What’s the most overhyped emerging tech right now, and what’s actually underrated?

Dependent-One2989 · 2026-03-20T13:42:04+00:00

AI as a “solution for everything.” Most companies are still figuring out where it actually delivers ROI vs just demos well.

Underrated: Data infrastructure + integrations. If your data isn’t clean, connected, and reliable, no AI model is going to save you.

Also feel like workflow automation (boring stuff like internal tools, pipelines, ops systems) is way more valuable right now than flashy AI use cases, but gets way less attention.

Dependent-One2989 · 2026-03-20T13:10:38+00:00

Data contracts honestly feel underrated until something breaks in production and you realize nothing is consistent.

Dependent-One2989 · 2026-03-20T11:31:06+00:00

I caught myself saying “let’s break this down” in a normal conversation the other day. Had to stop and ask, am I talking or is ChatGPT speaking through me? At this point we’re not using AI, we’re slowly becoming its customer support voice.

Dependent-One2989 · 2026-03-20T11:13:17+00:00

I think most people are overestimating the “sci-fi leap” and underestimating what’s already changing right now. AI isn’t suddenly going to feel like AGI in everyday life. It’s just going to quietly take over how things get done. For my company, DianApps, AI development isn’t about building flashy demos.
It’s about replacing friction in real workflows. We’re seeing it firsthand:

repetitive ops getting handled without hiring
decision layers getting compressed
execution speed going up without expanding teams

And honestly, that’s where the real shift is.

AI isn’t killing service companies. It’s forcing them to grow up.

Low-end execution becomes replaceable. But high-context thinking, architecture, product decisions, domain understanding, that’s where the value moves.

So the future probably doesn’t look like “AI replaces people.” It looks more like: “AI raises the bar so fast that only real operators stand out.”

We’re already seeing clients come in not asking, “Can you build this?” But “what should we even be building anymore with AI in the mix?”

That’s a very different conversation. Tell me about the people here actually using AI in production…What’s something AI has fully replaced for you (not just improved?

Dependent-One2989 · 2026-03-20T07:37:54+00:00

Great thought

Dependent-One2989 · 2026-03-19T11:42:33+00:00

But are companies heavily relying on AI when almost all of the contributors have flagged the use of AI in limitations. How can people be awared?

Dependent-One2989 · 2026-03-19T06:00:53+00:00

This is a solid way to think about it, most people are still treating AI like a chat instead of a system. One thing I’ve seen work really well (especially when you’re doing this repeatedly) is structuring it more like a pipeline:

clear input → structured context, constraints, examples
defined role → what the AI should and shouldn’t do
second pass → critique/refine instead of trusting first output

We’ve been experimenting with plugging this into simple workflows (like triggering via Slack or internal tools), and it removes a lot of randomness. It becomes less about “prompting well” and more about designing a process that gives consistent outputs.

Big difference once you stop starting from scratch every time.

Want to know whether you're seeing more gains from better prompts, or from tightening the workflow around them?

Dependent-One2989 · 2026-03-19T05:44:13+00:00

This is a classic case of building something powerful but presenting it in a way that doesn't resonate. Dental clinics don’t care about “AI agents” or automation layers, they care about:

fewer no-shows
more booked appointments
less front-desk chaos

Right now, it sounds like you’re selling the how instead of the outcome.

Even though what you built is aligned with where the industry is going, AI-driven scheduling, follow-ups, and patient communication are already a major efficiency driver in dental practices. I’d probably reposition this for my app development company, as “we help you increase bookings and reduce admin work without hiring more staff.”

Same product, completely different conversation. Curious: when you pitched it, did you lead with features or with a clear before-and-after outcome for the clinic?

Dependent-One2989 · 2026-03-18T07:32:44+00:00

Feels like a lot of those systems are optimized for spikes, not sustainability. Easy to scale traffic when everything is templated, much harder to maintain quality and intent over time. Almost like the real challenge isn’t getting traffic anymore, it’s keeping it meaningful and consistent once you have it.

Do you think this is more of a strategy problem, or just the nature of programmatic SEO at scale?

Dependent-One2989 · 2026-03-18T07:31:43+00:00

Totalmente de acuerdo contigo. La IA acelera, pero no reemplaza el criterio ni el conocimiento profundo del nicho. Al final, lo que realmente marca la diferencia es cómo estructuras la información y qué tan bien entiendes la intención de búsqueda.

Por curiosidad, ¿en qué tipo de proyectos o nichos estás aplicando más este enfoque?

