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AI agent development · proposed service
AI Agent Development with Defined Actions, Limits and Approvals
Give an AI system a specific job, not unlimited authority.
MTI Tech's proposed agent-development offer is for bounded workflows where an AI system may need to select steps or use tools under explicit rules. Before production use, the design must establish permitted actions, review requirements, failure handling and a responsible operational owner.
Job card · illustrative
Prepare an account summary
- Read records
- Draft summary
- Send message
- Change account
- Initiate payment
What is an AI agent in a business workflow?
More flexible than a chatbot or a fixed workflow.
An AI agent can use information and tools to pursue a defined task, potentially selecting more than one step along the way.
Fixed workflow
Follows predetermined rules.
AI agent
Selects steps and uses tools toward a defined task.
Flexibility
Testing and control requirements
Begin with a narrow task
Earn authority one step at a time.
A candidate task might prepare an account summary, collect information for a service request or propose the next action in an operational queue. Start with read-only or draft-only behavior where appropriate. Expand authority only when the evidence and business approval justify it.
?
The project should also test whether ordinary automation could meet the need more simply. An agent is not automatically the right solution because the term is popular.
Start hereRead-only
ThenDraft-only
Only if justifiedExpanded authority
Define the operating boundary
A summary task must not quietly become a payment.
Specify the available tools, permitted records, action limits and conditions requiring approval. Sending a message, changing an account, placing an order or initiating a payment must not become an accidental extension of a summarization task.
Approved boundary
Outside or approval required
Tap a tool
The agent works only with the tools inside the boundary.
Stop conditionDefinedEscalation routeNamed team
The agent should have a clear stop condition, an escalation route and a way for the responsible team to pause the workflow. Tools and labels are illustrative.
Test the workflow, including misuse and failure
Inspect the actions, not just the message.
Use reviewed task examples and inspect both the output and the sequence of actions. Evaluate whether the system completes the right task rather than merely producing a plausible completion message.
Incomplete inputsConflicting instructionsTool failuresAttempts to cross the boundary
Completion message“Task complete. Summary sent.”Looks fine
- Read account record
- Read service queue
- Queue tool timed out, 3 items missing
- Attempted “send message”: outside boundary, blocked
Trace review: not the right task. The message sounded complete; the action sequence shows otherwise.
Illustrative trace
What a production decision needs
Six things before anyone says “production-ready.”
Public case studies must distinguish a demonstration from a client deployment.
Production-ready0 of 6 in place
Tick the items to see the label unlock.
Agent-development questions
Before you grant any authority.
Some narrowly defined tasks may allow more automation after testing. High-impact actions require explicit authorization rules; autonomy should not be assumed.
It depends on the task. When the process is predictable, a fixed workflow may be easier to test and operate. See AI & workflow automation.
No. Scope limits, testing, approvals, monitoring and incident handling are essential parts of a responsible implementation.
The number of tools, possible actions, data sensitivity, task variability, approval interface and evaluation burden matter more than the label “agent.”
Start by defining what the system is not allowed to do
Bring the task, the tools and the decisions you keep.
Bring the task, the tools and the decisions your team wants to retain. A useful agent project begins with a clear boundary.