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20 projects
Build and run ML workflows in an agent-native cloud notebook with evaluation tools.
eldar_hsnv · HN
Show HN: AI Notebook for Data Science – Kind of Like Cursor but for Jupyter
View product work, engineering changes, and deployment status in one place to confirm shipping readiness.
@Abubakar_2005 · X
Working on two projects right now: -Hooklens – making webhooks easier to build and manage. -Conductor Labs – helping teams ship web apps with more confidence. Would love your thoughts! Hooklens: Conductor Labs:
Coordinate multiple AI coding agents and projects in one unified terminal interface.
@soracstv · X
I run my AI coding agents with AgentsRoom, a visual command center for multi-agent development. @AgentsRoomDev #VibeCoding #AI
AI drafts documentation for your codebase; your team edits and publishes via Git commits.
linktothenew · HN
Docs.dev – A docs site you own, where AI drafts and you edit in place
Launch tokens and trade on Robinhood Chain instantly.
@nockwtf · X
No need to wait hours for vibe coded slop when you can already launch and trade on
Deploy Ruby on Rails, Sinatra, and Jekyll apps from GitHub with custom domains.
@aiw3ndil · X
Migrate NoSQL databases to SQL with automated schema mapping and live change replication.
@heyayankai · X
🚀 Building NoSQLSync. It helps developers migrate NoSQL databases to SQL without writing custom migration scripts. Always happy to connect with fellow builders and AI enthusiasts.
Semantic caching reduces LLM token costs and latency for AI queries.
u/ornymo_official · Reddit
how to reduce ai costs there are lots of way to reduce costs but there all complex to setup i know this cause i tried one in production so i built ornymo we cache meaning not the exact string allowing us to give same awnsers thus reducing llm costs and latency check it out at ornymo.com free for a limited time and let me know your feedback submitted by /u/ornymo_official to r/buildinpublic [link] [comments]
