpenAI describes this workflow.

What it does on its own: Gathers the approved information, structures the comparison and creates the reviewable artifact. Available plugins and tools determine which sources it can retrieve. You can follow progress and steer the task as it works.

Where a person checks: Inspect the source for each important claim, the meaning of estimated figures and the weighting of your criteria. Verify a supplier's current offer before choosing it. An attractive spreadsheet does not establish that missing evidence was obtained.

Cost and limit: OpenAI's current pricing page includes limited free Work access and lists Plus at $20 per month as an entry paid option. Work shares usage with Codex, with limits and credits applying. Connected tool access varies, so the subscription is a starting budget rather than a guaranteed quantity of finished supplier reports.

The call: Use this for a reviewable research artifact when your source set and evaluation criteria are clear. A recurring supplier-monitoring job additionally needs a saved schedule and a check that the scheduled run completed.

Coding

Coding agents are useful to a founder who has a repository and someone able to review changes. The finished result should be a bounded code change with checks, rather than an undefined instruction to “build the business.”

12. Claude Code: Diagnose and Fix a Bounded Bug

Anthropic Claude Code is a coding agent that reads a project, plans work, edits files and runs commands. Its documentation describes tracing a bug through the codebase, implementing a fix and verifying the work. A technical founder could assign a reproducible form-validation error and ask for the smallest fix with relevant tests. Anthropic documents these workflows.

What it does on its own: Chooses the investigation steps, finds relevant files, makes the change and uses project commands to check it. This is agent behavior because it acts on the repository toward a goal rather than merely suggesting a code snippet.

Where a person checks: Read the changed code and the test results, then decide whether to merge and deploy. Give it a bounded issue and the repository's conventions. Broad access does not remove the need to understand a change to customer-facing behavior.

Cost and limit: Claude Pro includes Claude Code at $20 on monthly billing. The annual offer is $200 paid upfront. Usage limits apply; a subscription is not a fixed promise of bugs solved.

The call: Claude Code fits a technical founder or developer who can inspect its work. An operator without a code-review owner should first arrange that ownership.

13. GitHub Copilot Cloud Agent: Prepare a Backlog Change in the Background

GitHub Copilot cloud agent is a background agent that works in a GitHub Actions environment on a repository branch. GitHub documents repository research, implementation plans, bug fixes, test coverage and documentation work. A small software business could assign a defined logging improvement, let the agent prepare the changes and review the result before merge. GitHub describes its cloud agent.

What it does on its own: Investigates the repository, prepares a plan and changes code on a branch, with the option to open a pull request. It can continue background work while the developer handles something else.

Where a person checks: Review the branch changes, the checks that ran and the final pull request, or PR, which is the proposed mergeable code change. Organization policies and repository settings can also control whether the agent is enabled.

Cost and limit: Copilot Pro starts at $10 per user per month and includes cloud-agent access. Agent usage consumes GitHub AI Credits; the plan currently lists $15 in monthly total credits for Pro. Check the usage budget before expanding from occasional backlog work to sustained agent sessions.

The call: Choose it when the work already lives in GitHub and a developer owns the merge. A background agent can prepare work, but the quality bar for the resulting software remains yours.

AI Agent Architecture: Where the Human Check Belongs

Put the human check at the point where an error would become a business commitment. Let the agent choose the intermediate steps within the tools you have deliberately authorized.

A useful architecture is a loop: goal, plan, tool action, inspect the result, then continue or return the work for review. The tool can be a calendar lookup, a customer record, a website reader or a test command. The agent needs a way to recognize that the information is insufficient and hand the task back.

For support, your check might be an exceptional refund. For sales, it is the claims and offer in the outreach. For research, it is the source behind a recommendation. For code, it is the change before deployment. The same word, “agent,” covers different permissions and different consequences.

When building in n8n, the documented route is AI Agent node → Tools Panel → Human review → chosen approval channel, then connecting the action tools to that review step. The review request shows the proposed tool and inputs. Keep that information visible enough for the operator to make a decision.

What the Starting Prices Buy

Compare the total cost of an accepted result, including review and the commitment required to get the advertised price. The entry price is a useful filter, but its unit controls your operating budget.

A Shared Marblism Subscription Has a Shared Ceiling

Rachel, Stan and Eva together start at one $44 monthly subscription with 50 allowance hours. Marblism's published task values assign 10 minutes to a handled call and 5 minutes to a drafted email.

Here is an illustrative allocation, counting only those two task types:

• 100 handled calls × 10 minutes = 1,000 allowance minutes, about 16.7 hours.
• 100 drafted emails × 5 minutes = 500 allowance minutes, about 8.3 hours.
• Together they consume 25 of the 50 monthly allowance hours, leaving 25 before other work.

These are the maker's fixed task charges applied to an example workload. Treat the hours as a usage allowance when budgeting; this calculation measures no human time saved. The useful insight is that an inbox-heavy month can leave less capacity for calls, even though both roles are included.

Annual Prices Require an Annual Decision

The published MindStudio Individual offer is $20 on monthly billing or $16 per month on yearly billing. That is $240 versus $192 in platform fees over a year, a $48 difference, with model usage added in both cases.

