u/rohitprakash91

I've been talking with a lot of eCommerce store owners lately, and one thing keeps standing out.

Most are obsessed with getting more traffic.

More Meta ads.
More Google ads.
More influencers.

But very few look at what happens after someone lands on the store.

Customers ask about shipping.
They ask if a product is in stock.
They compare sizes.
They want to know about returns.
Sometimes they just need reassurance before buying.

If those questions aren't answered quickly, many simply leave.

It made me think that maybe the real bottleneck isn't traffic.

Maybe it's the buying experience.

For those running an online store:

Where do you think you're losing the most customers?

• Before they visit?
• During checkout?
• After they ask a question?
• Somewhere else?

I'd love to hear what you've noticed from your own data.

Everyone talks about the cost of advertising.

Almost nobody talks about the cost of missing the phone.

Imagine you're looking for a plumber, dentist, lawyer, or restaurant. You call one business.

No answer.

Maybe it rings for 20 seconds. Maybe you get voicemail.

What do you do next?

You call the competitor.

That's the hidden cost of a missed call. It's not just one unanswered phone call, it's a customer who may never come back.

I've noticed that many local businesses invest thousands in SEO, Google Ads, and social media to generate leads, but they still lose potential customers because no one is available to answer the phone.

And the frustrating part?

Most callers don't leave a voicemail. They simply move on.

This is where AI can actually solve a real business problem—not by replacing people, but by making sure every caller gets an immediate response, basic questions are answered, appointments are booked, and urgent inquiries are routed to the right person.

Of course, AI isn't the answer to every conversation. Complex issues, complaints, and relationship-building still need humans.

But missing calls because everyone is busy? That's a problem technology can solve today.

I'm curious, when a business doesn't answer your call, do you try again later, leave a voicemail, or immediately call the next business on the list?

If I bought a local business tomorrow, I wouldn't start by automating everything.

I'd start with the tasks that waste time every single day.

Here's my priority list:

1. Answering phone calls
Every missed call is a potential customer. An AI voice agent can answer instantly, qualify the caller, answer common questions, and book appointments—even after business hours.

2. Responding to website visitors
Most people won't wait hours for a reply. An AI chatbot can answer FAQs, collect lead information, and direct visitors to the right service in seconds.

3. Appointment scheduling
Back-and-forth messages to find a suitable time are unnecessary. Let customers book available slots automatically.

4. Lead follow-up
A surprising number of businesses lose leads simply because nobody follows up. Automated email, SMS, or WhatsApp reminders can keep conversations moving without someone manually checking every inquiry.

5. Repetitive admin work
Things like updating spreadsheets, sending invoices, creating CRM records, or notifying team members don't need human attention every time.

Notice what's not on the list.

I wouldn't automate sales conversations that require trust. I wouldn't replace skilled employees. And I definitely wouldn't automate a broken process just because AI makes it possible.

Good automation removes repetitive work so people can focus on work that actually creates value.

If you owned a local business, what would you automate first and what would you never automate?

I see a lot of businesses saying they "have an AI chatbot", but most of the time it's just a glorified FAQ page.

You ask it something, it gives you an answer, and that's the end of the conversation.

That's a FAQ bot.

A revenue bot behaves differently.

Instead of just answering questions, it tries to move the conversation forward.

Someone asks about pricing? It explains the options and asks what they're looking for.

Someone visits your website at 11 PM? It captures their details instead of letting them disappear.

Someone wants to book a demo? It qualifies them and schedules an appointment.

It remembers context. It asks follow-up questions. It guides people instead of waiting for perfect prompts.

Honestly, most businesses don't have a lead problem.

They have a response problem.

Paying for ads and SEO just to send people to a website that says -Fill out this form and we'll get back to you- feels crazy when visitors expect answers immediately.

A chatbot that only answers questions saves support time.

A chatbot that captures leads and moves prospects through the funnel actually makes money.

Big difference.

Curious how others are using AI chatbots right now. Are they actually generating revenue, or are they just answering FAQs?

I've noticed something funny.

Whenever a chatbot gives a bad answer, everyone's first reaction is:

These models still suck.

But after building a few chatbots, I've realized that most of the time the model isn't the problem.

We're the problem.

People expect AI to work like magic.

They throw a bunch of PDFs into a vector database, write a quick prompt, and expect the bot to answer everything perfectly.

Then it starts making things up and suddenly "GPT is unreliable."

Honestly, if you hired a new employee, handed them 300 documents, gave them zero training, and expected them to answer every customer question flawlessly, they'd fail too.

AI is no different.

Bad answers usually come from things like:

• Poor chunking
• Retrieving irrelevant information
• Weak system prompts
• Trying to make one agent do 50 different jobs
• Not giving the bot permission to say I don't know

One thing I've learned is that simple systems often outperform fancy ones.

Sometimes a basic workflow and a few AI calls beat a giant "autonomous agent" that's trying to be everything at once.

LLMs aren't perfect.

But a lot of AI hallucinations are really design mistakes wearing an AI costume.

Curious if others building chatbots have noticed the same thing, or if you've run into different issues.

I genuinely believed you could just connect:

STT → LLM → TTS

And boom, you have a voice agent.

After building actual systems, I realized that's maybe 20% of the problem.

The other 80% is stuff nobody talks about:

• Users interrupt.
• APIs fail.
• Models hallucinate.
• Latency kills conversations.
• Tool calls break.
• Context gets lost.
• People ask things you never expected.
• Customers don't care how "smart" your stack is. They only care if the task gets done.

The biggest lesson?

Most AI products don't fail because of bad models.

They fail because people underestimate engineering.

Sometimes a boring workflow with a few if-else statements beats a "fully autonomous AI agent."

And honestly, I think we're still in the "Flash websites" era of AI.

Lots of demos.

Very few production systems.

Curious:

What's one thing AI hype made you believe that turned out to be completely wrong?

I've been using Hermes Agent for 3 months now and it's completely changed how I work with AI.

Hermes is open-source (MIT licensed), self-hostable, and has persistent memory that actually remembers your projects across sessions. Unlike chatbots that forget everything, Hermes builds skills automatically from your experience.

Key features I love:
- Runs from Telegram, Discord, WhatsApp, Slack — one agent everywhere
- 60-second setup with one curl command
- 200+ AI models you can switch between
- Cron scheduling in plain English ("every night at 2am")
- Subagents for parallel work
- No vendor lock-in, no tracking, all data stays local

Built by Nous Research, and it genuinely gets smarter the longer you use it.

Been comparing it with Vapi, Retell, and other paid platforms — Hermes is way better for what it offers.

Anyone else using Hermes Agent? What's your favorite feature?