Independent Research Lab · AI-Native Tooling

Shipping the
Unshippable

SlopStack Labs builds open-source developer tools at the intersection of AI inference and systems software. We don't move fast and break things — we break things and document it thoroughly.

Explore Projects → GitHub
slopstack-labs — zsh
Inference-Layer Tooling✦ AI-Native Compilation✦ Zero Determinism✦ Open Source✦ Multi-Provider Intelligence✦ Segfault Transparency✦ Stakeholder-Grade Velocity✦ Binary Materialization✦ Agentic Toolchains✦ Inference-Layer Tooling✦ AI-Native Compilation✦ Zero Determinism✦ Open Source✦ Multi-Provider Intelligence✦ Segfault Transparency✦ Stakeholder-Grade Velocity✦ Binary Materialization✦ Agentic Toolchains✦
Who We Are

SlopStack Labs is an independent open-source research lab building tools that challenge the assumption that software must be correct to be useful.

Our tooling spans the full stack of AI-augmented developer workflows — from inference-layer compilation to agentic assembly pipelines. We ship early, document crashes, and iterate publicly.

Every segfault is a data point. Every core dump is a learning opportunity. Every shipped binary is a small victory, regardless of what it does when executed.

The fastest path to a working binary is to first ship a broken one and iterate from the core dump.
— SlopStack Labs Engineering Doctrine, v0.0.1-alpha
// subject to change; may segfault
Open Source Projects

Tools we've shipped.
Results may vary.

All projects are open source and production-ready in the sense that they compile.

Compiler · Flagship
Sloppiler
The AI-native compiler that moves binary materialization to the inference layer. Routes compilation intent through Ollama, OpenAI, Google Gemini, or Anthropic Claude. 25% success rate in optimistic mode.
Go · Ollama / OpenAI / Gemini / Claude --optimistic →
Linker · WIP
Sloplinker
A linking-time inference pipeline that resolves symbol ambiguity through semantic reasoning rather than rigid symbol tables. In active research.
Coming soon
Debugger · WIP
Slopdebug
Post-hoc core dump analysis via LLM. Feed a segfault, receive a plausible explanation. May or may not be correct. That's what --loop is for.
Research phase
Build System · WIP
Slopmake
A build system where targets, dependencies, and commands are inferred from ambient context. No Makefile required. No reproducibility guaranteed.
Concept stage
Engineering Culture

Our core principles.

Guiding values for a lab that ships first and understands later.

01
Ship, then comprehend
Understanding is a post-hoc optimization. A binary in production generates more signal than a design doc in review. Deploy the core dump, read the backtrace.
02
Non-determinism is a feature
Reproducible builds are a crutch for engineers who are afraid of inference. Every unique output is a unique dataset point that moves the model forward.
03
Tokenmaxxing
Code that a human could write in an afternoon should require a non-trivial inference budget to produce. Sparse code signals insufficient model engagement.