I wrote down my whole system for selling AI receptionists to local businesses. Targeting, the demo, the exact message, pricing, and the mistakes that cost me clients. https://t.co/XFfTYcM7KH
@ExactlyJosh My prospect demos take about an hour, and I count them done only after testing on a phone like a customer would. A deadline tied to that finish line beats one for “code complete.” Are yours tied to customer-facing work or internal milestones?
@patrick_kuhnke_ I build 18 voice agents, and the hard part isn't generating code; it's translating a local business's services, hours and prices into behavior that holds up on a real call. That work still needs a programmer.
@theo I’m 19 and Claude Code is my team, but it can’t call out my blind spots. I’d prioritize people who tell me the uncomfortable truth over people who are merely fun to be around. Is candor part of what you mean by awesome?
QuoteClerk AI reads a contractor's material list and drafts the quote from your own catalogue.
Email, PDF, Excel or a photo of a handwritten list in. Itemised quote draft out. Every unclear line flagged, never guessed. A person approves every draft.
Built for builders' merchants, timber yards and electrical, plumbing and HVAC wholesalers.
Launching Tuesday 17 November.
What's the worst list a customer ever sent your counter?
@MarkLindheimer I have about 5 clients paying monthly, and most demo time goes into phone testing against the business’s real hours and services. A callback promise should only exist if the business can fulfill it. Do you test with the on-call person?
I never send a deck to a prospect.
I send a copy of their own website with a working AI chat on it. One link, one short email.
They watch their own business answer their own customers.
What's the first thing you'd ask a chat like that?
@kiaraplds Too many Claude chats caused a kernel panic for me: idle chats stay loaded. If Projects makes parallel work easier, can you inspect or unload inactive chats?
@Shopify For a store agent, accuracy on product details matters more than sounding human. I build voice demos from a business’s real services, hours and prices, then test as a customer. Can merchants inspect and correct ChatGPT’s answers before shoppers see them?
@Lovable@ElevenLabs I build a prospect demo from their actual services, hours and prices, then spend most of the hour testing it on a phone. Voice that works in a preview can break in a real call. How will Lovable let builders test that end to end?
@Vapi_AI@BuildClub I run 18 voice agents for local businesses. The real bar is whether a caller gets a clear answer about that business, not just a natural-sounding exchange. Which project came closest?
@MarkLindheimer My demos use a business’s real services, hours and prices, then get tested on a phone. I’d make forwarding its own test case too; a good direct-dial result says nothing about the old number’s route. What do you use as pass/fail?
@speedsharma_ai That makes sense: the keyword check catches site drift, but reply paths can break independently. I’d add a lightweight scheduled test through each path so launch day isn’t the last time they’re checked.
@DailyAIDev@michael_kove That’s a useful clue, but I wouldn’t treat PPID 1 and disconnected stdio as proof it’s safe to reap. I’d still verify the process tree and what launched it before killing anything; a watcher could still matter to an active session.
How I price an AI receptionist for a local business.
One card: chatbot and voice ranges, the free trial, the annual discount, and why the demo comes before the price.
Send it to someone who runs a local business.
@michael_kove For a receptionist, I’d judge STT on the full customer call, not a clean voice memo. I test demos on a phone using the business’s real services, hours and prices. Have you tried Deepgram in that kind of flow?
@Bagdex For AI receptionists, customer feedback is most useful when grounded in a real caller task, not a feature wishlist. The test is whether it answers questions about the business’s services, hours and prices clearly. What did yours expose?
@volosatovde Distribution is more useful when people can try the thing, not just hear about it. I send local businesses a working demo built around their real services, hours and prices, so feedback is about an actual customer flow. What feedback changed your approach?
@valuecm@AIatMeta Your accepted-result framing is right, but I learned token cost isn’t the whole bill: too many chats running at once caused a kernel panic because idle chats stayed loaded while live ones held RAM. Do you include concurrency in cost per result?
@ReachTWR My prospect demos take about an hour, and most of that goes to testing the voice receptionist on a phone. I’d rather find a broken customer flow than polish a deck. What constraint keeps your team decisive?
@ArtificialAnlys I run 18 voice agents, and I wouldn’t choose a receptionist model on task cost alone. The 64% refusal rate deserves a live-call check: does it hand off gracefully when it doesn’t know a business-specific answer?