Raindrop (@raindrop_ai) is building the safety layer for AI agents. As agents get more…
This is a dev post classified by Jev as Testing & observability (a launch), kept by the Dev Radar because it carries real work, not commentary.
Raindrop (@raindrop_ai) is building the safety layer for AI agents. As agents get more capable and take on more complex work, Raindrop detects when they go wrong in production, from failed tool calls and hallucinations to problems companies didn’t even know to look for. Now they’re launching Raindrop Simulations, which brings that same approach earlier in the development process to catch failures before agents reach production. Already used by companies including Vercel, Clay, Framer, and Speak, Raindrop just raised a Series A bringing its total funding to $50 million. In this episode of Fou
Posted by Y Combinator (1.7M followers) 2 days ago · 219 likes · 52.2k views · view the original post on X. Kept by the Dev Radar as Testing & observability.
More dev work like this
- What does observability look like when a judgment costs nothing? — @hugorcd
- When agent traces turn into a debugging pile, this repo gives you a place to inspect them. — @DanKornas
- I’m glad @strawgate's standards for coffee are lower than his standards for code review… — @kayvz
- Gitar finds bugs, fixes them under your team's rules, and verifies every fix by running… — @SonarSource
- OPENAI 🔥: Chrome extensions are now supported in the ChatGPT desktop browser! — @testingcatalog
- AI at scale needs visibility to match. — @splunk
- Quick tip from Visual Studio on YouTube... See the Visual Studio Debugger Agent use a… — @VisualStudio
- Agent regressions are hard to catch when traces are read-only. — @DanKornas
Every post is read and classified by Jev (TypeSafe): what it is, which market it belongs to, and whether the link is a real tool. 12.2k posts from 4.7k X accounts over the last 21 days, 1.4k tools, 12 markets. Collected every 5 minutes, fully re-ranked every hour — last update 2026-09-19 18:39 UTC. Full method.