01 An agent builder's first question: does this need an agent?
Sebastian Mueller is a founding partner of MING Labs.[S5] He builds AI agents, yet in a recent public post he described many requests for them as the wrong fit. Some were fixed rules dressed up as agent projects. Others were occasional assignments that a person could handle with an AI tool.[S1]
That is a useful pause before approving a project. Take a task as ordinary as moving an approved order into another system. If the trigger, fields and checks are known, the team can specify the path. Giving a model freedom to choose that path adds a decision the job may not need.
Now consider a research task. The first document may answer the question, contradict another source or reveal a gap that needs a different search. The next step depends on what was found. That is a reason to investigate an agent. It still leaves a business question: will the extra flexibility produce work your team can use?
02 Choose the approach by how the next step gets decided
Anthropic draws the architectural distinction this way: workflows follow predefined code paths; agents let a model direct the process and tool use dynamically. A workflow can contain AI. An agent can handle a one-off task. The difference is who or what selects the next step.[S2]
The table turns that distinction and Sebastian’s operating advice into a starting point for a team decision. These are options to test, not a ranking of performance.[S1]
| The work | Start by considering | What to check |
|---|---|---|
| Known steps and explicit rules | A fixed workflow, with AI inside a step if useful | Can rules and validation cover the cases and route exceptions? |
| Occasional, person-led assignments | A person using an existing AI tool | Would a maintained agent role add enough value to justify its upkeep? |
| Recurring work where findings change the route | A bounded agent trial | Can it choose useful next steps, produce a checkable result and hand over safely? |
Many useful systems combine these approaches. For example, a fixed workflow might collect documents, an agent might investigate an unresolved question, and a person might approve the result. Define the boundary around the part that needs judgment rather than granting the whole process autonomy.
03 The busy queue may hide the better starting point
Choosing the technology comes after choosing the right work. Sebastian describes a technical-support team receiving about 2,500 calls a month. The apparent opportunity was to help answer the calls. But the people closest to the work pointed upstream: salespeople were forwarding questions they could not answer themselves.[S3]
The proposed alternative was to help those salespeople earlier. That is a hypothesis about where support belongs, not a measured reduction in calls. To test it, classify the forwarded questions and establish which knowledge gaps cause them. Otherwise, a faster queue could conceal an unchanged problem.
A separate scoping account describes a proposed agent overlapping with both an existing product and an internal build. Sebastian suggested investigating markets that had no research coverage instead.[S4] The lesson for a new project is to check what already exists and who would use additional coverage. An empty process alone does not establish a valuable opportunity.
04 Before the agent runs alone, name who takes over
In a follow-up comment, Sebastian adds a sharper test: who is responsible for the exception? Work can recur and have a written procedure, yet still have no clear person to resolve the awkward cases.[S1] A standing agent role needs that handover to be explicit.
For a research agent, the boundary might be: collect sources and prepare a draft; flag conflicting evidence; let the account lead decide what can be sent. This is an illustrative role boundary, not a reported deployment. Write the equivalent for your own task before choosing tools.
- Name the owner. Identify who accepts the result and who covers their absence.
- Define a usable result. State what the recipient must be able to do with it and how they check it.
- Set the stopping point. Specify what happens when evidence is missing, access fails or the task exceeds its limits.
Our guide to accountability for an agent’s mistakes covers the responsibility question in more depth. The ABC Framework helps separate the work people keep, the work they share and the operations they can delegate.
05 Test the same work before making the role permanent
Choose a bounded set of real tasks, including ordinary cases and exceptions. Compare the candidate approach with the simplest credible alternative using the same inputs, access and quality standard. Record usable results, human review, corrections and failures. Include setup and ongoing ownership in the budget; our agent operating-cost example shows why those hours matter.
Agree the decision rule before the trial: what improvement would justify keeping this system, and what result would make you simplify or stop? The sources here cannot supply a universal threshold. That depends on the job, the consequences of errors and the alternative you already have.
A good first agent has a clear job, a checkable result and a person to call when the work stops being routine.
Bring MING Labs one recurring task, a few representative inputs and the person who currently owns the outcome. Our Hybrid Organisation work starts with designing the role and its place in the team. Talk to us about whether that task needs an agent .
What this guide establishes
- A decision method: MING’s editorial synthesis of published practitioner accounts and technical guidance, reviewed on 2 October 2026. No matched agent-versus-workflow trial or general cost advantage is claimed.
- The support example: about 2,500 calls per month is Sebastian’s reported workload. Raw logs and the measurement period are not public. The upstream intervention is a proposal, with no measured reduction reported.[S3]
- The market example: a proposed change of focus, with no measured commercial outcome. The post’s speculative improvement figure is not used here.[S4]
- Source dates: LinkedIn displayed rounded ages for the three posts. Their source records show the retrieval date rather than an invented publication day.
