“We want an AI agent” does not describe a business need on its own. It may mean customers need better answers, employees need search assistance, or a task requires successive actions across several systems. Choosing a chatbot, a fixed workflow or an agent should depend on the task, how much it varies and the consequences of an incorrect action.
Answers and actions have different requirements
A chatbot primarily offers a conversational interface. It may answer from approved content, request clarification or hand the user to a person. An agent may choose subsequent steps and tools in pursuit of a goal. Product terminology varies, so request a specific description of behaviour rather than relying on the commercial label.
In a hypothetical example, a wholesaler receives questions about available products. If users need explanations of catalogue features, a knowledge assistant may be sufficient. If the task requires checking stock, creating a draft quotation and obtaining a salesperson's approval, it involves tools and states. When the sequence is always the same, the model does not necessarily need to choose the route.
Map where uncertainty exists
Uncertainty may concern data, the objective or the steps. An ambiguously worded enquiry can require clarification without autonomous execution. A task with many possible sources may require search while retaining fixed final actions. Avoid treating every comprehension difficulty as evidence that an agent is needed.
Collect real enquiries and describe how an experienced employee handles them. Which steps repeat? Which vary by case? Where does a decision carry professional accountability? For the wholesaler, selecting an alternative product may require judgement, while checking quantities and applying an approved price list can follow clear rules. Separating those elements helps avoid giving the system freedom where it offers little benefit.
Start with the smallest useful degree of autonomy
First design the minimum solution that produces an acceptable result. It may consist of searching approved sources, a single model call for synthesis, or a fixed sequence. Add autonomy only when evidence shows that the fixed route materially limits the task. Additional complexity should purchase a demonstrable capability.
Anthropic's discussion of effective agents distinguishes predefined workflows from systems that dynamically direct their own process. This helps frame the architecture discussion. It does not establish that a particular business needs the most autonomous option, nor replace testing its own work. Keep the distinction practical by describing what the system will decide in your implementation.
Tools need narrow, reviewable scope
Define every tool as a specific capability: read availability, create a draft, submit for approval. Avoid broad access permitting arbitrary changes. Creating a quotation does not necessarily require permission to alter prices or delete customers. Tool responses should include the information needed for safe decisions.
In the hypothetical project, a quotation remains a draft until a salesperson approves it. The agent may recommend an alternative code only from an allowed set and must explain the reason. Unknown stock must not become a claim of availability. Record every state change so it is clear what was proposed, approved and sent. The operational record should make that distinction understandable to someone reviewing the case later.
Establish stopping rules before starting
Specify when the system asks for a person, stops or retries a step. A missing required identifier, conflicting sources and repeated tool failures need different responses. Set time and attempt limits per task. An endless search loop is an operational problem, rather than evidence of persistence.
Consider what happens after stopping. The human team needs a request summary, completed steps and a specific referral reason. They should not have to read the entire conversation to establish whether an external action occurred. AI Agents need this human handover route as much as their execution capability. Define the receiving team and expected next action so a handover does not become an abandoned queue.
Evaluate completion, not just polished language
Include ordinary tasks, mistaken assumptions, missing data and misleading instructions embedded in sources in the test set. Measure the correct final result, permitted actions, time and human corrections. A polite answer that created an incorrect quotation is a failure. A brief handover to a person may be exactly the correct behaviour.
Acceptance criteria may include no unapproved sending, correct retrieval of product codes, evidence for alternatives and recognition of unknown availability. Also test the owner's ability to pause the system. If the requirement proves to be mainly search, AI Knowledge may provide a simpler starting point than a full agent implementation. Keep quality criteria tied to the job the employee would otherwise perform.
Frequently asked questions about chatbots and agents
Can a chatbot use tools?
Yes. A conversational interface can call tools within a predefined workflow. What matters is who chooses the steps and which actions are permitted, rather than whether the screen resembles a chat application. The interface alone does not establish autonomy.
When is greater autonomy justified?
When the action sequence varies materially by request and testing shows better completion at an acceptable cost and control level. Variation must be substantive, rather than simply different user wording for the same work.
Should an agent send quotations directly?
Only with clear authorisation, reliable rules and an acceptable risk level. During an initial implementation, drafts with human approval help measure errors without exposing the customer to them. Any later expansion needs its own evidence.
What if no safe answer can be found?
The system should state the specific gap and refer to the appropriate person. Correct abstention is part of quality. Producing an answer in every situation should not be rewarded when evidence or permissions are insufficient.
To choose a solution around your own task, contact DIGITALNOW and begin with a limited scenario whose outcome can be checked.