Developer Docs Audit (Nakora): Making Your API Docs Readable for AI

2026-02-09 | ProductHunt | Nakora.ai

30-Second Quick Judgment

What does this do?: This isn't a SaaS software, but an audit service. The Nakora team specialized in giving DevTools companies a "check-up" on their documentation to find out why developers sign up but don't activate, or why ChatGPT/Claude can't find answers about your product.

Is it worth watching?:

• If you sell APIs/SDKs: A must-watch. In 2026, docs aren't just for humans; they must be optimized for AI (LLM SEO).
• If you're a general user: Not worth it; this is a B2B service.

Compared to whom?:

• Think of it as an "SEO audit for documentation," but focused on DevTools + LLM visibility. There are almost no direct competitors in this emerging vertical consulting space.

🎯 Three Questions for Me

Is this relevant to me?

• Target User: DevTool founders, DevRel (Developer Relations) leads, technical marketers.
• Am I the target?: If you're worried about "nobody reading the API docs" or "users taking too long to integrate," then yes.
• When would I use it?:
  • Scenario 1: You realize ChatGPT's answers about your product are all wrong (LLM hallucinations).
  • Scenario 2: Users get stuck at the "Hello World" stage after signing up, causing high churn.

Is it useful for me?

ROI Judgment: For high-ticket DevTool products, fixing one documentation friction point can recover thousands of dollars in lost customers. The ROI is very high.

Is it satisfying?

The "Aha!" Moment:

• Curing "The Curse of Knowledge": They've analyzed 120+ top products and can point out the "turn-off" details you've missed.
• LLM Optimization: This is a fresh concept—once optimized, AI becomes your free sales agent.

🛠️ For Independent Developers

Tech/Service Implementation

• Core Logic: This isn't an automated scanning tool; it's a hybrid "expert experience + data analysis" service.
• Tech Stack: While they haven't disclosed internal tools, they clearly use LLMs to simulate developer reading paths and test "AI-friendliness."
• Team Background: Founder Filip Nakov previously grew an API product from zero to millions in revenue—he's a practitioner.

Business Model

• Monetization: Agency model (consulting fees).
• Pricing: Not public; usually project-based (estimated $1k - $5k+) or used as a lead magnet.

Giant Risk

• Low Risk: Giants like Stripe and Twilio have massive internal DevRel teams. Nakora serves the small-to-mid-sized market.

📦 For Product Managers

Pain Point Analysis

• The Pain: 90% of developers check the docs before deciding to buy. Bad docs = No revenue.
• Traffic Anxiety in the AI Era: In 2026, developers ask AI first. If your docs aren't indexed or understood by AI, you vanish from their radar.

Competitive Differentiation

Key Takeaways

• "Docs as a Product": Don't write docs as manuals; design them as conversion funnels.
• LLM-Friendliness Check: Before publishing, feed your docs to Claude/GPT to see if it can write correct code based on them.

✍️ For Tech Bloggers

Founder Story

• Filip Nakov: Focused on Developer Messaging with successful DevTool growth experience.
• Andreu Codina: Handles AI engineering to ensure audit advice aligns with LLM crawling logic.

Discussion Angles

• "AI SEO" (LLM Optimization): This is a great hook. Traditional SEO is dead; it's the era of LLO (Large Language Model Optimization).
• The Survival Battle for DevTools: In an age where AI writes code, if your API docs aren't standardized, AI won't call your libraries.

🧪 For Early Adopters

Pitfall Guide

• Not an automated tool: Don't expect to just enter a URL and get a report; it requires human intervention.
• Potential Waitlist: As an agency service, capacity is limited by manpower.

Alternatives

• DIY Approach:
  1. Feed your docs to Claude.
  2. Prompt: "You are a junior developer. Try to write a Hello World based on this documentation and tell me where you get stuck."

💰 For Investors

Market Analysis

• Sector: Developer Marketing & DevRel Tools.
• Trend: With the rise of AI Coding Agents (like Cursor, Windsurf), API doc standardization and machine readability are more critical than ever.
• Ceiling: As a service company, the ceiling is lower, but if they can standardize into a SaaS tool (like an automated doc scorer), the potential is huge.

Team

• Small and lean, a classic Boutique Agency setup with deep vertical know-how.

Conclusion

Final One-Sentence Judgment: This is a future-facing vertical consulting service that doesn't just fix docs—it helps you win the "mindshare" of machine users in the AI era.

Resource Links