Hunter Leath, CEO of Archil, explains how they’re building a “universal storage engine” that sits between your apps and S3—making an S3 bucket behave like a fast, POSIX-compatible disk for containers, servers, and even Lambda. Along the way, we dig into how their SSD-backed clusters and custom protocol avoid the usual small-file pain and where this approach shines (and where it doesn’t).Follow Hunter:Twitter/X:  https://twitter.com/jhleathArchil Twitter/X:  https://twitter.com/archildataArchil: https://archil.com/Follow Aaron:Twitter/X:  https://twitter.com/aarondfrancis Database School: https://databaseschool.comDatabase School YouTube Channel: https://www.youtube.com/@UCT3XN4RtcFhmrWl8tf_o49g  (Subscribe today)LinkedIn: https://www.linkedin.com/in/aarondfrancisWebsite: https://aaronfrancis.com - find articles, podcasts, courses, and more.Chapters:00:00 - Intro: Archil Data and “S3 as a disk”01:05 - Hunter’s background and the core pitch02:32 - The real problem: state management (S3 vs block storage)05:02 - SQLite on S3: what the stack looks like07:13 - The missing layer: durable SSD-backed clusters10:14 - Who uses this: unstructured data, CI/CD, Git, agents12:15 - Small files + Git performance and avoiding S3 request explosion16:22 - Why they built a new protocol (NFS vs Luster)20:00 - What gets written to S3: real files in your bucket22:29 - S3 limits, throttling, and the “keep it on SSD” escape hatch25:32 - Multi-cloud + R2, and why regions/latency matter32:10 - Pricing model: “pay only when data is active”34:41 - Tradeoffs: random reads and ultra-low-latency metal37:19 - Storage/compute separation and AI/agent-native workflows43:21 - YC timeline + the marketing challenge of a “universal layer”47:34 - Single-tenant clusters for enterprises and why it’s hard50:27 - Where the company is now, hiring, and how to try it (disk.new)

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