{"podcast":{"title":"Business Tech Brief By HackerNoon","slug":"business-tech-brief-by-hackernoon-6365657","podcast_index_feed_id":6365657,"rss_url":"https://feeds.transistor.fm/business-tech-brief-by-hackernoon","website_url":"https://hackernoon.com/c/business","image_url":"https://img.transistorcdn.com/OUWuR-Qwloz1TIhKajSLipyXw2kUGZcLi7sTCQEahMM/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9zaG93/LzQxMjY1LzE2ODM1/ODI2MTUtYXJ0d29y/ay5qcGc.jpg","author":"HackerNoon","episode_count":100,"summary":"Learn the latest Business updates in the tech world.","last_synced_at":"2026-06-17T06:20:05.817581+00:00","page_url":"https://stenobird.com/podcast/business-tech-brief-by-hackernoon-6365657"},"episode":{"title":"How I Built an AI VC Associate to Screen 3,000 Pitch Decks","slug":"how-i-built-an-ai-vc-associate-to-screen-3-000-pitch-decks","published_at":"2026-02-05T16:00:59+00:00","page_url":"https://stenobird.com/podcast/business-tech-brief-by-hackernoon-6365657/how-i-built-an-ai-vc-associate-to-screen-3-000-pitch-decks","show_page_url":"https://stenobird.com/podcast/business-tech-brief-by-hackernoon-6365657","url":"https://share.transistor.fm/s/a8358186","audio_url":"https://media.transistor.fm/a8358186/84c56ee5.mp3","summary":"This story was originally published on HackerNoon at: https://hackernoon.com/how-i-built-an-ai-vc-associate-to-screen-3000-pitch-decks . VC analysts review 3,000 pitch decks a year and waste hours on manual triage. This article shows how an VCs can automate dealflow screening and prioritization. Check more stories related to business at: https://hackernoon.com/c/business . You can also check exclusive content about #agentic-ai-for-venture-capital , #startup-pitch-deck-screening , #generative-ai-for-vc , #ai-vc-triage-deal , #automated-pitch-deck-analysis , #vc-dealflow-automation , #vc-crm-automation-workflow , #ai-investment-memo-generation , and more. This story was written by: @jurgispocius . Learn more about this writer by checking @jurgispocius's about page, and for more stories, please visit hackernoon.com . A typical VC analyst reviews around 3,000 decks annually and invests in roughly 9. Average time spent per deck: 2-3 minutes (up to 10 if we include preliminary research) This means 99.7% of their time is “wasted” This isn’t a dealflow problem. The issue is triage throughput.","meta_description":"This story was originally published on HackerNoon at: https://hackernoon.com/how-i-built-an-ai-vc-associate-to-screen-3000-pitch-decks . VC analysts revie…","key_points":[],"chapters":[],"topics":[],"duration_seconds":939,"processing_state":"not_requested","actions":[{"name":"request_transcript","method":"POST","url":"https://stenobird.com/v1/public/podcasts/business-tech-brief-by-hackernoon-6365657/episodes/how-i-built-an-ai-vc-associate-to-screen-3-000-pitch-decks/transcription-requests","description":"Idempotently request low-priority transcript generation for this episode."},{"name":"read_markdown","method":"GET","url":"https://stenobird.com/podcast/business-tech-brief-by-hackernoon-6365657/how-i-built-an-ai-vc-associate-to-screen-3-000-pitch-decks.md","description":"Read the agent-friendly Markdown representation of this episode resource."}]}}