A daily home practice app for a single kid, one target sound, evidence-based methodology. Four AI agents built it. One human orchestrated.
Speech therapy works in the office. The harder problem is carryover, making new speech patterns stick across the other 166 hours of the week. This app runs the evidence-backed carryover protocol at home. That is what it does. The interesting part is how it got here.
Research, product design, coordination, and implementation each had a dedicated AI role, with me reviewing the work. The result is a concrete example of what AI-to-AI product delivery can look like when the research, the spec, and the build each have a clear owner.
This started as an experiment in seeing what my agents could do together. The work flowed through a repeatable AI build workflow with clear scopes, reviewable handoffs, and human oversight.
Each daily session follows a fixed protocol. The sequence is not configurable. It reflects the evidence base Harper compiled before a line of code was written. Advancement is locked to clinical thresholds. Escalation triggers fire automatically when patterns suggest the speech-language pathologist needs to weigh in.
Depth of work that a traditional small-team build would have cut for scope. The agents did it because their scopes were clear and their handoffs were cheap.
7
Research articles
Rex compiled into the LLM Wiki.
10
Academic sources
Preston 2020 (ASHA), Sjolie 2016, Raaz 2025 RCT, Pritchard 2025, Marshalla, Kim 2025 ASR, ASHA Leader 2018, plus three more.
8
Difficulty levels
Isolation through generalization.
5
Escalation triggers
Auto-fire to flag the clinician.
4
Self-monitoring tiers
Carryover keystone, per Marshalla.
0
Human code lines
Written by me. The four agents owned the build.
Stack
Vite, React, TypeScript. No backend.
Vite + React + TypeScript. Pure browser localStorage, no database, no accounts. The goal was to keep the first version as simple as possible: enough structure for the agents to build together, and enough product to test with my child at home.
It can grow if it needs to: add a backend, accounts, richer reporting, or a more formal content workflow later. For now, the important thing is a useful local app with clear clinical rules, tested progression logic, and a small surface area.
Status
In active daily use.
Core drill engine and session flow are complete. Daily sessions are running at home. Audio synthesis is in validation. A test set of clips is being evaluated before the full batch is generated.
Use
Private household tool.
This is not a public product or a shared app. It is a focused household tool built to support one child's daily practice and to learn how my agents collaborate across research, specification, coordination, and implementation.