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Glupe πŸ™πŸŒΉ. Constrain where AI can generate code. Keep the rest of your codebase untouched.

34 starsC++

I built "Docker for code", isolate AI logic into semantic containers

by alonsovmΒ·Feb 15, 2026Β·3 pointsΒ·0 comments

AI Analysis

●●SolidBig BrainSolve My Problem

Container syntax restricts AI rewrites to marked zones, avoiding silent hallucinations.

Strengths
  • β€’Container hash-caching skips redundant LLM calls for unchanged logic blocks
  • β€’Sensible problem framing: AI as precision tool rather than all-or-nothing rewriter
  • β€’Works with any language via compiling containers down to native syntax
Weaknesses
  • β€’Competing against mature tools (Cursor, Cody) that already have hallucination mitigations built-in
  • β€’No real-world evidence it's better than explicit human-written prompts + review
Target Audience

Developers concerned about AI-assisted coding safety and code preservation

Similar To

GitHub Copilot Β· JetBrains AI Β· Continue.dev

Post Description

Hello HN, i want to share Glupe, a hobby project I've been working on for the last 30 days. Nothing fancy.

I've been pretty annoyed by the "all or nothing" approach of most AI coding tools, which are useful, yes, but also risky. If i tell an AI to "fix this bug" it may probably do it, but it can (or will) hallucinate a fake library, mess up my manually optimized code or subtly delete important code without explaination or notice.

Glupe summarized is this: "Stop giving AI root access to your code, Glupe isolates AI logic into semantic containers, so your code stays safe".

Instead of sending your whole file to the LLM and pray it does not break, with Glupe you can surgically tell the AI were to write code and what to do using the $${ logic }$$ syntax. Code outside the container is preserved as is. Instructions inside the container are turned into source code and embedded into the output file.

Containers can be named and are cached and hashed, Glupe detects which containers changed in a source file; when you run `glupe project.txt -make` it only calls the AI to update the "dirty" logic containers and uses cached code for the clean ones, saving time and API calls and allowing for incremental builds using AI.

What if there is a syntax error on the output code? Glupe has a self-healing loop which feeds the error history back to the LLM and tells it to fix it. No more trivial debugging.

Why do I say it is "Docker for code"? It is a metaphor, it applies the same core principle of Isolation to source text that Docker applies to running processes.

In Servers: If you run an app directly on a host OS, it has "root access." If it behaves badly, it can delete system files.

In Coding: If you give an AI access to your file, it has "root access." It can "crash" your architecture by deleting manual code or changing signatures. Docker protects the OS from the App. Glupe protects your Architecture from the AI.

Docker solved "it works on my machine", Glupe aims to solve "

I wrote a white papaer on the subject which is available in the repo.

Any feedback or critcism is welcome and encouraged.

repo: https://github.com/alonsovm44/glupe white paper:https://github.com/alonsovm44/glupe/blob/master/WHITE_PAPER....

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