Train Claude Code's replacement (ds4 and pi and aoe)

Hacker News

Remember how Meta monitored employee activity closely for a few months, and then had a bunch of layoffs related to AI efficiency? (oh right that was like 3 days ago). What if you could do the same thing to your workforce of Claude Code agents? Aka use Claude Code to observe and distill how to make a different AI model/harness work nearly as well, so that then you don't need Claude anymore? If AI is doing it to humans in the workforce, why can't we do the same thing to AI... I love Claude but it's always good to have a backup, in case, say, the subscription plan goes away and you're expected to pay for the API usage rates. If you'd like to follow along, discuss, or contribute, this is the repo where the work is going. I'm working on this using the DeepSeek V4 Flash repo but it would be interesting to see how the process works if trying to teach a smaller LLM.

Visit product View on Hacker NewsMay 29, 2026

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, claude · Missing: mac, macos, cursor

99%99% 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 · Missing: supports, reddit linkedin, podcasting

80%80% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

46%46% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

33%33% 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

24%24% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: subscription · Missing: arr, mrr, revenue

21%21% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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