HackerTube.dev

"Making Impossible States Impossible" by Richard Feldman

elm-conf · 63.1K views · 2016-09-19 · 25:06

Open on YouTube ↗

If playback is restricted in your region, try opening the original video. Use Mark watched to add it to your marked videos.

Overview

Richard Feldman's elm-conf talk on designing models so that bugs from impossible application states cannot occur, using Elm's compiler and types. It demonstrates techniques for making invalid states unrepresentable.

On Hacker News

HN repeatedly recommends it as a talk that changed how people model data, with ideas that apply well beyond Elm to any typed language.

Recommended by 9 HN people across 13 months · HN mentions 2017–2026

Topics

Functional programmingSoftware architecture & design
Search by tags
elmtype systemsmake illegal states unrepresentabledata modeling

What people said

terminatornet · 2024-04 · Strong recommendation

one of my favorite talks on this topic, "Making Impossible States Impossible" by Richard Feldman: [VIDEO] the talk is Elm lang focused, but the concepts still apply to other languages.

Read the original HN comment ↗
terminatornet · 2023-05 · Strong recommendation

highly recommend the talks "making impossible states impossible" and "make data structures" by richard feldman. [VIDEO] [LINK] the talks are geared towards elm but I think they offer some great advice applicable to programming in general.

Read the original HN comment ↗
kilian · 2018-10 · Strong recommendation

Making impossible states impossible" by Richard Feldman: [VIDEO] has really changed the way I approach dealing with data in my code and was very insightful.

Read the original HN comment ↗

Sources

Video by elm-conf, played through YouTube.

Data and selection notes

HN summaries and labels may contain AI errors. HN dates refer to discussions, not video publication.

HN Library: HackerTube export (2026-10-31) and open-index/hacker-news. Upstream summaries and classifications may contain AI errors.

Views, duration and playback status refresh separately from the published catalog. When an update fails, existing data remains visible.

Selection checks
  • SaaS & AI candidates: Topic keywords do not match
  • Editor-approved picks: Editorial review is required

Rule matches identify candidates. They do not guarantee video quality or financial results.

About the library and its sources