# Cogniscor - Interactive Mode Guide ## 🎯 What is Interactive Mode? After Cogniscor generates your company research, it shows you the **executive summary** and asks: **"Is this executive summary good?"** You can: - ✅ **Accept** - Keep the results as-is - 🔄 **Request improvements** - Ask for specific additional information - ❌ **Cancel** - Keep current results without changes This feature uses AI to perform **focused follow-up research** based on your specific needs! --- ## 🚀 How It Works ### Step 1: Initial Research ```bash ./cogniscor.sh https://github.com ``` Cogniscor collects and analyzes company data... ### Step 2: Review Executive Summary After analysis, you'll see: ``` ╔════════════════════════════════════════════════════════════╗ ║ 📄 EXECUTIVE SUMMARY PREVIEW ║ ╚════════════════════════════════════════════════════════════╝ # Executive Summary: GitHub, Inc. *Generated: 2025-10-07 17:30:00* ## Overview GitHub is a developer platform that allows developers to create, store... ## Key Facts **Industry:** Software Development Platform **Founded:** 2008 **Headquarters:** San Francisco, California ... (showing first 50 lines) ════════════════════════════════════════════════════════════ ╔════════════════════════════════════════════════════════════╗ ║ REVIEW & FEEDBACK ║ ╚════════════════════════════════════════════════════════════╝ Is this executive summary good? (yes/no/improve) [yes]: ``` ### Step 3: Your Choice #### Option A: Accept (Default) ``` Is this executive summary good? yes ✓ Great! Reports saved and ready to use. ``` #### Option B: Request Improvements ``` Is this executive summary good? improve ╔════════════════════════════════════════════════════════════╗ ║ 🔍 CUSTOM SEARCH REFINEMENT ║ ╚════════════════════════════════════════════════════════════╝ Describe what you want to find or improve: Examples: - 'Find more information about their engineering culture' - 'Get details about their remote work policy' - 'Focus on recent product launches and roadmap' Your request: Find more about their engineering culture and tech stack ``` ### Step 4: Focused Research Cogniscor then: 1. **Plans focused search** with AI 2. **Discovers specific URLs** likely to have that information 3. **Scrapes focused sources** (company blog, engineering pages, etc.) 4. **Verifies content** matches the company 5. **Enhances the report** with new information 6. **Shows updated summary** ``` 🔍 Performing focused research based on your request... 📋 Search Plan: Focus: Engineering culture, tech stack details, development practices URLs to try: 5 Search queries: 3 🌐 Collecting focused information... Trying: https://github.blog/engineering Trying: https://github.com/about/careers/engineering Trying: https://github.com/about/engineering-culture ✓ Collected information from 3 sources 🔍 Re-analyzing with focused information... ✓ Analysis complete 📝 Enhancing executive summary... ✓ Executive summary updated with focused information ✨ Research refinement complete! ``` --- ## 💡 Example Improvement Requests ### 1. Engineering Culture ``` Your request: Find more about their engineering culture and development practices ``` **What AI does:** - Searches for engineering blog - Looks for careers/engineering pages - Finds tech talks and presentations - Extracts culture information - Adds "Engineering Culture" section to summary ### 2. Remote Work Policy ``` Your request: Get details about remote work and work-life balance ``` **What AI does:** - Finds careers page - Looks for "remote" and "work from home" mentions - Checks employee reviews for WLB mentions - Searches for remote work announcements - Adds to "Company Culture" section ### 3. Recent Products ``` Your request: Focus on recent product launches in the last 6 months ``` **What AI does:** - Searches newsroom/press releases - Looks for blog announcements - Finds product pages - Filters for recent dates - Creates "Recent Product Launches" section ### 4. Compensation & Benefits ``` Your request: Find information about salary, benefits, and stock options ``` **What AI does:** - Searches careers page for benefits - Looks for Glassdoor compensation data - Finds press releases about equity - Checks for compensation philosophy - Adds "Compensation & Benefits" section ### 5. Tech Stack Details ``` Your request: Get comprehensive