I’ve been thinking about developing an AI assistant that handles OAuth authentication differently than what I see out there. The concept is pretty simple but I can’t find anyone doing it this way.
Basically, I want to build something where the AI asks for permission each time it needs to access a service. So if I tell it to analyze some data and save it to my Airtable, it would prompt me for Airtable access, do the work, then immediately delete those credentials. Next time I need Airtable access, it asks again.
Same thing for other platforms like Facebook, Microsoft tools, or whatever else. The AI would request OAuth permission, complete the specific task, then wipe the access token completely.
The main benefits I see are better security, clear tracking of what gets accessed, and giving users control over permissions in real time instead of granting permanent access.
I’ve looked around but most AI tools either don’t integrate with external APIs properly, or they’re stuck in one ecosystem like Google Workspace. Even the big platforms seem to avoid this approach.
Am I missing something obvious about why this pattern isn’t popular? Has anyone seen similar projects or working on something like this themselves?
Would love to hear your thoughts on this approach.
i get where ur coming from, but it also depends on the use case. if it’s for sensitive tasks, i can see the value. but u definitely need to balance security with user experience. people want seamless interactions, not hurdles, ya know?
This is actually a solid approach and I’ve seen variations of it work well in enterprise environments. The reason it’s not common comes down to friction and implementation complexity.
Most users hate re-authenticating constantly, even if it’s more secure. We tried something similar at my company for internal tools and the pushback was immediate. People want to say “analyze my spreadsheet” not “analyze my spreadsheet and oh wait let me authenticate again”.
The technical side is tricky too. You need robust token management, proper cleanup mechanisms, and handling for when tokens expire mid-task. Plus OAuth flows can be finicky - some services have rate limits on auth requests that could break your model.
That said, there’s definitely a market for privacy focused tools. The key is making the auth flow as smooth as possible. Maybe batch requests or use shorter-lived tokens instead of immediate deletion.
I’ve seen some success with hybrid approaches where users can choose between convenience mode (persistent tokens) and privacy mode (temporary tokens) based on the sensitivity of their task.
The regulatory landscape is pushing more companies toward this kind of thinking too, especially in healthcare and finance. You might be ahead of the curve here.
The friction argument is valid but I think you’re onto something that major players avoid for business reasons rather than technical ones. Persistent OAuth tokens are incredibly valuable for data mining and user tracking - companies don’t want temporary access when they can get permanent insight into user behavior. I actually prototyped something similar last year for a client who needed HIPAA compliance. The constant re-auth was annoying at first but users adapted quickly when they understood the privacy benefits. The bigger challenge was handling partial failures when tokens expired during complex multi-step operations. One pattern that worked well was grouping related operations into “sessions” where the user could grant temporary access for a defined time window rather than per-request. So instead of authenticating for every Airtable interaction, you’d get 30 minutes of access for the current workflow. The technical implementation isn’t as complex as it seems if you design for it from the start. Most OAuth headaches come from trying to retrofit temporary auth onto systems built for permanent tokens. Your approach could actually simplify a lot of the token refresh and storage complexity that enterprise applications struggle with.
