
John Hwang
2.7K posts

John Hwang
@ainativefirm
enterprise ai trends. ex-head, vix and variance derivatives, Morgan Stanley



this wasn’t a prompt. this was: - 8 hours of work - 5 iterations - 3 senior designers

A detailed and brutal look at the tactics of buzzy AI compliance startup Delve "Delve built a machine designed to make clients complicit without their knowledge, to manufacture plausible deniability while producing exactly the opposite." substack.com/home/post/p-19…


SMCI confesses to being Nvidia's partner-in-crime in Singapore sales. Amazing.


Introducing TigerFS - a filesystem backed by PostgreSQL, and a filesystem interface to PostgreSQL. Idea is simple: Agents don't need fancy APIs or SDKs, they love the file system. ls, cat, find, grep. Pipelined UNIX tools. So let’s make files transactional and concurrent by backing them with a real database. There are two ways to use it: File-first: Write markdown, organize into directories. Writes are atomic, everything is auto-versioned. Any tool that works with files -- Claude Code, Cursor, grep, emacs -- just works. Multi-agent task coordination is just mv'ing files between todo/doing/done directories. Data-first: Mount any Postgres database and explore it with Unix tools. For large databases, chain filters into paths that push down to SQL: .by/customer_id/123/.order/created_at/.last/10/.export/json. Bulk import/export, no SQL needed, and ships with Claude Code skills. Every file is a real PostgreSQL row. Multiple agents and humans read and write concurrently with full ACID guarantees. The filesystem /is/ the API. Mounts via FUSE on Linux and NFS on macOS, no extra dependencies. Point it at an existing Postgres database, or spin up a free one on Tiger Cloud or Ghost. I built this mostly for agent workflows, but curious what else people would use it for. It's early but the core is solid. Feedback welcome. tigerfs.io


i spent $800 so far this month on claude code : O




Looking to build resilient, observable AI agents without a heavyweight framework? Of course you are—you follow the Inngest corporate account. Well lucky for you, @djfarrelly 's latest guide is here to help. You'll need Inngest (Free version works!), an LLM provider (Anthropic, OpenAI, whatever), and TypeScript. Let's get started. inngest.com/blog/ai-agents…


spent most of my day playing with GLM-OCR it's a 0.9B param vision-language model. supports 8K resolution, 8+ languages, and has built-in text, LaTeX, and table recognition modes. awesome! I tested it across different OCR tasks. starting with shipping container serial numbers.