details about their technology stack and infrastructure ``` **What AI does:** - Finds engineering blog posts - Looks for tech talks and conference presentations - Searches for "built with" or "powered by" mentions - Checks job postings for required skills - Expands "Technology Stack" section --- ## 🎯 Best Practices ### Be Specific ❌ Bad: "Find more information" ✅ Good: "Find information about their internship program and new grad hiring" ❌ Bad: "Improve the report" ✅ Good: "Get details about their diversity and inclusion initiatives" ### Focus on One Topic ✅ Good: "Focus on their AI/ML engineering team and projects" ❌ Too broad: "Find everything about engineering, products, culture, and benefits" ### Ask for Findable Information ✅ Likely available: "Engineering culture", "recent news", "product roadmap" ❌ Unlikely: "Internal politics", "secret projects", "unpublished financials" --- ## ⚙️ Configuration ### Enable/Disable Interactive Mode Interactive mode is **enabled by default** when AI is configured. To disable it: ```bash # Use the --no-interactive flag ./cogniscor.sh --no-interactive https://github.com ``` Or in scripts/automation: ```bash # Always disable for batch processing for url in $(cat companies.txt); do ./cogniscor.sh --no-interactive "$url" done ``` ### Interactive Mode Requirements - ✅ AI must be enabled (requires OpenAI API key) - ✅ Terminal must support user input - ✅ Not using `--no-interactive` flag If AI is disabled, interactive mode is automatically skipped. --- ## 💰 Cost Impact Each improvement cycle adds: - Focused search planning: ~$0.003 - URL discovery: ~$0.002 - Additional scraping: ~3-5 new sources - Content verification: ~$0.003 - Report enhancement: ~$0.005 **Total per improvement**: ~$0.015 **Example**: - Initial research: $0.035 - One improvement: +$0.015 - **Total: $0.050** Still very affordable! --- ## 🔄 Multiple Improvements You can iterate multiple times: ``` Round 1: Initial research → "Find engineering culture" → Enhanced with engineering info Round 2: Review again → "Now get details about benefits" → Enhanced with benefits info Round 3: Review again → "Perfect, looks good!" → Final report saved ``` Each round adds ~$0.015 in API costs. --- ## 🎨 Example Session ```bash $ ./cogniscor.sh https://stripe.com ... [research happens] ... ╔════════════════════════════════════════════════════════════╗ ║ 📄 EXECUTIVE SUMMARY PREVIEW ║ ╚════════════════════════════════════════════════════════════╝ # Executive Summary: Stripe, Inc. ## Overview Stripe is a financial infrastructure platform... ## Key Facts **Industry:** Financial Technology (Fintech) **Founded:** 2010 ... [showing first 50 lines] ... ════════════════════════════════════════════════════════════ Is this executive summary good? (yes/no/improve) [yes]: improve Describe what you want to find or improve: Your request: Find more about their payment processing fees and pricing model ✓ Got it! I'll search for: "Find more about their payment processing fees and pricing model" 🔍 Performing focused research based on your request... 📋 Search Plan: Focus: Payment processing fees, pricing structure, transaction costs URLs to try: 4 🌐 Collecting focused information... Trying: https://stripe.com/pricing Trying: https://stripe.com/docs/pricing Trying: https://stripe.com/payments/pricing ✓ Collected information from 3 sources 🔍 Re-analyzing with focused information... ✓ Analysis complete 📝 Enhancing executive summary... ✓ Executive summary updated with focused information ✨ Research refinement complete! 📁 Results saved to: ./data/stripe/ ✓ Reports now include detailed pricing information! ``` --- ## 🎁 Benefits ### For Interview Preparation - 🎯 **Get exactly what you need** - Ask for specific info - 🔍 **Deep dives** - Focus on areas most relevant to the role - ✅ **Verify completeness** - Make sure nothing important is missing ### For Research Quality - 🤖 **AI-guided follow-up** - Smart suggestions for additional sources - 📚 **Comprehensive coverage** - Fill in any gaps - ✨ **Polished output** - Enhanced reports with focused information ### For Efficiency - ⚡ **Iterative refinement** - Improve until satisfied - 🎯 **Targeted research** - Only collect what you need - 💰 **Cost-effective** - Only pay for improvements you request --- ## 🚨 Important Notes ### Interactive Mode is Optional ```bash # Skip interactive mode (faster, automated) ./cogniscor.sh --no-interactive https://company.com # Enable interactive mode (default with AI) ./cogniscor.sh https://company.com ``` ### AI is Required Interactive mode only works with AI enabled. Without AI: - Reports are generated normally - No interactive review - No focused improvements ### Automated Workflows For scripts or CI/CD, always use `--no-interactive`: ```bash #!