Share your best AI workflow. We could show it to 2M+ people.

The new ChatGPT Chrome extension is surprisingly good at navigating complicated technical settings. My favorite use case so far has been using it to create the special DNS records for a new website. This has always been confusing, even though I’ve done it dozens of times. The process varies across platforms, every DNS registrar uses different names for records such as A and CNAME records, and the interfaces are constantly changing. It’s tedious and easy to get wrong. For this kind of one-off, highly detailed technical task, I copy and paste the specific instructions from my website host provider into the extension while I’m logged in to my DNS provider. GPT then takes control of the mouse and fills in the required fields. The use cases are endless, from filling out an expense report to handling other tedious tasks in legacy or old-school software that doesn’t have a simple CLI, MCP, or API connection. If AI can’t control a system directly through the backend, browser control closes another gap. These legacy systems often lack newer integrations, which also makes them annoying, tedious, and frustrating to use. That makes them particularly good tasks to give to AI—especially now that the ChatGPT Chrome extension is good at following instructions and completing actions in the browser. Step-by-step: 1. I log in to my DNS provider. 2. I copy and paste the specific DNS instructions from my website host provider into the ChatGPT Chrome extension. 3. I let GPT navigate the DNS provider’s interface and take control of the mouse. 4. GPT fills in the required fields for records such as A or CNAME records, accounting for the registrar’s particular interface. 5. I use the same approach for other detailed, repetitive tasks in legacy software that lacks CLI, MCP, or API connections.

A friend who had just started a pet-sitting and dog-walking business asked me to build a booking app. I used Google AI Studio to design the initial prototype. The process was straightforward, and I had a basic working system running within two hours. AI Studio created a Firebase database to store the details and was also effective at designing frontend changes. It published the app for me, and the resulting UI was intuitive. After demonstrating the app, I identified many additional features that needed to be added. This went beyond AI Studio’s capabilities, so I exported the code from AI Studio and started using Claude. I asked Claude to analyze the code and suggest the required changes. Claude identified critical security flaws in the database. I fixed them manually at first, but then realized that Claude could access the Firebase database and fix issues automatically. I continued prompting Claude with additional feature requests, and it built them. There were errors along the way, so I needed to be familiar with Google Chrome’s developer tools to copy the errors and ask Claude how to fix them. I used MailJS for email templates and Resend for email transport. I stored the app in GitHub and allowed Claude to access the repository so it could commit changes automatically. I ran the app locally with npm during development and then hosted it on Vercel. Eventually, I purchased an inexpensive domain name, and the app is currently hosted at Names. One major problem was that when Google AI Studio created the Firebase database, the permissions were locked, preventing me from making administrative changes. I solved this by recreating the database and asking Claude to write the SQL query to set it up. The permissions were still tricky, and I had to continue asking Claude to correct them. Google’s service permissions can be difficult to understand, and finding the correct settings was not always easy. Firebase was also complex to navigate, and getting the permissions configured correctly took time. Once I allowed Claude to connect to the app and its background services through the Google plugin, development became much faster. However, you need to trust the tool carefully and always work on a copy of the live app. Overall, I think app development with Google AI Studio and Claude is impressive. You can create professional apps quickly. I come from an IT support background, though, and I think people who are new to IT may find it difficult to troubleshoot errors without a basic understanding of networking and systems administration. I also built a litter-tracking app using ChatGPT, and it was equally effective. I eventually started using Codex and Claude Code, but I think standard Claude and ChatGPT are more intuitive for nontechnical users. Step-by-step: 1. I used Google AI Studio to create an initial booking-app prototype for a pet-sitting and dog-walking business. 2. I used the Firebase database created by AI Studio to store the app’s details and used AI Studio to design frontend changes. 3. I published the initial app with AI Studio and demonstrated it to identify additional features. 4. I exported the code from AI Studio and asked Claude to analyze it and suggest changes. 5. I addressed the critical database security flaws identified by Claude, first manually and later by allowing Claude to access the Firebase database. 6. I prompted Claude to build additional features and used Google Chrome’s developer tools to copy errors and ask Claude for fixes. 7. I recreated the Firebase database when AI Studio’s locked permissions prevented administrative changes, then asked Claude to write the SQL query to set it up. 8. I used MailJS for email templates and Resend for email transport. 9. I stored the app in GitHub and allowed Claude to commit changes automatically. 10. I ran the app locally with npm during development, hosted it on Vercel, and later purchased an inexpensive domain name that is currently hosted at Names. 11. I connected Claude to the app and background services through the Google plugin, while continuing to work on a copy of the live app.