Literacy Project

V0.1

https://github.com/uberbestest/Reading-Practice-MVP

As AI becomes more integrated into everyday life, literacy becomes increasingly important rather than less. A world filled with AI systems still requires people to read instructions, evaluate claims, communicate clearly, understand context, and distinguish useful information from noise. If anything, those skills become more valuable as the volume of generated content increases.

At the same time, frontier language models are unusually well suited to meeting people at their current level of understanding. They can simplify language, generate practice material, explain concepts in different ways, and provide immediate feedback. While much of the public discussion focuses on increasingly complex capabilities, there is also value in applying these systems to practical problems that already exist.

Literacy felt like one of those problems. Rather than treating advanced language models as an abstract future technology, it seemed worthwhile to explore how they might help create simple, tangible tools that support a fundamental human skill.

With that in mind, I spent some time this weekend building a small reading-practice application.

The goal was deliberately narrow: display a sentence, allow individual words to be spoken aloud, allow the entire sentence to be read aloud, and provide a simple speech-recognition attempt so the learner can practice reading it back.

The current version contains only a handful of sentences and is intentionally local-first. There are no accounts, no analytics, no data collection, no chatbot, and no attempt to turn it into a platform. The objective is simply reading practice.

I think there is a tendency in software development to immediately expand useful ideas into increasingly complicated systems. Sometimes that is appropriate. Other times it is worth asking whether the original objective can be addressed with something much smaller.

Literacy seemed like a good place to test that idea.

The project is still an MVP and there is plenty of room for improvement. Better feedback, additional reading levels, expanded content, and accessibility improvements are all obvious next steps. For now, however, I wanted to start with the smallest version that could be built, used, and evaluated.

We’ll see what people find useful and go from there.