Rapport · Product case study
The best feature was the one I stopped.
AI-written messages looked like the next obvious feature. The more useful problem was deciding which customer follow-ups were still real.
The decisions
Three decisions, the reasoning behind each, and what changed as a result.
Prioritization, in practiceFilm example
The untested assumption
A faster message still needs a useful reason to send it.
Planned featureAI-drafted messages
Assumes writing the message is the bottleneck.
Removed from the roadmapWorkflow findingWhich follow-ups are real?
People could already contact customers. The list was bringing back stale work.
Fix this dependency firstValidate the problem before investing in another product surface.
How it works
A quick guide to the interactive flow on this page.
Dynamic contentClick each step to see a different part of the story.
The outcome
Attention went to useful follow-ups.
Automated message drafting left the roadmap. The follow-up logic was reframed around context so resolved work would stop appearing as outstanding.