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GuideBuildingSeptember 3, 2026

Sleep Fixer: The AI Sleep Schedule Optimizer

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The full product guide and build story behind Sleep Fixer: a Flutter and Dart app with a chronotherapy-based plan engine and a Gemini-powered AI coach, shifting sleep and wake times in gradual daily steps rather than one overnight reset.

What's inside
  • Why tracking your sleep is not the same as fixing it
  • A gradual plan in 15–30 minute daily shifts, not an overnight reset
  • The Flutter, Dart, Hive and Gemini stack behind it
  • How the plan engine handles fixed wake-up times and flexible ones
  • The honest part: time-zone math, feature creep, and what they cut

Most Sleep Apps Track the Problem Instead of Fixing It

Between work, stress and screen time, plenty of people sleep and wake at irregular hours. The apps built for this mostly log what happened or play a meditation. The harder question goes unanswered: how do you move from the schedule you have to the one you want, without a drastic overnight reset you can't maintain?

Sleep Fixer is a small, focused app built around that question — and this guide is its full product story, from the idea through the architecture to what the team learned.


What It Does

You give it your current and target sleep and wake times, and it produces a gradual, science-informed adjustment plan — day by day, in shifts of roughly 15 to 30 minutes rather than one painful jump. A solidification phase helps lock the new schedule in once you reach it. It adapts to fixed wake-up times for school or work, and adds XP, levels and streaks so consistency stays engaging. A Gemini-powered coach turns the raw schedule data into conversational guidance that adjusts to your actual progress.


What's in the Guide

The full build story: a Flutter and Dart codebase running on iOS, Android and web from one source; Hive and SharedPreferences for local storage; the custom plan engine built on circadian-rhythm and chronotherapy principles; and how the Gemini layer converts schedule data into supportive coaching. Plus the honest parts — the time-zone and cross-day math that took several passes, handling fixed and flexible schedules in one algorithm, and why resisting feature creep made the product stronger. Every framework and package is linked, and the source is on GitHub.

The full guide is in the PDF.


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