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Explore Go + HTMX + SQLite : The $6/mo AI Tech Stack with 8,960 views, 283 likes, and 10 comments. Experience the impact of this video content that has captured audience attention.

Are you paying thousands of dollars for Next.js on Vercel and complex cloud architectures just to host a simple AI wrapper? Discover why developers are abandoning bloated React SPAs and massive AWS bills for a minimalist $5 VPS stack built entirely on Go, HTMX, and SQLite. 🔔 Subscribe: https://www.youtube.com/channel/UC0DZj1PNa_Fp0MU6uPSKv5w?sub_confirmation=1 💙 Become a Member: https://www.youtube.com/channel/UC0DZj1PNa_Fp0MU6uPSKv5w/join 🐦 Twitter/X: https://x.com/cloud_codes 💬 Discord: https://discord.gg/4kJqEBMMf In this system design breakdown, we expose the brutal economics of AI app development: your server spends 99% of its life waiting for LLM tokens, meaning the actual compute required to run a full web server, queue, and database fits on a $5 Hetzner box. We dive deep into how Go's 2KB goroutine stacks handle 10,000 concurrent LLM API connections without breaking a sweat, why HTMX completely removes the need for client-side state and hydration, and how SQLite (paired with Litestream for real-time backups) can easily handle production workloads up to 20,000 writes per second. We also break down the hidden costs of AI API billing—why caching your system prompt drops your OpenAI bill by 72%, and how limiting output tokens is the highest-leverage performance tuning you can do. If you found this technical deep-dive into AI infrastructure and software engineering architecture helpful, drop a like and subscribe for more content on system design and scaling applications! ⚙️ CORE SQLITE PRAGMAS COVERED: PRAGMA journal_mode = WAL; PRAGMA synchronous = NORMAL; PRAGMA busy_timeout = 5000; ⏱️ TIMESTAMPS: 00:00 - The Economics of AI Hosting (Waiting is Free) 01:12 - The Stack: Go, HTMX, SQLite on a $5 VPS 02:04 - Goroutines: Solving the 10,000 Concurrent User Problem 02:40 - HTMX v2: The End of Hydration & Bundlers 03:51 - SQLite in Production: WAL Mode & Benchmarks 05:27 - Caching, Vector Search, and the 1-Writer Limit 07:07 - AI API Billing Math: Input vs Output Tokens 08:19 - Real-World Proof: PhotoAI & The Vercel Tax 09:09 - The 4 Catches: Where This Stack Fails 10:10 - Deployment Setup (Caddy, Litestream, Cloudflare R2) 11:01 - The Final Verdict on AI Infrastructure #golang #htmx #sqlite #systemdesign #softwareengineering #vps #hetzner #webdevelopment #artificialintelligence #localai #architecture #systemdesign User Queries: golang htmx sqlite web app architecture how to deploy go app on hetzner $5 vps replace react with htmx for ai applications sqlite wal mode concurrent writes benchmark litestream sqlite backup to cloudflare r2 golang goroutines vs threads memory usage openai api pricing caching input tokens vs output server sent events vs websockets for llm streaming nextjs vercel bandwidth pricing overage sqlite vec vector search benchmark mac mini

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