Agentic AI
Agents that can be run, stopped and explained.
An agent is software that can take steps toward a goal, calling tools inside limits you set. Dynacore designs those limits with the workflow, the identity model and the record of what the agent did.
From a pilot to a system you can run
A pilot shows that a model can attempt a task. Production asks a different set of questions: who owns the outcome, which tools the agent may call, what data is allowed into the prompt, how you know the answers are good enough, and how a person challenges a bad one.
We work with the teams who will live with those answers: the business owner, the security and identity function, the people who run the systems of record, and the infrastructure group if the agent needs dedicated compute.
What the practice covers
- Use-case selection, including the cases that should stay a deterministic workflow.
- Agent and tool design, with an allow-list rather than an open set of actions.
- Orchestration across steps, people and systems, including approval where the impact warrants it.
- Retrieval over sources you have approved, with a record of which source was used.
- Evaluation before go-live, and monitoring once the agent is in the path of real work.
- Guardrails: identity, data boundaries, rate and cost limits, and a kill switch.
Integration with enterprise systems is the neighbouring practice. AI integration and automation is where the agent meets the workflow.
Governance, aligned to Australian guidance
The Australian Government’s Guidance for AI Adoption, published in October 2025, sets six practices for responsible adoption. It evolves the Voluntary AI Safety Standard and points back to Australia’s AI Ethics Principles. The guidance is voluntary. It is a management aid. It is a certification we do not claim, for ourselves or for clients.
ISO/IEC 42001:2023 is the international management-system standard for AI. Organisations can align an operating model to it. Alignment is a design choice. Dynacore does not claim certification.
1. Decide who is accountable
A senior owner for the program, and a named owner for each agent that can touch a real system.
2. Understand impacts and plan accordingly
Who can be affected, and a channel to challenge an outcome that matches the impact.
3. Measure and manage risks
Tool access, data leaving the boundary, and actions that are hard to undo.
4. Share essential information
People can tell when they are dealing with an agent, in language a customer or colleague can follow.
5. Test and monitor
An evaluation set before go-live, and logs of prompts, tool calls and outcomes after.
6. Maintain human control
A person can stop the agent, and a path remains that does not depend on it.
The six headings are the government’s. The sentences under them are our planning shorthand for agent programs. Read the source before you adopt the wording into policy.
A production gate
Before an agent is allowed into a real process, we expect the pack to include:
- A named owner and a description of the decision the agent may influence
- The tools it may call, the identity it uses, and the data it may see
- An evaluation set and the threshold for going live
- Logging, a rollback, and a contestability path for people affected
- A privacy check where personal information is in prompts, logs or tool outputs
The longer version is the briefing From an agent pilot to a system you can run.
Answers
Direct answers
Short statements for the questions this page is here to settle.
What is an agent in an enterprise system?
An agent is software that can take steps toward a goal, calling tools inside limits the organisation sets. Production needs an owner, an allow-list, an evaluation, a record of what ran, and a way for a person to challenge or stop an outcome.
How should agentic AI move from pilot to production?
Treat the pilot as a demonstration and the production system as a different object. Name an owner, restrict the tools and data, write the evaluation threshold, and keep a path that does not depend on the agent.
Brief us on the agent
Tell us the process, the systems it would touch, and who owns the outcome.