I build custom AI agents that help complete defined business tasks using approved tools and information. Give your team an assistant that can prepare useful actions, follow clear boundaries and ask for approval before making important changes.
Custom AI Agents
An agent can choose between permitted steps to work towards a goal. That flexibility needs limits: bounded execution, validated tool inputs and clear conditions for stopping or asking for help.
Prepare customer handovers, assemble internal reports or gather information for an operational task. Define the expected result and the evidence needed to support it.
Expose only the functions a task requires, such as searching permitted records or preparing a draft update. Keep authorisation in application code rather than relying on instructions to the model.
Show staff exactly what an agent proposes to change or send. Require approval for agreed actions and check that approval still matches the proposed payload before execution.
Record tool calls, outcomes and errors at an appropriate level. Limit execution steps, time and spend so an agent cannot continue indefinitely when it cannot complete a task.
Delivery and controls
I start with a narrow scope and representative examples. The agent should be useful when a task is straightforward and predictable about when it needs a person.
Agree allowed inputs, available tools, success criteria and prohibited actions. Identify when a fixed workflow would be simpler and more reliable than an agent.
Validate arguments, enforce permissions and treat retrieved text as data. Untrusted documents or messages must not be allowed to grant access or authorise an action.
Review ambiguous requests, unavailable tools and misleading source material. Measure successful completion alongside incorrect actions, review effort and escalation behaviour.
Begin with draft-only or read-only tasks where appropriate. Increase access only after reviewing results and agreeing operational ownership, budgets and recovery procedures.
Example project
An illustrative task for a controlled agent that gathers information and prepares a handover, while staff retain responsibility for the final result.
Search permitted account records and recent task updates. Stop and ask for clarification if the customer or scope is unclear.
Summarise outstanding work, identify missing details and link to the supporting records. Prepare suggested follow-up tasks.
Present the draft and proposed tasks to the account owner. Create only the tasks that are explicitly approved.
Tell me what happens today, which systems are involved and what a useful improvement would look like.
Custom AI Agents FAQ
A fixed workflow follows predefined steps. An agent can select from permitted tools or steps to pursue a goal. Many projects need only a fixed workflow; an agent is useful when controlled flexibility provides a clear benefit.
It can be designed to perform limited, low-impact actions automatically. We agree the boundaries first. Important changes can require explicit approval, with application permissions enforced independently of the model.
Use narrow tools, input validation, permission checks, approval gates and limits on steps and spend. Evaluate realistic failure cases and keep a manual recovery path. These controls reduce risk but do not make model behaviour infallible.
Usually, a single focused workflow or agent is the sensible starting point. Additional agents add coordination and debugging work and should only be introduced when the task justifies them.
Yes, where supported integration methods and suitable permissions are available. Access should be scoped to the specific task and user, with sensitive or irreversible operations protected by additional checks.
