AI AGENT DEVELOPMENT
AI agents with a clear job and controlled actions.
An AI agent connects reasoning with the tools needed to carry out a task. I help businesses in Dubai, the UAE and the UK scope agents around a defined workflow, with clear limits on what they can read, decide and change.
Potential starting points include collecting research for review, preparing support responses, organising incoming requests or assisting a team with repetitive operations. Each needs a defined outcome, an owner and a way to recognise when human input is needed.
Design the workflow before the agent
We map the goal, available information, tools and stopping conditions. Some tasks need one agent with a few tools; others benefit from separate research and review stages. A multi-agent design is worthwhile only when the extra coordination helps the task.
- A workflow map with explicit inputs, outputs and ownership.
- Agreed tool connections and permission boundaries.
- Approval points for actions such as sending or updating records.
- Traceable runs, error handling and task-specific evaluation.
Make progress visible
A person using the system should be able to understand its current step, inspect a proposed action and take over when needed. The implementation can include run history, cited research, structured outputs and a review queue, depending on the agreed scope. Time limits and tool-call limits help keep execution bounded.
Prepare examples and boundaries
Bring several real tasks, successful outcomes and cases that should be rejected or escalated. We also need a workflow owner, access to approved tools and clarity on sensitive data. Testing should include unavailable tools, ambiguous instructions and incomplete information before the agent is given wider access.
BEFORE WE BUILD
Questions,
made clearer.
Can an AI agent send emails or change business records?
It can if the connected tools allow it. The design should define the allowed actions, required permissions and which changes need approval before execution.
Does every project need several agents?
No. A simpler workflow is usually easier to inspect and maintain. Separate agents are considered when distinct roles improve the result enough to justify additional complexity.
How do you evaluate an agent?
We test representative tasks against agreed outcomes, including unsuccessful runs. Useful measures include task completion, approval accuracy, tool errors, response time and cost per run.