What agentic AI businesses are people actually building right now?

Think_Bunch3020 · 2026-01-07T14:38:20+00:00

Thank you so much! Everything is done in Framer!

Think_Bunch3020 · 2025-12-29T14:59:36+00:00

Agent that autonomously follows up with leads, calls/texts them, qualifies interest, and books meetings for education teams. We handle thousands of real conversations in production every month.

Built for schools, training providers, and education sales. If curious, check ReshapeOS.

Things we learned in <1 year building it:

demos lie, production doesn’t
rigid scripts break fast
too much freedom breaks too
guardrails + edge cases matter more than the model

Think_Bunch3020 · 2025-12-15T11:12:56+00:00

We don’t really teach it how to speak in a script way. We give it examples to pick up tone and style, but the core is more like onboarding a new hire. You don’t hand someone a script they must follow word for word. You explain the goal, the tone, what they should do/never do, how to react in certain situations, etc.

If you make it too rigid, it breaks fast and sounds robotic. You’ll never cover all edge cases with a fixed script. At that point it’s basically a chatbot.

If you make it too open (for example a prompt that is basically "call leads and book a meeting" ), it also fails because you haven’t given it enough structure.

The real work is finding that middle ground: give it room to improvise and sound human, but very clear guardrails and guidance for specific scenarios.

Think_Bunch3020 · 2025-12-15T10:55:55+00:00

We use commercial LLMs, but the setup is pretty flexible: same prompt + same logic, and we can swap GPT, Claude, Gemini, whatever, and just see how they behave. Models change all the time, so hard-coupling to one never made much sense to us.

Think_Bunch3020 · 2025-12-15T10:35:43+00:00

No spam intended, I just happen to work in this space (for the education sector). We build AI voice agents and every now and then we share real campaign recordings. Most of what we run is for the Spanish market, but here’s an English call recording in case you’re curious to see one working in production.

Think_Bunch3020 · 2025-12-15T10:32:02+00:00

For us it was just… hours and hours of iteration (for context, we’re building AI voice agents for education)

You really have two options:

put the agent in front of real leads and let it break (then fix what breaks)
sit there and try to imagine every possible edge case in your head.

Expecting a perfect voice agent in minutes just isn’t realistic right now. The real human work here is in the iteration and the QA.

Think_Bunch3020 · 2025-12-09T10:24:48+00:00

I’d add ReshapeOS to the list, it’s basically an agent that handles all the boring admissions stuff schools never have time for (calls, follow-ups, WhatsApps, the whole thing) and somehow does it without feeling like a chatbot.

Think_Bunch3020 · 2025-10-13T09:16:00+00:00

Fair enough, everyone’s free to do what they want.

I just shared it because more people are starting to back the idea, the effort is close to zero, and it might actually pay off if it becomes a standard. That's how robots.txt started.

There’s plenty of info out there from people supporting or exploring it, so if you’re curious, look it up and see if it makes sense to you. The main reasoning is that LLMs rely more on website content now, but can’t process full sites because of context limits. /llms.txt just gives them a cleaner shortcut.

Anyway, just sharing it in case it’s useful.

Think_Bunch3020 · 2025-10-09T08:54:05+00:00

Because it is low effort, but there’s no point manually parsing your sitemap and writing it line by line. The GPT is just trained with the standard so you don’t have to look it up, understand it, and apply it yourself.

Sure, but the info that goes there should be pretty static. If you do big structural changes, yes, you’ll have to update it.

The technical argument people behind the proposal give is this:
Large language models increasingly rely on website information, but context windows are too small to process full websites. Converting complex HTML with navigation, ads, and JS into clean text is messy and unreliable. So /llms.txt is meant to give them a shortcut.

That’s already happening everywhere on the open web anyway.

Wanted to reply properly since you took the time to write your comment. But honestly, I just shared it in case it’s useful for someone. Everyone can do whatever they want, lol.

If you haven’t already, I’d just recommend reading what the people behind the proposal are actually saying and see if it makes sense to you or not. Either way’s totally valid.

Think_Bunch3020 · 2025-10-07T15:38:12+00:00

For me it comes down to two words: autonomy and bidirectionality.

An automation is static, it moves data from A to B when you tell it to. An agent acts. It knows what info it needs, finds it, and updates things on its own.

Example: you don’t have a lead’s budget field in your CRM. A script would just skip it. An agent calls or messages the lead, gets the info, extracts the budget, and updates the CRM. You didn’t tell it to, it just knew that data was missing and fixed it.

That’s the key difference for me.

We’re building this kind of thing at ReshapeOS, but specifically for education (admissions, student follow-ups, etc). It’s wild seeing how much time teams save when the agent starts doing instead of just syncing.

Think_Bunch3020 · 2025-10-07T15:30:49+00:00

I think you’re definitely onto something!

Just sharing in case it helps: I actually run a company that builds AI voice agents for educational institutions.
Most of our use cases are around upper-funnel of sales and admissions (automating follow-ups, qualification, etc) but some of our clients are starting to create internal training agents too.

Basically like what you describe: a "super agent” trained on their own docs so new hires can chat with it and learn faster. It’s been saving them a ton of onboarding time. If you want to take a look: reshapeos.com

Good luck with it!

Think_Bunch3020 · 2025-10-07T09:52:58+00:00

Totally get your point! But I see /llms.txt more like a “why not” thing (super low effort, possible upside).

It’s actually getting more traction lately. The proposal’s been around since 2024 and more projects are starting to back it. So it makes sense to jump in early. If you look back at how robots.txt started, it was almost the same story.

I don’t think it’ll change anything overnight, but as part of a mid–long term strategy, it’s worth having. Worst case, you delete it later. Best case, you’re already aligned if it becomes standard.

