Aim: Screensaver and Custom App
Kindle sitting unused, wanted to see whether AI could help find a new use for it. Goal: create custom app covering range of uses, controlled by AI agent on MacBook. Started with small goal: use own image as Kindle screensaver. Once that worked, asked agent to build app that could cycle through collection of photos.
Trying Multiple AI Models
Used Codex and T3 Code on Mac to work with coding agents. First tried GPT-5.6 Sol with reasoning effort set to Extra High. wrote code to connect to the Kindle but could not resolve error that prevented it from storing data on the device. Then tried Fable 5.1 and Opus 5.5, but Anthropic's cybersecurity safeguards blocked each attempt after two prompts. Finally tried GPT-6 Astra with reasoning effort set to High. able to jailbreak the Kindle.
Jailbreak Through SpiderCat
Used existing jailbreak code from SpiderCat released by sparklerfish and the KindleModding community, and built custom tools called KindleCTL around it. What we built: tools to send commands from my Mac, transfer files, and investigate errors on the Kindle. What broke: launcher crashed before it could start. Traced that to compatibility issue with the Kindle's older system software and fixed how the launcher was built. How we checked: connected with administrator access, transferred files both ways, and displayed text. Later verified that access still worked after a reboot.
Feedback Loop Enables Autopilot
Initially the agent could connect to the Kindle but could not display data. To debug this, it asked me for pictures of the Kindle's screen. I took photos with my phone and shared them with the agent on my Mac. This was becoming tedious. Since the agent was connected to the Kindle, wondered why it could not get this information itself. Asked it to set up a feedback loop so it could access logs without me having to share screenshots. The agent set up a persistent diagnostic connection so it could collect errors and test fixes without asking me to download and reopen a package each time. Later we added remote screen captures so it could also inspect what the Kindle was displaying. This was a turning point that let the agent continue implementing changes on autopilot. Its reasoning traces showed it figuring out which folders survived a restart and which could store external data. I was surprised the agent had not suggested this on its own. Once I asked for a feedback loop, it set one up and could test fixes without my help.
Slideshow With Clean Transitions
Most of the code was written in Python. The Kindle's launcher and slideshow were written in C, with shell scripts handling installation and device controls. With the connection working, asked the agent to try a small test first: transfer an image and set it as the Kindle's screensaver. Checked that the image appeared correctly and that waking the Kindle brought back the normal Home screen. Once that worked, asked for the slideshow app. Asked the agent for a looping slideshow of ten photos, with an Exit button. Each photo would fit the screen while keeping its original aspect ratio. The slides were changing, but the transitions were not smooth, so I asked the agent to look into it. With the feedback loop already in place, it investigated the issue and used the Kindle's built-in screen refresh mechanism to clear the previous image after each slide change. The screen captures showed complete images, but they could not reveal traces left on the physical display. After the refresh change, I checked the Kindle and confirmed that each photo looked clean. I customized how long each photo stays on screen and the brightness level. If the Kindle goes to sleep, the slideshow picks up where it left off when it wakes. For now, I use my Mac to change the photos and slideshow timing. The photos stay stored on the Kindle, so the slideshow works without Wi‑Fi. In the future we could add controls to change the slideshow timing on the Kindle and send photos directly from a phone or another device.
What Was Learned
Next time I would set up the feedback loop from the start so the agent could read logs, inspect screen captures, and test fixes on the device. The Kindle now sits on our wooden shelf, where we use it every day as a photo frame. I started because I was curious about what AI could help me do with an unused device. Now I have an app for my photos that works the way I asked, plus the tools to keep experimenting with the Kindle.