Most AI coding agents fail not because they lack coding ability, but because they lack context. After months of hitting a wall with Cursor and Bolt, I realized a 1-sentence prompt is the fastest way to get trapped in a "bug-fixing loop."
The missing link isn't better AI—it’s Technical Grammar.
I built https://ideaforge.chat to shift the workflow from "prompting" to "specification forging."
What’s different about this approach?
Adaptive Interviewing: Instead of a static template, the AI acts as a PM/Technical Co-founder that grills you on logic gaps you didn't know existed.
Forcing Technical Decisions: It won't let you start coding until you've defined things like data relationships, session persistence, and edge cases.
Machine-Readable Specs: The output is a structured Markdown document specifically formatted to maximize the performance of coding agents like Cursor or Windsurf.
I’ve moved from "broken apps on the first try" to "MVPs that actually work" by using this interview-first method.
To the engineers: Is the "Specification Gap" something you see as the primary bottleneck for non-technical partners? I’d love your feedback on whether this Socratic approach produces the kind of PRD you’d actually find useful for a high-stakes project.
Sorry to hear you gave up! That’s really helpful feedback. The interview is thorough because I wanted to ensure a 'one-shot' code generation, but I clearly need to work on the UX and maybe a 'Fast Track' mode. I'll be looking into how to make the steps feel less like a chore. Thanks for being honest!
Spot on. The 'Ask me what questions you need' prompt is the secret sauce. IdeaForge essentially automates and refines that process so users don't have to figure out what questions to ask the AI. It's about reducing the cognitive load for the user.
Thanks for pointing those out! GSD and spec-kit are great tools. IdeaForge tries to focus more on the pre-development interview phase—helping non-technical founders or solo devs clarify the logic before they even look at a repo.
Great question, @ravroid. Custom GPTs are fantastic for general workflows, but IdeaForge is built for a more focused 'one-shot' success rate. Here’s why I think it’s worth a try over a generic prompt/GPT:
Guided Extraction vs. Open Chat: Custom GPTs can sometimes drift or get 'lazy.' IdeaForge uses a specific Socratic interview logic designed to pull out the 'unknown unknowns' (like edge cases and data relationships) that users often forget to prompt.
Optimized for Codex Context: The output isn't just a summary; it’s a structured specification specifically formatted to minimize hallucinations when pasted into Cursor or Codex.
Zero Context Switching: Instead of jumping between an 'interview GPT' and a 'dev plan GPT,' IdeaForge handles the entire pipeline in one specialized UI, ensuring the logic remains consistent from idea to spec.
Lower Barrier: No ChatGPT Plus subscription required for your end-users to get high-quality technical specs.
I'd love for you to run one of your existing ideas through IdeaForge and let me know if the resulting MD is more 'executable' than your current workflow
Thank you for the reality check! You’re absolutely right. As a solo creator, I initially focused on the core logic, but trust is the most important feature. I’ve just added a formal Privacy Policy and Terms
I have a confession: I’m not a developer. >
Like many people here, I’ve been blown away by Cursor, Bolt, and Codex. But as a non-technical person, I quickly hit a wall. It wasn't that the AI couldn't code—it was that I didn't know how to describe what I wanted. >
I would give a 1-sentence prompt, get a broken app, and then get stuck in a "bug-fixing loop" because I hadn't defined the logic, the database schema, or the edge cases properly. I had the vision, but I lacked the "Technical Grammar" to communicate it.
It acts as the "Technical Co-founder" or "Product Manager" I didn't have. Instead of me struggling to write a prompt, the tool interviews me. It asks the questions I didn't know I should be asking (e.g., "How should we handle session persistence?" or "What's the data relationship between X and Y?").
How it works for me:
I chat with IdeaForge about my "napkin sketch" idea.
It grills me on the details until the logic is watertight.
It generates a structured Markdown specification.
I paste that spec into Cursor/Codex.
For the first time, I’m actually building tools that work on the first try. I’m sharing this today because I think there are many other "dreamers" who are just one clear specification away from their first functional MVP.
I’d love to get the perspective of the experienced engineers here: Does the output look like something you’d actually want to receive as a dev spec?
I'm excited! Almost everyone here is looking forward to big future payouts of gigs that require cleaning up during emergency slop outages that impact the loss of a critical line of business.
Most AI coding agents fail not because they lack coding ability, but because they lack context. After months of hitting a wall with Cursor and Bolt, I realized a 1-sentence prompt is the fastest way to get trapped in a "bug-fixing loop."
The missing link isn't better AI—it’s Technical Grammar.
I built https://ideaforge.chat to shift the workflow from "prompting" to "specification forging."
What’s different about this approach?
Adaptive Interviewing: Instead of a static template, the AI acts as a PM/Technical Co-founder that grills you on logic gaps you didn't know existed.
Forcing Technical Decisions: It won't let you start coding until you've defined things like data relationships, session persistence, and edge cases.
Machine-Readable Specs: The output is a structured Markdown document specifically formatted to maximize the performance of coding agents like Cursor or Windsurf.
I’ve moved from "broken apps on the first try" to "MVPs that actually work" by using this interview-first method.
To the engineers: Is the "Specification Gap" something you see as the primary bottleneck for non-technical partners? I’d love your feedback on whether this Socratic approach produces the kind of PRD you’d actually find useful for a high-stakes project.
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