Marblism's base offer is $44 monthly or $24 per month yearly: $528 versus $288 over a year, a $240 difference. A lower annual-equivalent price becomes useful after you know the workload fits.

n8n Starter's displayed €20 monthly rate is billed annually, a €240 annual platform commitment. The rendered pricing page quotes this offer in euros; no dollar conversion is assumed. You should compare it with a monthly subscription using the commitment as well as the headline rate.

Outcomes and Activities Need Their Own Forecast

At Fin's starting $0.99 rate, 100 chargeable service outcomes produce a $99 usage component. Seats, minimum commitments and the exact commercial setup still affect the total. Count the unit the vendor actually bills.

For Zapier Agents, suppose your specific lead workflow uses five activities per lead. Its 400-activity free allowance would cover 80 such leads; 1,500 activities would cover 300. Five is an illustrative assumption, and real workflows consume different activity counts. Check how the migration changes billing before carrying that forecast into AI by Zapier.

For ChatGPT Business, the maker's two-user minimum makes the $20 annual-equivalent seat price at least $40 per month, or $480 over a year. Monthly billing at $25 per user starts at $50 for two users. A solo research task may justify a different plan from a shared company workspace.

Your adoption calculation can stay simple: total tool and operating cost divided by completed results you accepted. Then compare that cost with the value you observed after subtracting review effort. You need your own workload evidence to complete that calculation; a vendor's demo supplies no universal return on investment.

What Is Overhyped About Business Agents?

The overstatement is the promise that giving an agent a broad goal removes the need to design the surrounding workflow. You still need current source data, a defined handoff and someone responsible for unfinished work.

“AI employees” is a product category, not evidence that the subscription supplies a complete business function at unlimited volume. Marblism's shared allowance and pause behavior matter when you depend on it for a phone line. MindStudio's free platform fee still leaves model usage to budget. Coding access still leaves code to review.

Product transitions create another practical limit. Zapier's migration guidance warns that the original agent and migrated Zap can both run. Turn off the original after the new workflow is ready, or the same event may trigger duplicate actions.

Act now when the job repeats, the source data is dependable and a person can inspect the finished result. Wait when the policy, calendar or customer definition is unsettled. Keep your current process when a fixed automation already completes the task reliably; an agent needs to earn the additional judgment and operating cost.

Frequently Asked Questions

What are the top 5 AI agents?

For the jobs covered here, five useful starting choices are Tidio Lyro for support, Vida Global for phone workflows, Marblism for packaged assistant roles, MindStudio for a custom agent and Claude Code for coding. The best choice depends on the job, the billing unit and who can review the result.

What are the big 4 AI agents?

There is no standard four-vendor category. Tidio, Vida Global, MindStudio and Marblism are four relevant small-business options, but they solve different problems. Compare the specific workflow before treating them as substitutes.

What are the 5 types of AI agents?

IBM describes five common types: simple reflex, model-based reflex, goal-based, utility-based and learning agents. Those names describe ways agents make decisions, not a shortlist of business software. For buying decisions, focus on the tools the system can use and the human check.

What are the 7 types of AI agents?

There is no universal seven-type list. Classifications use different dimensions; Google Cloud, for example, discusses interactive versus background agents and single-agent versus multi-agent systems. A larger count does not establish greater autonomy or a better product. See Google Cloud's categories.

Is ChatGPT an AI agent?

ChatGPT Work can act as an agent: it uses approved tools and files to complete a goal and produce work for review. A basic chat exchange that only answers a question does not demonstrate that behavior. OpenAI's current Work documentation describes the distinction.

Is Claude an AI agent?

Claude Code is an agent because it chooses steps, edits project files and runs commands toward a goal. The model name alone does not tell you which tools a particular interface can use. Anthropic's Claude Code documentation describes those capabilities.

Start With One

Start with one recurring task whose finished result you can inspect. If it needs a different tool or a different person to review it, that is a separate workflow to evaluate later.

Choose an AI Agent Platform by the First Job

For support, begin with Lyro or Fin and a maintained knowledge base. For phone work, define the exact call outcome and compare Vida's scoped deployment with a packaged option such as Rachel. For a custom internal workflow, consider MindStudio or n8n. For code, choose the agent that fits the repository and review process you already have.

You can prepare the first brief without logging into any tool:

1. 1

   Name one task

   Choose a repeated job such as capturing missed-call requests, preparing support answers or creating a supplier shortlist. Identify the input that starts it and the person who owns it.

2. 2

   Define a finished result

   Write down what a usable result contains: a complete intake record, a verified order answer, a sourced comparison or a code change with relevant checks. Name the missing information that should cause a handoff.

3. 3

   List the tools and source data

   Specify which knowledge base, calendar, records or files it may use. For a custom build, list the lookup and draft tools before granting any wider access.

4. 4

   Place the human check

   Decide which outputs need review and which actions require approval. Put the reviewer and destination in the brief so a paused task has somewhere to go.

5. 5

   Review cost and accepted work together

   Once configured, record completed results, corrections, review effort and billed usage. Expand only after the completed task is useful and the cost is understandable. If exceptions consume the benefit, revise the workflow before adding more jobs.

For the next working week, the useful move is a written task brief and an accountable reviewer. That gives you something concrete to compare with a maker's pricing page, instead of another broad promise about agents.

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