Everyone’s buzzing about “prompt engineering” or “vibe coding” using tools like Cursor or Windsurf to turn text prompts into code. It feels exciting, but it’s fundamentally limited.
Why? Because text prompts require massive, precise context to work well.
Right now, you’re either pasting snippets of code or manually selecting files to contextualize prompts. This might seem fine at first, but as complexity grows, keeping every module and dependency in your head is impossible — especially when AI-generated code starts piling up. It’s like editing a book by repeatedly reprinting the whole thing and hoping nothing gets accidentally changed in unrelated chapters or footnotes. This approach is brittle, error-prone, and fundamentally doesn’t scale.
Current tools (Cursor, Windsurf) still rely heavily on text-based context, introspecting code or basic UI — but never truly understanding modules declaratively. They’re stuck at the “whole-book” level, unable to compartmentalize logic cleanly or efficiently.
We don’t just need better prompts — we need IDEs that can contextualize intelligently and structurally:
Instead of dumping entire codebases into a prompt, imagine IDEs structuring code contextually — like chapters, sections, or paragraphs in a book — so LLMs know precisely what to edit without breaking something three modules away.
External integrations today mean manually coding APIs and OAuth flows — super painful and slow (try building authentication!). Future IDEs should leverage open protocols (like Anthropic’s Model Context Protocol) to autonomously select and integrate the right modules visually and declaratively, generating integration code transparently behind the scenes.
You shouldn’t have to worry if changing a detail breaks something elsewhere. IDEs need to manage context boundaries intelligently — allowing developers to iterate conversationally within clearly scoped modules or flows.
Text alone can’t deliver this. Current tools can’t deliver this.
We need a fundamentally new approach — an IDE explicitly designed around structured, modular context and iterative, visual assembly — powered by LLMs that understand and reason at the module level.
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If you have any questions or thoughts, don't hesitate to reach out. You can find me as @viksit on Twitter.