Hi, Slobodan here. I run a PTO/leave-management SaaS (Vacation Tracker, bootstrapped, profitable) with my co-founder for almost 8 years now, and this started as our internal tool.
We monitor competitors' websites and changes from the very beginning. It's one of the most annoying jobs (similar to PTO tracking), but we are not that bad at turning annoying things into products.
With some help, we shipped a prototype almost a year ago and shared it with a few friends. The idea was simple: get a short email with competitor website changes that actually matter every Monday morning. And 6 months later, everyone with access to the tool actually read these emails every week, so we decided to convert it into a real product MVP. But we built it in a way that's API and MCP-first, because we don't want another dashboard we need to log in to. The goal is to create a product with just 2 founders and a bunch of AI agents (we have 22 employees in Vacation Tracker, we want to see how far a product can go without hiring).
What Competitor Tracker does: we crawl competitor pages, store full snapshots (HTML, MDs, and screenshots), diff them, then classify each change (pricing, features, positioning, etc.) and write a short explanation with before/after evidence. We already track 2,000+ SaaS companies across 137 categories. In addition to that, we try to pull an older snapshot so new users have some results after ~15 minutes, instead of waiting a few weeks.
Everything is built using Cloudflare. We use Workers, D1, R2, Browser Rendering, AI Gateway, etc. I spent about a decade doing AWS serverless and co-wrote a Manning book on it, and this is my first product built entirely on Cloudflare instead. Happy to go deep on that tradeoff.
Honest limitations: extraction isn't perfect. We caught markdown extraction mangling prices, so price detections are now verified against screenshots. Error pages used to create phantom "changes" until we made them a distinct state. Classification sometimes overstates a page edit as a product change. JS-heavy sites are still hit and miss. We run automated QA passes on random samples to prevent users from seeing incorrect results.
Another cool thing was building a website and the product in a film noir detective theme with various checks (LLMs + deterministic) for voice and rules.
If this tool is useful to anyone else, feel free to sign up on the link above. You'll get 25 credits (we call them coins) for free (1 coin = 1 competitor/month). And just ping me if you need more credits.
slobodan_•45m ago
We monitor competitors' websites and changes from the very beginning. It's one of the most annoying jobs (similar to PTO tracking), but we are not that bad at turning annoying things into products.
With some help, we shipped a prototype almost a year ago and shared it with a few friends. The idea was simple: get a short email with competitor website changes that actually matter every Monday morning. And 6 months later, everyone with access to the tool actually read these emails every week, so we decided to convert it into a real product MVP. But we built it in a way that's API and MCP-first, because we don't want another dashboard we need to log in to. The goal is to create a product with just 2 founders and a bunch of AI agents (we have 22 employees in Vacation Tracker, we want to see how far a product can go without hiring).
What Competitor Tracker does: we crawl competitor pages, store full snapshots (HTML, MDs, and screenshots), diff them, then classify each change (pricing, features, positioning, etc.) and write a short explanation with before/after evidence. We already track 2,000+ SaaS companies across 137 categories. In addition to that, we try to pull an older snapshot so new users have some results after ~15 minutes, instead of waiting a few weeks.
Everything is built using Cloudflare. We use Workers, D1, R2, Browser Rendering, AI Gateway, etc. I spent about a decade doing AWS serverless and co-wrote a Manning book on it, and this is my first product built entirely on Cloudflare instead. Happy to go deep on that tradeoff.
Honest limitations: extraction isn't perfect. We caught markdown extraction mangling prices, so price detections are now verified against screenshots. Error pages used to create phantom "changes" until we made them a distinct state. Classification sometimes overstates a page edit as a product change. JS-heavy sites are still hit and miss. We run automated QA passes on random samples to prevent users from seeing incorrect results.
Another cool thing was building a website and the product in a film noir detective theme with various checks (LLMs + deterministic) for voice and rules.
If this tool is useful to anyone else, feel free to sign up on the link above. You'll get 25 credits (we call them coins) for free (1 coin = 1 competitor/month). And just ping me if you need more credits.
Feedback is more than welcome!