Custom Agents
Map data sources before building the custom agent
The data source map is the difference between a reliable agent and a guessing machine.
By JirakJ
5 min read
I do not read this as a tooling problem first. I read it as a sign that the agent is expected to answer questions without a clear source hierarchy.
If the buyer cannot name the reviewer, the project is not ready for autonomy. That is why the early work should be concrete enough that teams connecting agents to internal systems can argue with it.
A small field test
Take one recent example of this workflow and replay it from request to finished output. The weak point will usually match the complaint: the agent is expected to answer questions without a clear source hierarchy.
Where the human stays
The human work is deciding what good means, what risk is acceptable and when a draft is not good enough. That judgment should be designed into the flow, not left to chance.
What to change first
Rank systems by authority, freshness, access and review requirements. Do that before choosing a platform or adding another automation layer.
What I would keep
Keep the data source map. It becomes the reference point when the team forgets why the workflow was changed in the first place.
Monday morning checklist
- • Turn the next meeting into a decision log instead of another broad AI discussion.
- • Write down the artifact that would make the work reviewable: in this case, a data source map.
- • Decide who owns the next version if the first version works.
- • Mark the part of the workflow where human judgment must stay visible.
If this sounds familiar
Start with one workflow. FlowMason AI can map it, identify the right intervention, and define whether the next step should be a prototype, agent, documentation pipeline or delivery system.
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