tonyww
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If you are building AI agents with frameworks like browser-use, LangChain, or OpenClaw, you've likely hit the "blast radius" problem. A misconfigured prompt or hallucination can cause an agent to navigate to a phishing…
- A verification layer for browser agents: Amazon case study (sentienceapi.com)
A common approach to automating Amazon shopping or similar complex websites is to reach for large cloud models (often vision-capable). I wanted to test a contradiction: can a ~3B parameter local LLM model complete the…
- A verification layer for browser agents: Amazon case study (sentienceapi.com)
A common approach to automating Amazon shopping or similar complex websites is to reach for large cloud models (often vision-capable). I wanted to test a contradiction: can a ~3B parameter local LLM model complete the…
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Hi HN, This is an integration between browser-use and Sentience SDK, where Sentience acts like Jest for AI web agents: it lets agents assert what changed on the page, instead of guessing when they’re “done”. Most web…
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Hi HN, I’m the solo founder behind SentienceAPI. I’ve spent the last December building a browser automation runtime designed specifically for LLM agents. The Problem: Building reliable web agents is painful. You…
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Hi HN, I’m a solo founder working on SentienceAPI, a perception & execution layer that helps LLM agents act reliably on real websites. LLMs are good at planning steps, but they fail a lot when actually interacting with…