u/Mammoth-Row4460

run a small wholesale/distribution business with a growing list of b2b customers on terms. As volume goes up, ar is getting messy: repeat orders, partial shipments, returns and credit notes, and the same accounts that drift late but are still too important to just cut off. Right now everything lives in the accounting system’s AR module plus a couple of spreadsheets to track edge cases. I’m trying to decide whether it’s worth adding dedicated accounts receivable software that fits wholesalers and distributors better, or if that just means one more system to feed and reconcile.
If you stayed on the built‑in ar and made it work, or if you switched to a separate AR tool and actually felt the difference in how you manage invoices and collections, I’d be interested in how it played out over a few months.

We recently tried to simplify our demo booking flow and accidentally pushed a routing rule that sent all signups straight into the calendar, regardless of fit or region. For a short window, even enterprise leads were getting booked with the wrong owners. Marketing initially thought we had improved conversion rates, because demo bookings suddenly increased. But once we looked closer, a big chunk were duplicates, misrouted, or completely irrelevant meetings. The worst part is one of our highest priority target accounts went through the broken flow during that window.

Does anyone know how would we fix this?

We're in a weird position where our email list is growing but our deliverability metrics have started slipping over the past few months. we're already cleaning inactive subscribers, verifying emails and following most of the usual best practices but I keep wondering if the issue starts much earlier in the customer journey. we spend a lot on paid traffic, yet only a small percentage of visitors ever identify themselves, so we're constantly trying to squeeze more emails out of popups and forms.

 we've moved past chatbot-style llm stuff into agents that update records, call internal apis, and touch prod-adjacent systems. agentic ai security is the term getting thrown around for this but nobody at my company has a clear answer on what it means in practice.

most of what's written about ai security still assumes the risk is the model saying something bad. that's not our risk anymore. our risk is an agent doing something bad, updating the wrong record or calling the wrong api.

the stack we're piecing together starts with scoped identities per agent instead of one shared service account. on top of that we want a policy layer that sees the tool calls themselves, not just the text going in and out. and we need logging that ties an instruction to the action it triggered so an incident is reconstructable.

i can't tell if this is a mature space yet or if everyone's duct-taping it together like we are. for people running agents wired into real internal systems, what does your security stack look like end to end?

Sometimes we try something with low expectations, and it ends up becoming one of our favorite ways to spend time.

What's a hobby you were skeptical about at first, but now genuinely love? What changed your mind?

I'm always curious how people discover hobbies they never expected to enjoy.