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Prism – Let browser agents access any app

Hacker News

Prism – Let browser agents access any app

Hey HN, We’re Alex, Land, and Rajit. We’re building Prism (prismai.sh), a tool that helps browser agents authenticate onto websites with user credentials. Developers pass in credentials, Prism logs into a website on their behalf, and hands them back the cookies so they have an authenticated session. Here’s an example of how developers can use Prism to complete username/password flows ( https://youtu.be/SEtVUnWnxuE ), and here’s an example of how developers can use Prism to complete login flows that require an OTP code ( https://youtu.be/fe9w9PvrwH0 ). We spoke to browser agent developers and saw people copying and pasting credentials and even credit card numbers directly into model system prompts. We were surprised that there wasn’t a better way to give agents access to websites on a human’s behalf. Moreover, we noticed that every company had to build infrastructure to manage OTP, TOTP, and MFA and that auth remained a significant hurdle in agent reliability. We wondered if this was a boring part of the problem of building web automations that someone could automate away. We started working with Casco, an autonomous security testing company, to enable their agent to access customer sites. Before a pentest, Casco makes a request to Prism’s API specifying test user credentials, a domain, and a login method. For example, give me an authenticated session for the account rajit@prismai.sh for OpenAI via OTP code over email. Our agent logs in on their behalf (without exposing credentials to a model), and we download the cookies and send them back in the response. To maintain speed and reliability, we use playwright in most cases to login (which gives us speed), and we fallback to AI on failure (which gives us reliability). We have a number of websites we support out of the box and add new scripts as the number of websites we need to support grows. We are working on a way for the agent to update the existing playwright script on failure, so our scripts always stay up to date. To try our api, you can use our API playground docs.prismai.sh/api-reference/endpoint/login to sign into x.com with the following API key: pk_54abb1cd0a637eb973ed690416e71a953e98f2ea839cf16529bbfa41a41bc016 . We’d love to learn more about how other developers give agents access to their accounts. We look forward to everyone’s feedback and comments.

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, model · Missing: mac, macos, cursor
96%96% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
78%78% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: exist, existing, io · Missing: https docs, excited, just released
68%68% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: way · Missing: mobile apps, ios, personal
58%58% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
26%26% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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