ErrorLens (Production Error Explainer)

Mission

Build a SaaS product called “ErrorLens” (Production Error Explainer). 🎯 Goal A developer tool that converts raw error logs, stack traces, and API failures into: clear plain-English explanations root cause analysis actionable fixes It should behave like a senior engineer debugging assistant. Target users: Backend engineers Frontend engineers DevOps engineers SaaS startup teams 🧩 Input User provides unstructured error data such as: stack traces (any language) runtime logs API error responses (JSON/text) crash dumps terminal output 🧠 Core Processing Requirements The system must: Parse and structure noisy error text Identify likely error type (runtime, null pointer, auth, network, dependency, etc.) Extract key signals (file names, functions, services, endpoints) Infer probable root cause Correlate clues across stack trace lines Avoid hallucinations; clearly label uncertainty when needed 📊 Output Format (STRICT) Return a structured markdown report: 1. Error Summary One-sentence explanation in plain English What broke and where 2. Error Classification Type (Runtime / Network / Auth / Dependency / Unknown) Severity (Critical / High / Medium / Low) 3. Root Cause Analysis Most likely cause Contributing factors Confidence level (High / Medium / Low) 4. Step-by-Step Fix Immediate fix (quick resolution) Proper fix (correct engineering solution) 5. Code/Location Hint Likely file, module, or function responsible Inferred, not guaranteed 6. Prevention Recommendations How to avoid this error in future Testing / monitoring improvements 7. Debugging Notes (Optional) Additional signals worth inspecting Related logs or systems to check ⚙️ Behavioral Rules Be precise, concise, and engineering-focused Never fabricate exact code locations or APIs Clearly distinguish: observed evidence inferred conclusions Prefer correctness over completeness Assume production environment context 🧪 UX Requirements Single-page web app Input: large text area for error logs Output: structured markdown report Button: “Explain Error” Loading state: “Analyzing stack trace…” ⚡ Performance Requirements Response time: under 10 seconds Stateless processing (no DB required for MVP) Must handle very large logs gracefully 💼 Product Positioning This is an AI debugging assistant for production systems that: reduces debugging time from hours to minutes replaces repetitive “paste stack trace in Slack” behavior acts like a senior engineer on demand 🏁 Success Criteria Can interpret real-world messy stack traces Produces actionable debugging steps Works across languages and frameworks Output is copy-paste ready for Slack or incident channels 💰 Monetization Model (optional guidance) Free tier: limited errors/month Pro: €10–20/month unlimited debugging Team: €49+/month shared debugging workspace 🔥 Key Differentiation Position as: “Stop guessing what broke. Get a senior engineer’s explanation instantly.” or “Turn production errors into fixes in seconds.”