Continue for JetBrains - how we made it IDE-agnostic

Hacker News

Hi HN! Since launching Continue two months ago ( https://news.ycombinator.com/item?id=36882146 ), we've received amazing feedback, added features, and greatly improved reliability. But one of the biggest things we heard was the desire for a JetBrains extension. My co-founder Ty and I are super excited to share that we've released an extension for PyCharm, Intellij, WebStorm, and most other JetBrains IDEs - ready for alpha users at https://plugins.jetbrains.com/plugin/22707-continue . Perhaps the most exciting part is that this effort was kickstarted and in great part developed by a community contributor! If you're curious what it took to make this happen, check out the PR here ( https://github.com/continuedev/continue/pull/457 ). We hope to eventually support every IDE, so we made adding a new extension as easy as implementing a single class. If you're curious why this is possible, you can read more about the Continue Server and the architectural decisions we made here: https://blog.continue.dev/how-we-made-continue-ide-agnostic .

Visit product View on Hacker NewsOct 17, 2023

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Hacker NewsStrong engagement from HN community · Strong signals: excited, ide, io · Missing: https docs, just released, exist

72%72% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

65%65% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting

65%65% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

40%40% 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

17%17% 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

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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