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- 1Developer pays strangers to test if README instructions work●I paid people to try and follow my README
A developer paid people to attempt setting up a project using only its README file, then documented what broke and where the instructions failed. The experiment highlights how software documentation that seems obvious to its author often confuses new users, and how small usability tests with real people can reveal gaps that reviewers miss.
- 2
Developer Terence Eden hired people to try installing his project using only its README, exposing how badly software documentation usually fails. He argues that open source projects routinely ship poor documentation — outdated notes and abandoned forums — instead of clear instructions, and tested his own by paying real users to follow it cold.
- 3Developer shares lessons from building GravLang v1.1.0▼While recording a demo video for GravLang v1.1.0, I pasted the example from my own README into my own... # programming #
A developer has released version 1.1.0 of GravLang, a self-built programming language, and is recording a demo video for it. While preparing the demo, they pasted an example from the project's own README into the language and ran into an unexpected problem. The write-up reflects on what the creator got wrong while building their own programming language, touching on Python tooling, open-source development and community feedback.
- 4Good Documentation Decides Whether Developers Contribute●GitHub's 2021 Octoverse report found that 60% of developers decide whether to contribute based solely... # documentation
GitHub's 2021 Octoverse report found that 60% of developers decide whether to contribute to an open source project based solely on its documentation, particularly the README. Developers are now sharing practical advice on usability-testing README files, arguing that clear, welcoming documentation is essential for usability, inclusivity, and growing open source communities.
- 5Prompt injection in coding agents exploits everyday project files●Prompt injection in coding agents comes through READMEs, issues, PR text, tool results and web pages. Why filtering fail
Security researchers and developers are highlighting how coding agents can be manipulated through prompt injection hidden in ordinary developer materials — READMEs, issue text, pull request descriptions, tool output and web pages they read. Discussion centres on why content filtering fails to catch these attacks and which capability limits, rather than filters, actually constrain the risk.
- 6Writer pays strangers to test if his README actually works●I paid people to try and follow my README https://shkspr.mobi/blog/2026/10/i-paid-people-to-try-and-follow-my-readme/ #
A developer blogger paid several people to follow a README file and report where they got stuck, testing whether his documentation truly stands on its own. The experiment highlights a familiar problem in software: instructions that seem clear to the author often confuse everyone else. Readers are sharing their own experiences of unclear documentation and debating how much effort maintainers should put into testing guides on real users.
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Blogger Terence Eden argues that most open-source READMEs are never truly tested by their own authors. He walks through the typical Linux install experience: following the README step by step, only to hit missing instructions on unpacking archives, running setup scripts, or hidden prerequisites. His point is that developers should verify documentation the way a new user would, rather than assume it works.
Repos
- storytold/vectorcraft VectorCraft: An open-source, vector art tool written by scratch in pure Rust
- DuarteSantos8/openGym Self-hosted gym & body-weight tracker — plan routines, log workouts (supersets, warm-ups, cardio), see which muscles
- openai/math
- bas3line/ascii Animated ascii art for web pages, in TypeScript: React, Next.js, Astro, or one HTML tag
- NationalSecurityAgency/ghidra Ghidra is a software reverse engineering (SRE) framework
- aardappel/goose The Goose Programming Language
- jorgeandrecastro/github-workflow
- volotat/mini-AGI Continual learning model trained from scratch on 8GB VRAM laptop with batch-1 stream of data.
- wy-coliney/jev-browser-use 5–10x faster browser operations: Jev clicks, Codex thinks and verifies. Built at EZCollegeApp.
- incoai/splash A local inference engine for Apple silicon, built around the model.
- Sparticle62ops/pssa PSSA: a non-transformer language model written from scratch in Rust. Recurrent state-space layer, episodic memory, self-
- jegly/jegly boring readme
- githubnext/localjev