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The New Rules – Developer's survival guide for the AI era

Hacker News

The New Rules – Developer's survival guide for the AI era

Hey HN :) I'm Andrzej, 15 years building distributed systems. Over the past two years, I watched AI change everything about how we work as developers – and most of the discourse was either panic or hype. So I spent that time researching what actually works. The result: "The New Rules" – 16 chapters on navigating the AI era as a developer. Accompanied by a website to help us all get more in-depth into the discussion. Some of the controversial takes inside: * GitHub stars became meaningless vanity metrics – so how do we quick-filter for quality? * Skills that got you to $100K won't get you to $200K (the career ladder just shifted) * Small teams with AI will crush large teams without it * Your moat isn't code quality anymore – it's judgment, architecture, and trust I've created this book with heavy AI assistance (Claude and ChatGPT) – proud of the outcome, my learning and the effort it took to get quality content through the full pipeline... Note that some examples and case studies are illustrative, combining real insights with fictional elements to better convey concepts. I've checked what I could, but I'm sure there's room for further improvement. Its not a scientific publication, but rather in-depth share of my perspective on changes happening in these interesting times. Licensed under CC BY 4.0 – free to share, adapt, even use commercially with attribution. Hardcover available for $39 if you want the physical version (shipping from Poland). I'm here all day for discussion, pushback, corrections, and hearing about your experiences. If you spot inaccuracies in the examples or have better case studies, I'd love to hear them. Direct PDF download: https://pub-7a9dcf4135624a49ac92e46823c312c1.r2.dev/TheNewRu...

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Product HuntOn track for Day 1 leaderboard · Strong signals: claude, new, chatgpt · Missing: mac, agents, macos
87%87% 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: created · Missing: supports, reddit linkedin, podcasting
71%71% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, pipe, io · Missing: https docs, excited, just released
58%58% 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 · Missing: mobile apps, ios, personal
34%34% 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
28%28% 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
15%15% 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.

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