How to Turn a Technical Feature Into a Story Without Dumbing It Down
A feature list leaves out the work it supports. A before-and-after example of explaining a technical feature so both the engineer and finance can follow.

Suppose an engineer is about to remove an old field from a billing database. Finance needs its monthly revenue report tomorrow. The field looks unused, but one of the queries behind that report still relies on it. Delete the field, and the report could fail when finance tries to run it.
A software company has a feature that could help the engineer find that connection. On its website, the feature appears under “Column-level lineage.”
An engineer may know exactly what the term means. Someone in finance probably needs an explanation. Either reader would benefit from seeing why the feature matters in this particular situation, including what happens after the software finds the connection.
The product and workflow in this example are fictional.
What the feature list leaves out
Here is a technically specific description of the product:
Before |
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Our platform provides column-level lineage by parsing supported SQL view definitions. It displays downstream view dependencies and the last successful scan time, with an on-demand rescan option. Coverage excludes dynamically generated SQL and external spreadsheet formulas. Users must review those dependencies separately and make any required changes themselves. |
This tells a technical evaluator what to investigate. It gives a less familiar reader several terms to look up before they can even consider the product.
It also leaves the work itself out of the explanation. Why is someone tracing a database field? What are they worried about breaking? Once they have the map, what do they do with it?
The people who built the feature may have those answers ready. Their prospective customer has to supply them alone. I would bring the engineer’s situation into the copy, keeping the same capabilities and limits.
After |
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Before deleting an old field from your billing database, check whether the monthly revenue report still needs it.Your engineer opens the platform’s dependency map to see which SQL views use the field. A view is a saved query that pulls data from the database; in this case, one supplies the figures for finance’s report. The platform builds the map by parsing the view definitions it supports, tracing dependencies down to individual columns. The engineer checks the last successful scan time and requests a fresh scan. The report’s view still refers to the old field, so the engineer holds off on deleting it and arranges the view’s update with finance. Your team still needs to review dynamically generated SQL and external spreadsheet formulas separately, because those sit outside the map’s coverage. The platform shows the dependencies; your team makes the changes. |
Keep the finance report in the story
The report gives someone outside the data team a way into the subject. They can follow what the engineer is trying to prevent without already knowing how database dependencies work. A technical reader can examine how the platform identifies those dependencies and where its coverage ends.
That matters when an engineer has to explain a proposed purchase to finance. “It could help us find a report that still depends on a field we’re about to delete” is a conversation finance can join. They may still decide that the existing manual check is sufficient. At least they are assessing a use of the product they recognize.
Once the report is in the explanation, I know which technical details to keep. The scan time stays because the engineer needs to know whether the map reflects recent changes. The column-level detail matters because the planned deletion concerns one field.
Finding the dependency doesn’t fix the report
The tempting ending is that the software saves the report, finance gets its figures, and everyone gets on with their day. That would skip the work still required.
In our example, the engineer has found a dependency and changed the plan. Someone still has to update the query and check that the report works. A writer who turns that into “prevent reporting failures” has made a much larger promise than the feature description supports.
I would stop the story at the point where we can explain the product’s contribution. The engineer knows which supported view needs attention before the field is removed. That is useful enough to describe plainly. Claims about fewer reporting incidents or hours saved would need evidence from actual use.
A polished ending is especially risky when it makes a customer’s responsibilities disappear. If the product only identifies a problem, the story has to leave someone responsible for fixing it. Otherwise the sales conversation and the implementation conversation begin with different expectations.
Ask to see the customer’s work
For a real product, I would ask the team to walk me through a recent use of the feature. I’d want to see what prompted someone to open it and what they did after seeing the result. If the conversation stays at “they get better insights,” I’d ask to look at the output together. Which part would the customer act on?
That conversation may produce an ordinary story. An engineer delays a database change. Finance checks a report before a field disappears. There is no need to manufacture a crisis when the work already has consequences the buyer recognizes.
Try this with one feature on your website. Write the paragraph you would use to explain it to a prospective customer, then read it aloud. Pay attention to the places where you would naturally stop to give an example. Those may be the connections your current copy expects the reader to make alone.
If you’re getting stuck, send the feature description to angelica@sirotinventures.com and tell me who it is for. At Sirotin Ventures, we work with your team to understand the product and write an explanation your customers can use.

Written by
Angelica Sirotin
CEO, Sirotin Ventures
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