Hatch v1.16.0 – workspaces, dependency groups and SBOMs

Hacker News

This release wouldn’t have been possible without Cary, our new co-maintainer. He picked up my unfinished workspaces branch and made it production-ready, added SBOM support to Hatchling, and landed a bunch of PRs from contributors! My motivation took a big hit last year, in large part due to improper use of social media: I simply didn’t realize that continued mass evangelism is required nowadays. This led to some of our novel features being attributed to other tools when in fact Hatch was months ahead. I’m sorry to say that this greatly discouraged me and I let it affect maintenance. No more of that! Development will be much more rapid now, even better than the way it used to be. We are very excited for upcoming features :-)

Visit product View on Hacker NewsNov 27, 2025

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

76%76% 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

60%60% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

52%52% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

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

44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

20%20% 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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