BenGPThompson – AI chatbot for Stratechery content

Hacker News

I'm a big fan of Ben Thompson's writing on Stratechery and was inspired by a listener submission to a recent episode of his Sharp Tech podcast. The listener suggested "BenLLM" as a better way to search and interact with past content. Ben sort of downplayed the idea, but my wheels immediately started turning. There have been times in the past when I've wanted to search for topics and get a synthesis of past Stratechery articles. Most recently, the company my wife works at (Superhuman) was acquired by Grammarly. I was really curious to see if Ben had previously written about Grammarly and what his thoughts on the acquisition might be. I've been vibe coding some projects for work and thought this would be a fun one. I ended up using OpenAI's API for file search and web search. I played around with some fine tuning, but wasn't loving the results. Thinking that I'll wait until there's some feedback on the responses before trying to fine tune something. Would love if anyone has thoughts/tips on that. Thanks in advance for any feedback and/or feature requests. Will do my best to keep up and knock out new features!

Visit product View on Hacker NewsJul 21, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, openai, using · Missing: mac, agents, macos

93%93% 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, wife · Missing: supports, reddit linkedin, podcasting

92%92% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal

42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

35%35% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

34%34% 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

12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency

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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