The mistake is committing too early. Start with one agent, learn where it struggles, then split off specialists for the tasks that need deeper accuracy or domain knowledge. That way you’re not over-engineering before you understand real usage, and you’re not stuck with a jack-of-all-trades that’s mediocre at everything. One interface, many skills just build the seams in from day one.

I’ve noticed the shift from “tools I operate” to “teammates I delegate to.” The bar really is different I’ll forgive a clunky dashboard, but an agent that takes a wrong action erodes trust fast. What’s interesting is that the best ones seem to know their limits and ask before acting, which paradoxically makes them feel more capable, not less. I don’t think they’re just add-ons anymore, but I also don’t think every SaaS needs one. The ones that earn their place are where the work is repetitive and the context is rich enough for the agent to actually be useful. Curious whether others are seeing the same trust dynamic.

Absolutely — I think AI agents could genuinely become the new “search engine” for online shopping. Instead of juggling ten tabs, comparing prices, and scrolling through fake reviews, you’d just tell your AI what you need and let it do the digging. It’s convenient, and honestly, kind of inevitable.

• This reply was modified 1 week ago by  Christabell.