Thanks everyone for the lively discussion, and huge thanks to the folks who emailed mods and vouched to clear the automated filter flag on my new account!
A few common points raised across the thread that I’d like to address in one place:
1. On "Alone", AI, and the Craft Anything methodology:
Some folks dug into the repo, found the rules and chronicles, and pointed out this is heavily AI-assisted. They are 100% right — and I don't hide it (there is an open public dev chronicle in docs/ detailing every single step). By "alone" I meant no venture backing, no university grant, and no human engineering team.
However, this isn't chaotic one-shot prompting. StatCraft is built as part of the ArtCraft suite, following the philosophy and methodology of Craft Anything (https://github.com/storytold/craft-anything - "understand how any software works, and craft your own"): using evidence-backed, clean-room investigation to replace closed, predatory software with open, reliable tools. We pair an orchestrator with specialized AI agents, constrained by strict compiler invariants and external mathematical oracles. That's also why StatCraft has a native Model Context Protocol (MCP) server: the software itself is designed to live natively in an agent-first world where researchers can interact with deterministic tools via natural language.
2. On "100% Safe Rust" terminology:
Fair critique from the Rust community on the phrasing: what I technically meant is #![forbid(unsafe_code)] across the workspace, zero unsafe blocks, and a zero-panic invariant (Result<T, E> everywhere, zero unwrap/expect in non-test code). The compiler ensures memory safety invariants, while domain correctness is enforced via fuzzing and mathematical oracle tests.
3. On Clean-Room & Legal concerns:
No IBM binaries were reverse-engineered or decompiled. The .sav and .zsav codecs follow open specifications established by GNU PSPP and the MIT-licensed ReadStat library. The statistical procedures are implemented strictly from academic literature and public formula specifications (such as the SPSS 24 Algorithms Guide), validated against SciPy with <= 1e-6 precision.
4. "Why not just use R/Tidyverse?":
R and Python are wonderful for coders. But thousands of students, sociologists, psychologists, and clinicians are trained purely on SPSS's GUI. When their university license expires, they face a $1000+/year paywall from IBM and have legacy .sav files they can't easily open without proprietary software. StatCraft is built for them: a free, native GUI tool that respects their muscle memory, works offline, and never crashes on messy survey data.
If you have old, weird, or corrupted .sav files, or want to audit a statistical procedure against your own SPSS outputs, issues and PRs are very welcome on GitHub.
A few common points raised across the thread that I’d like to address in one place:
1. On "Alone", AI, and the Craft Anything methodology: Some folks dug into the repo, found the rules and chronicles, and pointed out this is heavily AI-assisted. They are 100% right — and I don't hide it (there is an open public dev chronicle in docs/ detailing every single step). By "alone" I meant no venture backing, no university grant, and no human engineering team.
However, this isn't chaotic one-shot prompting. StatCraft is built as part of the ArtCraft suite, following the philosophy and methodology of Craft Anything (https://github.com/storytold/craft-anything - "understand how any software works, and craft your own"): using evidence-backed, clean-room investigation to replace closed, predatory software with open, reliable tools. We pair an orchestrator with specialized AI agents, constrained by strict compiler invariants and external mathematical oracles. That's also why StatCraft has a native Model Context Protocol (MCP) server: the software itself is designed to live natively in an agent-first world where researchers can interact with deterministic tools via natural language.
2. On "100% Safe Rust" terminology: Fair critique from the Rust community on the phrasing: what I technically meant is #![forbid(unsafe_code)] across the workspace, zero unsafe blocks, and a zero-panic invariant (Result<T, E> everywhere, zero unwrap/expect in non-test code). The compiler ensures memory safety invariants, while domain correctness is enforced via fuzzing and mathematical oracle tests.
3. On Clean-Room & Legal concerns: No IBM binaries were reverse-engineered or decompiled. The .sav and .zsav codecs follow open specifications established by GNU PSPP and the MIT-licensed ReadStat library. The statistical procedures are implemented strictly from academic literature and public formula specifications (such as the SPSS 24 Algorithms Guide), validated against SciPy with <= 1e-6 precision.
4. "Why not just use R/Tidyverse?": R and Python are wonderful for coders. But thousands of students, sociologists, psychologists, and clinicians are trained purely on SPSS's GUI. When their university license expires, they face a $1000+/year paywall from IBM and have legacy .sav files they can't easily open without proprietary software. StatCraft is built for them: a free, native GUI tool that respects their muscle memory, works offline, and never crashes on messy survey data.
If you have old, weird, or corrupted .sav files, or want to audit a statistical procedure against your own SPSS outputs, issues and PRs are very welcome on GitHub.