DeckWeaver – Create AI-powered Google Slides presentations in minutes

Hacker News

As I frequently run bespoke training sessions and project-based workshops for clients, I create quite a lot of presentations and, naturally, to some extent rely on ChatGPT and similar tools to help me create the content. However, as I use Google Slides (rather than a Markdown-based presentation tool), I faced the significant problem of having to manually import the content into Google Slides presentations via copy and paste, which was very time-consuming. Hence, I built a solution called DeckWeaver that not only takes this tedious work off my hands, but also allows me to review generated content directly from within the application, which has the added benefit of fewer context switches and media breaks: https://usedeckweaver.com/

Visit product View on Hacker NewsApr 22, 2026

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

88%88% 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

74%74% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: google · Missing: mobile apps, ios, personal

56%56% 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

42%42% predicted probability of success on AppSumo, 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

39%39% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Strong signals: training · 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 · 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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