Compare rules-based workflows, knowledge assistants, tool-using agents, and custom applications. Then decide who should build and operate the result.
AI agent, automation, or a custom tool?
Start with the task's uncertainty. Known rules suit automation; questions about documents may need knowledge retrieval; a changing sequence of tool calls may justify an agent. A custom application provides the working interface and can contain any of these. The choices overlap: one workflow can combine rules, AI preparation, and human approval.
Rules-based automation
When it fits
The trigger, conditions, and next steps can be written down in advance.
What it needs
Structured fields, agreed rules, and reliable system connections.
Who decides
Automate agreed routine steps; route exceptions and approval decisions to their owners.
What to test
Try missing fields, repeated requests, and an unavailable destination. Check safe reruns.
Department and amount determine the reviewer. Start with rules-based automation. If requests arrive as free text, add AI extraction before field validation. Keep incomplete requests in a review queue; purchasing approval remains a separate step.
The employee needs a source-supported answer. Start with knowledge retrieval and version checks. The assistant should expose an uncovered exception and refer it to the policy owner. Booking travel is a different scope with different permissions.
The next lookup depends on what the account record and policy say. A limited agent may help gather context; fixed rules can still govern escalation. Add a custom review screen only if the existing help desk cannot support the journey.
A useful outline names the work, the owner, and the result worth testing. Download an editable Markdown template, or use the questions below in your own document.
Free to download. No email required. Keep credentials and confidential records out of an initial brief.
Once the approach is clear, compare the people and tools that can deliver it.
Option 01
Use the software you already have
When it fits
Best when the workflow is standard and existing features cover it.
What it offers
A configuration review or better operating process may solve the problem without a custom build.
What to check
Confirm integration limits, permissions, and whether the team will actually use the feature.
Option 02
Build with your internal team
When it fits
Best when product ownership and engineering capacity already exist.
What it offers
Your team retains close context and can evolve the system alongside the business.
What to check
Account for competing priorities, evaluation work, maintenance, and operational support.
Option 03
Use a low-code or automation platform
When it fits
Best when the process fits available connectors and clear rules.
What it offers
A focused workflow can be configured without creating a whole application.
What to check
Check failure handling, usage costs, permission boundaries, vendor limits, and who maintains it.
Option 04
Scope a build with Agents Autonomous
When it fits
Best when the workflow needs tailored AI, integration, evaluation, or implementation help.
What it offers
The proposed engagement joins problem definition, a bounded build, realistic tests, and a practical handoff.
What to check
Agree deliverables, exclusions, timing, ownership, and support.
A useful decision rule
Buy the standard part. Build the specific part.
If the workflow is common and the tools fit, configure them. If a particular data, interaction, or decision boundary makes the task different, investigate a focused custom scope. If the need is still unclear, start with discovery rather than a large commitment.
A few useful answers
Before we begin.
Do we need an AI agent for every automation?+
No. When agreed rules can determine the steps, a conventional workflow may be easier to inspect and operate. Add AI where interpreting variable information helps; add agent-controlled steps only when the task needs them.
Is a chatbot the same as an AI agent?+
Chat describes the interface. Behind it might be document search, a fixed workflow, or an agent choosing among tools. Ask what it can read, which actions it can take, and how those permissions are enforced.
How do we choose when several approaches could work?+
Try the smallest plausible approach on the same representative cases. Compare the accepted outputs, review effort, failures, and operating cost. A more complex design needs evidence that its added capability is useful.
Do we have to choose a route before contacting you?+
No. Describe the task and the existing tools. AI strategy and audits can help compare practical options.
Is Agents Autonomous cheaper or faster than an internal team?+
Cost, timing, context, and maintenance depend on the scope and resources.
A useful conversation starts here
Where does the work get stuck?
Bring the options you are considering and the task they need to solve.
