I Built a Storage Experiment That Represented 3 TB in 134.6 MiB. Here's What Actually Happened.

Bohdi, founder of Bamboozled Labs, built Hermione Storage, a content-addressed system that deterministically reconstructs related version histories from a smaller authoritative foundation, representing 3,000,009,359,993 bytes of logical Git-derived history with 141,124,743 bytes of retained durable state — a 99.9952959% reduction at roughly 21,258:1, with all 29,460 frozen ordered roots verified. An isolated Android integration passed 100/100 exact-return trials across ten synthetic file populations but was graded PASS_WITH_LIMITS, and testing surfaced a real corruption-cleanup defect where a failed restore left an unwanted destination placeholder. The founder states the enterprise effort Hermione-S is not enterprise-qualified, with only 2 of 19 qualification rows met.

I'm Bohdi, founder of Bamboozled Labs in Nebraska. I'm a dad, a former welder, an ethical hacker, and a human + AI coder with ADHD. I didn't come into software engineering through the traditional route. I came into it because I see problems, get curious, and have a really hard time leaving interesting ideas alone. 🤣 And one of those ideas became Hermione Storage . Most people understand compression. You take a file, run it through ZIP or another compression algorithm, and represent its contents using fewer bytes. When you decompress it, you recover the original. Hermione explores a related but different question: What information actually needs to remain stored, and what can be deterministically reconstructed from a smaller authoritative foundation? Imagine having thousands of versions of a book. Instead of storing every complete book independently, you preserve the unique information, shared information, and reconstruction instructions necessary to recover each version exactly. The important requirement isn't just making the stored representation smaller. It's proving that the original information comes back. Hermione investigates content-addressed storage, shared information, deterministic reconstruction, integrity verification, and evidence-backed storage accounting. Conventional compression can still be part of the system. In a bounded experiment using highly related, public Git-derived history, Hermione produced this result: | Measurement | Result | |---|---| | Logical data represented | 3,000,009,359,993 bytes | | Retained durable data | 141,124,743 bytes | | Reduction | 99.9952959% | | Representation ratio | Approximately 21,258:1 | | Frozen ordered roots verified | 29,460 / 29,460 | That's approximately 3 TB of logical history represented by 134.6 MiB of retained durable state . The population was highly related version history, not 3 TB of independent random data. That's a huge distinction. This result does not prove that Hermione can reduce arbitrary movies, games, encrypted files, or unrelated user data by the same percentage. And it does not establish enterprise readiness. The experiment is interesting because of what it demonstrated within its defined population, not because of what somebody might imagine it means everywhere else. We also built an isolated integration between Hermione and an Android launcher called Bamboozled Drawer. The system lets a user select an ordinary file, store it through Hermione, verify it, and restore it to a user-authorized destination. Our controlled Android API-35 emulator campaign eventually accounted for 100/100 exact-return trials across ten synthetic file populations, including text, JSON, PDF, image, audio, video, repetitive data, and incompressible data. The campaign's verdict was PASS WITH LIMITS . Why the limits? Because 63 earlier trials had a different destination-evidence tier than the 37 successor trials, and emulator evidence doesn't automatically prove physical-device or production behavior. We also ran lifecycle and hostile-security experiments. Those tests found a real corruption-cleanup defect: a failed restore could leave an unwanted destination placeholder. A separate isolated repair subsequently demonstrated rejection of corrupted durable data without leaving that placeholder. The original failure remains in our records. That's what testing is supposed to do: find what doesn't work so we can improve it. I want this part to be absolutely clear. Hermione-S, our enterprise storage research effort, is not enterprise-qualified. Its last reported enterprise qualification scoreboard was 2 of 19 rows qualified . There are still open requirements involving independent infrastructure, distributed behavior, real restart and recovery conditions, storage economics, custody, and operational validation. Our Android prototype is also not production-ready. And our storage accounting has shown that some populations can consume more total resident storage once metadata, caches, and other costs are included. We preserve those results too. I work with an AI-assisted engineering team I call my Jamily. I direct the vision, ask questions, challenge assumptions, and decide what we're trying to accomplish. The agents handle much of the implementation, testing, and technical investigation. I don't pretend I personally typed every line of code. And I don't pretend a successful test means something has been proven universally. My standard is simple: Evidence over confidence. Receipts over claims. If you're interested in content-addressed storage, deduplication, reproducible benchmarks, deterministic reconstruction, or storage economics, I'd genuinely like to hear your technical questions. What would you test next? What would you challenge? What evidence would you require before considering a storage system enterprise-ready? I'm not asking anyone to believe a percentage because it looks impressive. I'm inviting people to examine the boundaries and help make the experiments stronger. The Basement Lab is still building. And I'm having a hell of a time doing it. 🤣🧡♟️ Bohdi Flint — Founder, Bamboozled Labs CheckTheReceipts BasementDoesItBest