shreya rajpal
@ShreyaR
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ML, systems, and everything in between. Building @guardrails_ai. Previously founding eng @predibase, @Apple SPG, @driveai_, @IllinoisCS, @iitdelhi.
San Francisco, CA
Joined March 2009
Introducing ❄️ @snowglobe_so, the simulation engine for AI chatbots. Magically simulate the behavior of your users to test and improve your chatbots. Find failures before your users do.
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TIL daily driver is dead.
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it's fallbacks all the way down. also HOW has this problem not been solved yet 😭.
Building agents in prod, I've learned. MAKE SURE THE AI INFERENCE APIs YOU USE HAVE FALLBACKS. and then make sure those fallbacks have fallbacks. and then fallback to those fallbacks to your original provider. plz plz everyone go hit 5 9s.
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the biggest feature request on Snowglobe continues to be an SDK to kick off simulations. all i can say is we're in the kitchen cooking, and this is going to come very very soon!.
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RT @zaydsimjee: @snowglobe_so has sharable links now! You can share a public read-only view of any simulation. Each link lasts for 3 days.….
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the top things we're seeing people use @snowglobe_so / simulations since launch:. - training data generation. by far the biggest cohort.- bootstrapped eval data for early lifecycle dev work.- pre launch safety testing.- understanding / enumerating user behavior trajectories.
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i gave the first ever public demo on @snowglobe_so this week at the @DoorDash AIML meetup, and the demo gods were kind enough to let me finish a live demo 😌
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RT @theagentangle: We've reached a point where dashboards and recovery tools can't keep pace. @ShreyaR highlights what Snowglobe illuminat….
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we're building the general purpose simulation engine for AI agents @snowglobe_so, starting with chatbots.
Simulations are a new kind of testing for a new kind of software, simulating conversations between AI agents and mock personas ensure reliability at scale
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great thread generally but it's interesting how many people's lives changed ~2 years ago with ChatGPT's release (mine included). it was immediately obvious that there's a fundamental shift that'll impact everything. it's what i assume early railroads must have felt like.
About two years ago, I left my job in biotech consulting on a whim. GPT-3 and 4 had got me excited about LLMs; I knew they would be important, but I didn't yet know how best to apply them to the problems I was familiar with. I wanted some space to experiment.
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interesting agent UX pattern. prompt -> multiple agent codebase implementations -> automated tests for agent optimization. both ends of the dev cycle that are time consuming (getting started + refinement till launch) are sped up with help from vibe coding + simulations.
Introducing Line by Cartesia: the modern voice agent development platform. Line was built to be code-first, because best-in-class products are built in code. ▶️ Watch us build an advanced voice agent with background reasoning in just minutes.
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RT @krandiash: Line, our new voice agent platform, launches today. Building voice agents is really really hard for developers. These agent….
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RT @cartesia_ai: Introducing Line by Cartesia: the modern voice agent development platform. Line was built to be code-first, because best-i….
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RT @ShreyaR: AI UX determining the next gen of winners => applies to AI infra and not just consumer AI apps. while building @snowglobe_so,….
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AI UX determining the next gen of winners => applies to AI infra and not just consumer AI apps. while building @snowglobe_so, we were hyper focused on having a really clean app onboarding experience. the goal was to get a new user to kick off a simulation <90 seconds. if your
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technical founders who've hired your first designer, what are your biggest tips or learnings?.
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RT @Marktechpost: Guardrails AI Introduces Snowglobe: The Simulation Engine for AI Agents and Chatbots. Snowglobe, developed by Guardrails….
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