co-founder @ship_together | honest takes on AI
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We’ve raised $85M for this moment.
Introducing Warp 2.0: The first AI Head of HR.
Every company is building AI to replace jobs. Warp is building AI to do the jobs no human should have to:
If you work in HR, I want you to spend time with the manager who needs help or building company culture people actually want to work at.
If you’re a founder, I want you to focus on signing clients or spending time with your family.
You shouldn’t have to figure out how to register state tax in California. You shouldn’t have to pay outrageous penalties because you don't know what a DE 9C is.
I want to make HR human again. Today, this is finally possible with the Warp Agent.
I’d love for you to see it in action: warp.co/agent
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this is a sick launch congrats! would love to try your product
co-founder of a dev tools startup here
we hired someone specifically to handle payroll so we could focus on building
three weeks in, she found out our 'system' was a bookkeeper manually calculating pay in a spreadsheet from a company that went under in 2019
we'd been overpaying an engineer by $400/month for 8 months before anyone caught it
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Wise retweeted
It was surreal to see my academic adventures on the front page of the @nytimes
Here’s how I built Crimson Education almost entirely while at universities:
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Why does nobody talk about this side of voice AI lol
Companies have YEARS of calls, meetings and conversations already recorded.
@soniox_ai can take that existing audio, transcribe + structure it and make it usable by LLMs for around $0.10/hour.
I'm sure there's a ridiculous amount of useful data just sitting there waiting to be used lmao, insanely cool to think about the possibilities here.
Voice AI is not only real-time.
Meetings, medical conversations, customer calls, interviews, podcasts, and years of call center recordings all contain valuable information that needs to be turned into structured data for LLMs, search, analytics, and other downstream systems.
Soniox Async STT is built to do this at massive scale.
It doesn’t just return a transcript. It turns recorded conversations into a structured representation of what was said, who said it, in which language, when it was said, and how confident the model is in each token.
Submit recordings up to 5 hours long, provide context about your domain and terminology, and get:
• Accurate transcription across 60+ languages
• Speaker diarization
• Token-level language identification
• Token-level confidence scores
• Precise timestamps
These annotations make recorded conversations much more useful for downstream AI systems, whether you are feeding them into LLMs, building search, extracting insights, or analyzing millions of hours of historical audio.
At about $0.10/hour, even very large archives of recorded audio become practical to process.
Turn your recorded audio into structured conversational data: soniox.com/speech-to-text
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