Software should earn its keep
There is a category of software that is spectacular in a fifteen-minute demonstration and exhausting to use for fifteen hours. The demo is tight. The narrative is clean. The features that look impressive on a screen recording are front and centre. The features that would help you finish a real task on a hard Tuesday afternoon are somewhere in the settings menu, or missing entirely.
We have a name for this in our heads: demo-ware. It earns attention without earning its keep.
The demonstration problem
The problem with optimising for demos is subtle. Demos reward breadth, novelty, and visual fluency. They punish depth, reliability, and the invisible competence of a tool that just works without announcing itself. A live demo never shows what happens when a task is long, ambiguous, or halfway done at the end of the day. It never shows the twentieth time you use a feature, only the first.
Real work is not the first time. Real work is the hundredth time. It is the task you started yesterday, the context you need to restore, the result that has to be in a form your colleague can use, the citation that has to hold up when someone checks it. Software that earns its keep is built for that version of the work, not the demo version.
What "finishing" actually requires
Finishing work is harder than generating output. A tool can produce a draft; finishing the draft means the draft is accurate, attributed, scoped correctly, and in a format someone can act on. A tool can surface a data point; finishing the analysis means the data point sits in context, the contradictions are surfaced, and the conclusion is defensible.
The gap between output and finished work is where most AI tools stop short. They get you to a promising state and then hand you a half-built thing that requires significant effort to cross the finish line. The tool's contribution is impressive. The last mile is yours.
We think about that last mile more than anything else. Not because we are pessimistic about what AI can do, but because we believe a tool that helps you close the gap is categorically more useful than a tool that opens the gap with a flourish and leaves.
Reliability is a feature that doesn't show up in screenshots
There is a class of features that make products trustworthy and almost never appear in a product launch. Consistent formatting. Accurate citations. Behaviour that is the same on the fiftieth use as on the fifth. A result you can hand to a colleague without a disclaimer.
These things are not exciting to write about. They do not generate a reaction when you demonstrate them. But they are what separates a tool someone uses every day from a tool someone uses once, admires, and puts down.
When we make decisions about what to build and what to leave out, we ask a version of the same question: does this help someone finish something? Not "does this expand what askFinz can claim to do?" Not "does this make the product look more sophisticated?" Does it help you close the tab and move on, confident the work is done?
The right relationship between tool and user
A tool that earns its keep knows its place. It does its part of the work — the retrieval, the synthesis, the structuring, the drafting — and delivers something you can use rather than something you have to manage. It does not require you to become an expert in prompting or orchestration. It does not produce a wall of output that you have to edit down to the useful fraction.
The right relationship is not: the tool is impressive and you are the audience. It is: you have something to accomplish and the tool is genuinely useful in accomplishing it.
That is what we are building toward. Not software that earns admiration. Software that earns its place in your day.
Explore what the platform looks like in practice.