Uploaded March 2026 | Updated September 2026, 3 weeks ago
🌐 Sign Up For Bright Data (coupon code "leonvanzyl" for $20 credit):
brdta.com/leonvanzyl
Learn how to build an AI brand monitoring app with Claude Code, Bright Data, Next.js, and Inngest.
🎁 My FREE 7 Day AI Builder Challenge - learn my RAMP workflow and ship a real app in a week 👇
skool.com/leonvanzyl
🚀 Free resources: source code, prompts, workflows + peer discussion: skool.com/leonvanzyl
🧪 Agentic Labs: AI coding courses, live Q&A, weekly builder challenges, direct access to me + a serious builder community: skool.com/agentic-labs
In this video, I walk you through my entire thought process for identifying a real business opportunity and building a sellable product using coding agents. We build an AI brand monitoring app that scrapes real responses from ChatGPT, Perplexity, Gemini, Grok, Copilot, and Google Search to track whether a brand is being recommended by AI platforms. You will learn how to use Bright Data AI web scrapers to collect actual user-facing responses, implement context engineering to get better results from your coding agent, and use Inngest to run background jobs with retry logic and concurrency limits at scale.
📦 Boilerplate GitHub Repository: github.com/leonvanzyl/brand-monitor-tutorial
🔍 Search Everywhere Article:
searchengineland.com/search-everywhere-new-seo-reality-472134
📦 Unified LLM Scraper Repository:
github.com/brightdata/brightdata-agent-showcase/tree/main/agents/seo/unified-llm-scraper
📃 Build an LLM Mentions Tracker Tutorial:
brightdata.com/blog/ai/build-an-llm-mentions-tracker
🌐 Bright Data Web Scraper APIs:
brightdata.com/products/web-scraper
🌐 Bright Data SERP API:
brightdata.com/products/serp-api
📃 AI Scrapers Overview Documentation:
docs.brightdata.com/datasets/scrapers/scrapers-library/ai-scrapers
📃 Async Trigger Endpoint:
docs.brightdata.com/api-reference/rest-api/scraper/asynchronous-requests
📃 Monitor Progress Endpoint:
docs.brightdata.com/api-reference/scrapers/management-apis/monitor-progress
📃 Snapshot Data Download:
docs.brightdata.com/api-reference/scrapers/management-apis/snapshot-data
⚡ Inngest Next.js Documentation:
inngest.com/docs/getting-started/nextjs
⏰ TIMESTAMPS:
00:00 AI brand monitoring app demo
00:57 Why brands need AI mention tracking
02:57 Identifying the business opportunity
03:08 Why scraping beats API calls
06:09 Project setup and boilerplate walkthrough
09:00 Bright Data AI web scrapers explained
14:01 Setting up Bright Data in the project
17:14 Context engineering your coding agent
21:25 First scan results and debugging providers
26:16 Adding Inngest for background job processing
30:25 Final demo with parallel scraping and Inngest dashboard
31:55 Challenge and next steps
Business & sponsorship enquiries: leon@cognaitiv.ai
#claudecode #vibecoding #agenticcoding
🌐 Sign Up For Bright Data (coupon code "leonvanzyl" for $20 credit):
brdta.com/leonvanzyl
Learn how to build an AI brand monitoring app with Claude Code, Bright Data, Next.js, and Inngest.
🎁 My FREE 7 Day AI Builder Challenge - learn my RAMP workflow and ship a real app in a week 👇
skool.com/leonvanzyl
🚀 Free resources: source code, prompts, workflows + peer discussion: skool.com/leonvanzyl
🧪 Agentic Labs: AI coding courses, live Q&A, weekly builder challenges, direct access to me + a serious builder community: skool.com/agentic-labs
In this video, I walk you through my entire thought process for identifying a real business opportunity and building a sellable product using coding agents. We build an AI brand monitoring app that scrapes real responses from ChatGPT, Perplexity, Gemini, Grok, Copilot, and Google Search to track whether a brand is being recommended by AI platforms. You will learn how to use Bright Data AI web scrapers to collect actual user-facing responses, implement context engineering to get better results from your coding agent, and use Inngest to run background jobs with retry logic and concurrency limits at scale.
📦 Boilerplate GitHub Repository: github.com/leonvanzyl/brand-monitor-tutorial
🔍 Search Everywhere Article:
searchengineland.com/search-everywhere-new-seo-reality-472134
📦 Unified LLM Scraper Repository:
github.com/brightdata/brightdata-agent-showcase/tree/main/agents/seo/unified-llm-scraper
📃 Build an LLM Mentions Tracker Tutorial:
brightdata.com/blog/ai/build-an-llm-mentions-tracker
🌐 Bright Data Web Scraper APIs:
brightdata.com/products/web-scraper
🌐 Bright Data SERP API:
brightdata.com/products/serp-api
📃 AI Scrapers Overview Documentation:
docs.brightdata.com/datasets/scrapers/scrapers-library/ai-scrapers
📃 Async Trigger Endpoint:
docs.brightdata.com/api-reference/rest-api/scraper/asynchronous-requests
📃 Monitor Progress Endpoint:
docs.brightdata.com/api-reference/scrapers/management-apis/monitor-progress
📃 Snapshot Data Download:
docs.brightdata.com/api-reference/scrapers/management-apis/snapshot-data
⚡ Inngest Next.js Documentation:
inngest.com/docs/getting-started/nextjs
⏰ TIMESTAMPS:
00:00 AI brand monitoring app demo
00:57 Why brands need AI mention tracking
02:57 Identifying the business opportunity
03:08 Why scraping beats API calls
06:09 Project setup and boilerplate walkthrough
09:00 Bright Data AI web scrapers explained
14:01 Setting up Bright Data in the project
17:14 Context engineering your coding agent
21:25 First scan results and debugging providers
26:16 Adding Inngest for background job processing
30:25 Final demo with parallel scraping and Inngest dashboard
31:55 Challenge and next steps
Business & sponsorship enquiries: leon@cognaitiv.ai
#claudecode #vibecoding #agenticcoding
