Exploring a more deterministic approach to AI-assisted code generation
AI coding agents are effective for small projects but face challenges with scalability due to prompt instability. A more deterministic approach involves treating prompts as explicit, reusable, and composable source code. This method improves predictability and control, especially in larger codebases.
- ▪Prompt instability in AI coding agents leads to inconsistent outputs and unpredictable behavior in large projects.
- ▪The SVI tool uses structured specification files (.svi) to generate code from deterministic, reusable prompts.
- ▪Unlike traditional agents, SVI does not rely on chat history or implicit context, making the code generation process more transparent and controllable.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3908112) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Aleksandr Razinkin Posted on May 1 Exploring a more deterministic approach to AI-assisted code generation #ai #vibecoding #programming #webdev Introduction AI coding agents are getting surprisingly good. In small projects, you can ask them to add features, fix bugs, and even write tests—and they often succeed. But once your project grows, things start to break down. In my experience, the issue is not model capability. It’s something more subtle: prompt instability.
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