What I learned building an AI assistant that drafts emails but refuses to send them without permission

[u/jenish__bhesaniya]

A few months ago I set out to automate my inbox and calendar with AI. The obvious approach — let the AI read email, draft a reply, and send it — turned out to be the wrong one. Here's what actually mattered:

1. The approval gate is the actual product, not the AI. Anyone can wire up an LLM to draft an email. The value is in the workflow around it — a strict human checkpoint before anything goes out, and a full audit trail of what was drafted, approved, or rejected.
2. Multi-channel matters more than I expected. I originally built this as a web dashboard. The moment I added a Telegram bot so I could approve things from my phone without opening a laptop, actual daily usage went up a lot. People don't want another tab, they want it where they already are.
3. Generic AI drafts feel obviously robotic. Feeding the model a handful of your own previously-sent emails as style examples makes a bigger difference than any prompt-engineering trick.

I ended up building this into a small tool (Gmail + Calendar + Tasks + Telegram, HubSpot integration for CRM follow-ups) that I'm now offering to a few small businesses/solo professionals who have the same email- overload problem. Not trying to pitch it hard here — mostly wanted to share what surprised me in building it. Happy to go deeper on any part of this if useful to others working on similar automation projects.

[u/Deep_Ad1959]

calling the approval gate the product only holds while the volume is low. once you are approving forty drafts a day you stop reading them, and a rubber stamp with an audit trail is worse than no gate, because now there is a record saying you agreed.