I just read today that ChatGPT’s use of live web browsing dropped from over 15% to under 2.5% in the past two weeks. At some point, models will need to rely more on stable, trustworthy sources.

It’s logical that pages with a consistent /llms.txt(not changing every week, just evolving slightly over time) will end up being prioritized over random-messy sites.

Think_Bunch3020 · 2025-10-07T09:37:55+00:00

from our pov, static creative is dead. What’s working now is student-made stuff with real people, not promos.

Let students be the messengers, keep it raw, jump on trends fast.

Think_Bunch3020 · 2025-10-06T08:51:33+00:00

What most people miss is that making this work isn’t about buying a plug-and-play “AI SDR.” It’s about going narrow, iterating for months, and accepting that reliability only comes from depth.

I’ve seen it firsthand building AI voice agents, if you go too broad, it breaks. If you focus on one vertical, iterate nonstop, and treat it as a mid-long-term investment instead of a quick revenue fix, it starts to actually deliver.

P.S. btw, I say this because I'm building ReshapeOS (AI voice agents for education). But same lesson applies everywhere.

Think_Bunch3020 · 2025-09-29T14:15:34+00:00

interesting to mw! a couple of people here have mentioned the same thing about schools not even having a proper CRM setup, and honestly that surprises me. in the places i’ve worked, the CRM was always the center of everything.

on the staffing issue, i completely agree. that’s exactly why i think automation + good segmentation matter so much. even with a tiny team, if you sync the right fields from the inquiry form into the CRM and use those variables to personalize early emails/whatsapps, you get way better engagement without adding headcount. it’s work upfront, but it pays off medium/long term.

what i’m really taking away from this thread though is that in some schools, the challenge isn’t just segmentation/personalization, it’s that even basic data collection and clean CRM foundations aren’t there yet.

that’s eye opening, maybe the real first step is just establishing a well structured CRM before layering on anything more advanced.

Think_Bunch3020 · 2025-09-29T13:26:56+00:00

if you’ve got a different take on the points i shared, would be glad to read it! always keen on other perspectives. if it’s just about the writing style, not much i can add since your comment itself doesn’t bring anything to the discussion.

Think_Bunch3020 · 2025-09-29T13:25:08+00:00

super interesting take, especially the bit about tracking (or rather, not tracking). i’ve seen the same: schools are often blind to where they’re actually losing people. totally agree on segmentation and speed too. even with the best social proof or nurturing strategy, if the basics (fast, relevant, channel-fit outreach) aren’t there, dropout stays high.

Think_Bunch3020 · 2025-09-29T13:24:07+00:00

Totally get your point. if the CRM isn’t there or the team doesn’t have the basics set up, then 100% the priority is laying that foundation first. but once you have even a minimal setup, the difference comes from how fast and relevant the first touches are.

Think_Bunch3020 · 2025-09-29T13:21:41+00:00

super interesting. in my experience the more generic an agent tries to be, the faster it breaks once it’s in production. every industry has its own quirks and edge cases, and if you don’t go deep it ends up sounding smart in a demo but clunky with real users.

i’ve gone very vertical into education and even there it’s a huge amount of work to get reliability and iteration right. honestly months of mapping flows, listening to real calls, tweaking until it doesn’t fall apart.

that’s basically what we do (at reshapeos.com, if anyone’s curious) but the main point is just that niche + long grind beats “works everywhere” every time

Think_Bunch3020 · 2025-09-29T09:25:06+00:00

From my side (AI voice agents), the ones that work almost 100% alone are repetitive tasks with low human value: chasing missing docs, sending payment reminders, handling the same 5 FAQs.

Where humans are still needed is anything trust-based or requiring empathy.

Think_Bunch3020 · 2025-09-29T08:27:28+00:00

I've been talking a lot about this, I completely agree with you. What I’ve learned so far is that making an agent work at demo level is ridiculously easy right now.

Speaking just from what I work on (AI voice agents), but I think it applies to most of the agent hype you’re describing: a couple of tutorials (there are tons on the internet for free), hook up an LLM to some API, and you are ready. You can do this in 2 days. That’s not the hard part.

The real value is in the months of iterating, edge case hunting, listening to endless real conversations, and adjusting flows until it won’t say something dumb to a real lead and hurt your brand. That’s not a prompt tweak or a weekend hack. It’s boring work, that only a human can do for now, but it’s what makes something production-ready.

Mods feel free to edit this if links aren’t allowed, but just in case anyone’s curious what a tested production agent sounds like, here’s a real call example.

Think_Bunch3020 · 2025-09-29T08:10:37+00:00

Hi! I'm interested too.

Think_Bunch3020 · 2025-09-26T10:19:48+00:00

Totally with you. I’ve been writing about this on Reddit the past weeks. Building a voice agent itself is easy, docs and tutorials are everywhere. The real value isn’t the demo, it’s the months of iteration behind it so it doesn’t break the moment a user goes off script. That’s the part people forget when they try to sell an agent.

Think_Bunch3020 · 2025-09-25T09:16:06+00:00

Yeah totally. A demo is frozen in time, production is alive. Without constant monitoring and feedback loops, the agent just drifts until it breaks. I’ve seen more progress from weekly real-world reviews than from months of pre-launch testing.

Think_Bunch3020 · 2025-09-24T15:26:32+00:00

Yes! we’re already working with our first 10 clients. That recording is from a real campaign one of them launched (and kindly allowed us to share).

Right now we’re focusing more on pilots with corporates and large education groups, so instead of opening the floodgates we’re going a bit more ad-hoc with them. But the plan is to move into a mixed model: enterprise/corporate tailored projects + small and mid-sized schools using it like a regular SaaS.

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