Building No Longer Ends the Debate
I keep seeing a new kind of roadmap discussion. Someone proposes an idea, and before the team can argue about engineering time, a working version exists. The prototype is not ready for customers, but it is real enough to make the idea harder to dismiss.
This is useful. A team no longer needs a long specification before it can test the important assumptions. People can use the rough version, see what they misunderstood, and change the idea while it is still cheap to change.
But this also removes a familiar reason to say no. When implementation was expensive, resourcing performed some of the curation. Secondary ideas died because the team could not afford to build all of them.
Now the decision is no longer this or nothing. It is this or that. At least it should be.
Good Demos Are Hard to Kill
A prototype makes a good case for itself. It follows the main path, uses selected data, and runs with its creator nearby. Everyone can see the potential without having to deal with the conditions that make the real product difficult.
Once the demo exists, its status changes. It is no longer an idea the team might reject. It is something that appears almost finished, so the conversation becomes how to ship it instead of whether it belongs.
Each decision still looks reasonable on its own. The feature works. Someone wants it. The additional code no longer looks expensive enough to force an argument.
The damage appears when these decisions accumulate. If every useful demo becomes a feature, the product turns into a record of everything the team could build instead of an expression of what it chose.
Useful Features Can Still Make a Bad System
Imagine a support product with one assistant that drafts a reply, another that scores the conversation, and a third that recommends the next action. Each prototype can perform its task well. Together they can leave the employee unsure which output to trust, which step comes first, and who is responsible for the final decision.
Adding more capable parts did not create a more complete product. It created several competing versions of how the work should happen.
A complete product does not need a feature for every task. Its parts need to agree on the same model of the work. The interface, automation, permissions, and human responsibilities should reinforce one another instead of exposing every idea the team was able to implement.
Without that coherence, the product can keep gaining functionality while feeling less finished after every release.
This Is Product Slop
We use AI slop to describe content that was generated but never meaningfully edited. Product slop is the same failure at the system level. It can be well designed, technically sound, and full of features that users requested.
The slop is the missing decision.
The team never chose which workflow should dominate, which feature should replace an older one, or which useful prototype should disappear. Everything survived because nothing was bad enough to reject and building it was no longer painful enough to force the choice.
This is where taste becomes practical. Taste is not adding polish after implementation. It is knowing what the product is trying to do well enough to reject ideas that pull it away from that purpose.
Prototypes should make that judgment easier. They let the team compare real alternatives instead of debating imagined ones. But some prototypes have to teach the team something and then die. If they all graduate into the product, the experiment never ended.
The Remaining Idea Still Has to Become Real
Curation is only half of the work. The idea that belongs still has to become dependable.
The support assistant that worked in a demo now has to handle incomplete histories, conflicting customer records, model changes, and people with different access. The team has to decide which outputs can trigger action, how uncertainty appears, and who owns a mistake when the system is wrong.
This is not polish around an otherwise finished feature. These decisions define what the product is allowed to do. A demo proves that one path can work. A product decides what happens when the conditions stop being convenient.
Agents can help implement those decisions. They cannot decide which failure is acceptable, which promise the company is making, or whether the feature belongs in the first place.
AI gives teams more things they can build. It does not give the product an editor.
Speed is useful when it helps the important choices arrive sooner. If it lets the team avoid choosing, the product fills with unfinished decisions.