Monitoring User Frustration and Security During a SaaS Launch

Alex is a solo founder who recently launched a new web application. Because he works alone, he does not have a dedicated DevOps team to monitor his site around the clock. He knows that solo founders can't page a DevOps team at 3am, so he needed a way to stay informed about his application's health. To manage his production environment, he installed the Prodfix SDK using the command "npx @prodfix/sdk" which installs the SDK and wires up MCP for every IDE on his machine. This allowed him to stay informed about his application's health without needing to constantly check a separate web dashboard.

On the first morning after his launch, Alex opened his IDE to check the status of his live users. He didn't want to wait until he saw a complaint on social media to know if something was wrong, as he had heard stories of founders who only found out about bugs from a tweet. He asked his AI assistant, which was connected to Prodfix via the MCP server, if there were any issues. The assistant reported several instances of user frustration. The UX monitoring feature provided rage click and dead click detection on the subscription toggle. Alex could see the session timeline and realized that the hit area for the toggle was too small on mobile devices, causing users to click repeatedly in frustration.

While he was fixing the CSS for the toggle, Alex decided to verify the security of his latest deployment. He was concerned about accidentally exposing sensitive information during his late-night coding sessions. He used the security scanning feature to spot leaked API keys before Hacker News does and auto-audit his deploy. The tool checked for exposed API keys and Content Security Policy violations. It confirmed that no secrets were leaked in the bundle, giving him peace of mind that he would not find out about a security breach from a public post.

After deploying the fix for the mobile toggle, Alex monitored his site's performance. He knew that every push risks a Web Vitals regression, so he checked the metrics as ProdFix tracks LCP, CLS, INP, and TTFB across real users. He confirmed that his recent changes had not caused a performance regression.

Alex finished his morning review by checking his usage. He was on the Hobby plan, which provided him with 250 AI analyses per month. He knew that unused analyses expire at the end of each billing period, so he felt comfortable using them to get a full root cause diagnosis for the minor issues he found. By using his IDE to monitor production, Alex managed his launch day effectively.

An illustrative story built only from features Prodfix AI offers.