{"slug": "pseudo-compiler-vibe-coding-an-ai-that-translates-pseudocode-to-executable", "title": "Pseudo-Compiler: Vibe-Coding an AI that Translates Pseudocode to Executable Scripts", "summary": "A developer built Pseudo-Compiler, an AI-powered engine that translates plain-English pseudocode into executable Python or JavaScript, using Sanity as the state-management and workflow backend rather than a simple LLM wrapper. The system models compilation as a data pipeline with Drafting, Compiling, Review, and Approved-for-Execution stages, where a Sanity webhook triggers a background agent to generate code and a human must approve it in Sanity Studio before execution. The build used Cursor, Next.js App Router, and Sanity's App SDK, with a pseudoScript document type holding rawPseudocode, targetLanguage, compiledCode, and executionLogs.", "body_md": "What I Built\n\nI built Pseudo-Compiler, an AI-powered translation engine that acts as a real-time compiler for pseudocode. It allows users to write logic in plain, structured English (or any loose pseudocode format) and automatically compiles it into working Python or JavaScript.\n\nRather than just being a wrapper around an LLM API, this app uses Sanity as the core engine for state management and execution workflows. By treating the compilation process as a data pipeline, the app utilizes Sanity Workflows to manage the lifecycle of a script: from Drafting (writing pseudocode), to Compiling (agentic generation of code), to Review (human-in-the-loop validation), and finally Approved for Execution.\n\nIt is designed for beginners learning algorithm logic without getting bogged down by syntax, and for developers who want to rapidly prototype business logic before writing boilerplate.\n\nMy Build Process\n\nI used Cursor as my AI-native IDE alongside a Next.js (App Router) frontend and a Sanity backend. My goal was to see how far I could push \"vibe-coding\" to handle not just UI generation, but complex data state transitions using Sanity's newer features.\n\nThe Prompting Journey:\n\nI started with a broad structural prompt:\n\n\"Scaffold a Next.js app with a split-pane code editor. The left side accepts plain text pseudocode, and the right side displays read-only code. Connect this to a Sanity backend where every new snippet is saved as a document with a draft status.\"\n\nCursor nailed the UI using Tailwind and Monaco Editor within minutes, but the data modeling required more explicit steering.\n\nWhere the Model Got Stuck:\n\nInitially, the AI tried to put the entire LLM \"compilation\" call inside a frontend React component, bypassing Sanity entirely. It just wanted to fetch the OpenAI API on the client side.\n\nThe Course Correction & Hitting the Bonus Objectives:\n\nI stopped the IDE and pivoted to explicitly prompting for Sanity Workflows and a background agent.\n\n\"Refactor this. Do not call the LLM from the frontend. Instead, when the user clicks 'Compile', save the pseudocode to Sanity and update the document's state to Pending Compilation. Write a Sanity webhook handler that listens for this state, triggers the AI agent to write the code, saves the compiled code back to the document, and transitions the workflow state to Needs Human Review.\"\n\nThis worked brilliantly. By modeling the compilation process as data next to the content, I achieved the \"Workflows\" bonus objective. The Sanity Studio now acts as the central control room:\n\nAgent Handoff: An external API (Next.js route) acts as the autonomous agent, listening to Sanity webhooks, compiling the code, and pushing it back.\n\nHuman Approval: Before any code can be executed in the custom App SDK dashboard, a user must open Sanity Studio, review the agent's code, and click \"Approve\".\n\nI also utilized the App SDK to build a custom real-time dashboard on top of the content. Instead of a read-only blog frontend, the frontend acts as an execution environment that pulls Approved scripts directly from the Sanity dataset and allows users to run them in a sandboxed browser environment, logging the console outputs back into a RunHistory array on the Sanity document.\n\nSchema Highlights: The primary document type is pseudoScript, featuring fields for rawPseudocode, targetLanguage, compiledCode, and executionLogs.", "url": "https://wpnews.pro/news/pseudo-compiler-vibe-coding-an-ai-that-translates-pseudocode-to-executable", "canonical_source": "https://dev.to/solomon1029/pseudo-compiler-vibe-coding-an-ai-that-translates-pseudocode-to-executable-scripts-39ig", "published_at": "2026-10-03 17:58:18+00:00", "updated_at": "2026-10-03 18:07:56.221167+00:00", "lang": "en", "topics": ["ai-tools", "ai-agents", "developer-tools", "generative-ai"], "entities": ["Sanity", "Cursor", "Next.js", "OpenAI", "Monaco Editor", "Tailwind", "Pseudo-Compiler"], "also_reported_by": [], "alternates": {"html": "https://wpnews.pro/news/pseudo-compiler-vibe-coding-an-ai-that-translates-pseudocode-to-executable", "markdown": "https://wpnews.pro/news/pseudo-compiler-vibe-coding-an-ai-that-translates-pseudocode-to-executable.md", "text": "https://wpnews.pro/news/pseudo-compiler-vibe-coding-an-ai-that-translates-pseudocode-to-executable.txt", "jsonld": "https://wpnews.pro/news/pseudo-compiler-vibe-coding-an-ai-that-translates-pseudocode-to-executable.jsonld"}}