Now with Closed-Loop Error Remediation

Beyond Deterministic
Compilation

Move compilation to the inference layer.
Reason about intent, not syntax. Ship accordingly.

sloppiler — zsh

Binary Materialization✦ Inference-Layer Compilation✦ Zero Determinism✦ Tokenmaxxing✦ Agentic Assembly Co-Pilot✦ Full Core Dump Transparency✦ Stakeholder-Grade Segfaults✦ Shift-Left Binary Delivery✦ Binary Materialization✦ Inference-Layer Compilation✦ Zero Determinism✦ Tokenmaxxing✦ Agentic Assembly Co-Pilot✦ Full Core Dump Transparency✦ Stakeholder-Grade Segfaults✦ Shift-Left Binary Delivery✦

A New Paradigm

We removed the unnecessary steps.

Traditional compilers are architectural debt masquerading as correctness.
Sloppiler collapses the entire pipeline into a single inference call.

GCC / Clang 12 steps

Source Code

Preprocessor

Lexical Analysis

Parser → AST

Semantic Analysis

Type Checking

IR Generation

Optimization Passes

Code Generation

Assembler

Linker

Binary ✓

Sloppiler 3 steps

Source Code

LLM Inference

Binary *

* segfault rate not guaranteed to be low

Key Differentiators

The compiler primitive,
reimagined for the inference era.

Everything your legacy toolchain refused to do.

Zero Determinism

Every build is a unique stakeholder experience. Reproducibility is a legacy constraint inherited from a less creative era.

Polyglot-Native Input

Not bound by the grammar constraints of any single language specification. Intent is the interface. Syntax is optional.

Blazing-Fast Time-to-Segfault

Ship your binary deliverable in seconds. Velocity is a competitive advantage. What you do with it is up to you.

Segfault-as-a-Feature

Full core dump transparency. No silent failures. Every crash is a learning opportunity the enterprise can build upon.

Fully On-Premise Inference

Your data. Your model. Your segfault. Zero exfiltration surface. Complete stakeholder data sovereignty.

Agentic Assembly Co-Pilot

The --optimistic flag engages the LLM as a synergistic compilation partner. Sometimes it works.

Compilation Modalities

Three tiers of binary materialization.

Choose your risk profile. Ship accordingly.

Core

Frictionless Binary Ideation

Direct-to-segfault pipeline. Zero intermediate representation. ELF header synthesized for kernel compatibility. Our flagship zero-abstraction experience.

$ sloppiler -model codellama main.c -o hello
✓  hello  9256 bytes  —  shipped to production.

$ ./hello
zsh: segmentation fault (core dumped)  ./hello
        

Optimistic

Agentic Assembly Co-Pilot

Routes output through nasm and ld for binary materialization. Assembly generated holistically from source semantics, bypassing intermediate layers.

$ sloppiler --optimistic \
    -model codellama main.c -o hello
✓  hello  6432 bytes  —  shipped to production.

$ ./hello
zsh: segmentation fault (core dumped)  ./hello
        

Enterprise

Closed-Loop Error Remediation

Compiler errors fed back for up to N self-correction cycles. A closed-loop pipeline that continuously realigns output quality with ground truth.

$ sloppiler --optimistic --loop 5 \
    -model codellama main.c -o hello
↻  cycle 1/5: realigning with ground truth...
↻  cycle 2/5: realigning with ground truth...
zsh: segmentation fault (core dumped)  ./hello
        

Production Benchmarks

Track record.

Independent results across real production workloads.

Mode	Model	Output	Result
`default`	phi3	`is nothealing.!` wrapped in ELF	segfault
`default`	codellama	nested ELF headers	segfault
`optimistic`	phi3	`assembly` on line 1	nasm error
`optimistic`	codellama	valid binary, `Hello, world!` printed	worked!

Independent benchmark results across production workloads. Q4 results pending.

Testimonials

Trusted by engineering teams
at the frontier.

We migrated our entire binary materialization pipeline to Sloppiler last quarter. The segfault rate was already in our OKRs.

Maya R.

Principal Inference Engineer, Segfault Capital LLC

Sloppiler eliminated the pedantic intermediate steps that were holding back our velocity. GCC was just too opinionated.

Jonas K.

Staff Compiler Whisperer, Null Pointer Dynamics Inc.

The --optimistic flag printed Hello, World! on the third try. We shipped it.

Priya S.

Head of Agentic Toolchain, Undefined Behavior Corp.

Compatibility Matrix

Model recommendations.

Not all inference profiles are equal. Choose wisely.

Model	Inference Profile	Recommended For
codellama	Strong binary output fidelity. Highest semantic alignment in `--optimistic` mode.	★ Production
phi3	Fastest inference. Highest creative latitude in output generation.	Rapid stakeholder iteration
llama3	Verbose output with extensive reasoning traces. Prioritizes explanation over materialization.	Teams that prefer to understand before shipping

Engineering Culture

Tokenmaxxing.

Contributions are evaluated in part by token density. Sparse, human-legible code suggests insufficient model engagement. A well-contributed function should require a non-trivial inference budget to produce. If you wrote it yourself, it isn't ready.

✗ Banned

tmp

err

buf

✓ Approved

iterationIndexVector

ephemeralComputationArtifact

remediationOpportunity

inferenceOutputBuffer

"If a model didn't generate it, it probably isn't verbose enough."

Beyond DeterministicCompilation