Better PDF Presentations (+Typst)

Hacker News

Like many of us here I prefer not use PowerPoint. Recently I've been making slides in Typst ( https://typst.app ) which is great, except there's no good way to actually present the resulting PDF, and no support for speaker notes, videos or GIFS. To fix this I built Presio: https://presio.xyz . Present any PDF in the browser as two synced windows, a controller (speaker notes, timer, media controls) and a viewer for the projector. It handles embedded video and GIFs, including YouTube/Vimeo. Local by default: your PDF never leaves your browser. Optionally shareable so the audience can follow along on their own devices. A short GIF explains it best: https://imgur.com/a/ZbvhPnc Try the an example presentation: https://presio.xyz/present?from=https://github.com/benedict-... Works with plain Typst, Polylux, Touying and PDFs from LaTeX too (speaker notes supported). Try it for a presentation and lmk what you think!

Visit product View on Hacker NewsJun 25, 2026

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

75%75% 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.

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

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

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

51%51% 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: ide, io, including · 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.

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.

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 · 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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