/bin/bash # Batch processing script for company in github.com stripe.com notion.so; do ./cogniscor.sh --no-interactive "https://$company" done ``` --- ## 🎓 Tips for Great Results ### 1. Review the Initial Summary First - Read through what was found - Identify what's missing or weak - Be specific in your improvement request ### 2. One Topic at a Time - Focus on one area per improvement - You can iterate multiple times - Quality over quantity ### 3. Use Domain Knowledge - If you're interviewing for engineering: "Find tech stack details" - If you're interviewing for sales: "Find customer base and market position" - If you're interviewing for product: "Find product roadmap and vision" ### 4. Check Focused Sources - New sources are saved with type "focused_search" - Review them to see where info came from - Helps verify quality of improvements --- ## 📊 Improvement Request Examples by Role ### Software Engineer ``` - "Get comprehensive details about their technology stack and infrastructure" - "Find information about their engineering culture and development practices" - "Look for details about their code review process and testing" ``` ### Product Manager ``` - "Find detailed information about their product roadmap and vision" - "Get insights into their product development process" - "Look for customer testimonials and product feedback" ``` ### Designer ``` - "Find information about their design system and tools" - "Get details about their design team and culture" - "Look for their design philosophy and process" ``` ### Sales/Business ``` - "Find detailed pricing and business model information" - "Get information about their customer base and market segments" - "Look for case studies and customer success stories" ``` ### Data Scientist ``` - "Find details about their data infrastructure and ML stack" - "Get information about their AI/ML team and projects" - "Look for publications or talks about their data work" ``` --- ## 🔍 How AI Plans Focused Searches When you request improvements, AI: 1. **Analyzes your request** - Understands what you're looking for 2. **Reviews existing summary** - Identifies gaps 3. **Suggests specific URLs** - Company blog, docs, careers page 4. **Creates search queries** - Targeted searches for the information 5. **Defines extraction focus** - What to look for in content 6. **Plans report enhancement** - How to integrate into summary **Example Plan for "engineering culture":** ```json { "urls": [ { "url": "https://github.blog/engineering", "reason": "Engineering blog likely has culture posts" }, { "url": "https://github.com/about/careers/engineering", "reason": "Careers page describes engineering culture" } ], "searchQueries": [ "GitHub engineering culture", "GitHub development practices" ], "extractionFocus": "Engineering practices, team structure, culture values", "reportEnhancement": "Add Engineering Culture subsection under Company Culture" } ``` --- ## ✨ Advanced Usage ### Multiple Iterations ``` Round 1: "Find engineering culture" → Enhanced Is this good? improve Round 2: "Now get benefits and compensation" → Enhanced Is this good? improve Round 3: "Add details about interview process" → Enhanced Is this good? yes → Done! ``` ### Combining with Verbose Mode ```bash ./cogniscor.sh -v https://company.com ``` See detailed logs of: - What URLs AI discovers - Why sources are chosen - What content is extracted - How reports are enhanced --- ## 🎉 Summary Interactive Mode makes Cogniscor a **collaborative research assistant**: - 🤖 AI does the heavy lifting - 👤 You guide what matters most - 🔄 Iterate until perfect - ✅ Get exactly the information you need **Perfect for interview prep** where you need specific insights about the company! --- **Try it now:** ```bash ./cogniscor.sh https://github.com # Review the summary # Request improvements as needed # Get the perfect research report! ```