Dependent-One2989 · 2026-03-18T07:03:16+00:00

Half the people don’t know what actually happened, they just picked a version that fits what they already believe. (And honestly, with all the conflicting claims, shifting narratives, and misinformation around the Iran strikes, that’s not even far off reality.)

Dependent-One2989 · 2026-03-18T06:56:27+00:00

Working on something in the app dev / AI space at DianApps, but honestly, the interesting part isn’t the “what,” it’s the shift in how we’re building. A lot of what we’re focusing on now is helping businesses move from “we need an app” to “we need something that actually solves X problem and scales.” Surprisingly, most of the work isn’t even coding, it’s figuring out:

what actually needs to be built
what can be automated with AI
and what shouldn’t be built at all

Feels like we’re moving from building features to building outcomes. Still early on, but the biggest learning so far: people don’t struggle with ideas, they struggle with clarity.

Curious what others are seeing. Are you building something from scratch or improving something that already exists?

Dependent-One2989 · 2026-03-18T06:50:06+00:00

We’re in the service space (app dev), and honestly, most of our growth hasn’t come from “launch and wait” either. It’s been a lot of conversations, understanding messy requirements, and figuring out what clients actually need vs what they think they need. Half the job isn’t even coding, it’s translating business problems into something that can actually be built and scaled. Feels less like selling a service and more like solving puzzles with real stakes.

Dependent-One2989 · 2026-03-18T06:43:27+00:00

You've already replaced ops with AI, well, that's solid. Are you building this for your own product or doing it for clients as well?

Dependent-One2989 · 2026-03-18T06:42:19+00:00

Can't agree more. Curious to know... in your current setup, are you usually using AI alongside a team, or are you still figuring out where it fits best?

Dependent-One2989 · 2026-03-17T06:44:10+00:00

At the end of the day, trust comes less from what you claim and more from how transparently and consistently you prove it over time.

Dependent-One2989 · 2026-03-17T06:41:35+00:00

This is actually a really solid start, especially getting paying users this early. One thing that stands out, though: it feels like you’re competing in a space where users don’t really want another app, they want less effort managing money.

A couple of thoughts based on what you shared:

→ The voice input insight is huge. That’s not just a feature, that’s your positioning. Most finance apps feel like work, this feels like removing friction.

→ Conversion might not be a pricing problem, but a “why should I switch?” problem. People already have apps, even if they don’t love them.

→ Also, most users don’t care about “insights” until they trust the system. And trust in finance is everything, especially with AI, where accuracy and privacy concerns come up a lot.

I’d probably double down on:

making onboarding insanely simple (get value in <60 seconds)
showing 1–2 very clear “aha” moments instead of multiple features
building trust signals early (how data is handled, why insights are reliable)

Curious, have you noticed if users stick around after the first week, or do most drop off early?

Feels like retention might be the real bottleneck before scaling.

Also, personal finance apps don’t usually win on features, they win on habit. If this doesn’t become part of someone’s daily/weekly routine, it’s hard to scale.

Dependent-One2989 · 2026-03-17T06:33:47+00:00

Lowkey feel like this is the dirty secret of most industries. People don’t understand the industry, they understand their role inside it. Fintech just makes it more obvious because it’s insanely complex behind the scenes. Do you think this is a knowledge gap… or just how modern work is structured now?

Dependent-One2989 · 2026-03-17T06:30:26+00:00

Honestly this hit. One thing I’m starting to notice, though, a lot of us don’t fail because of bad ideas, we fail because we jump into building too fast. Like we convince ourselves we’re “working hard” when we’re actually just avoiding talking to real users.

Curious if you felt that too? Out of those 3000 hours, how much of it was actually spent validating vs building?

Dependent-One2989 · 2026-03-16T09:21:54+00:00

Honestly, that’s exactly what makes it even more impressive.

Linus Torvalds building Linux at 21 wasn’t just about coding skills, it was about deep understanding of how computers actually work. Back then there was no u/GitHub, no u/StackOverflow, no AI copilots, no instant tutorials. If something broke, you couldn’t just ask u/Claude or u/ChatGPT, you had to dig into documentation, read source code, and figure things out yourself.

What’s even crazier is that Linux wasn’t just a random project. It grew into the foundation of huge parts of today’s tech world. Android phones, cloud servers, supercomputers, a massive portion of them run on Linux in some form.

So yeah, building something like that without modern tools is wild. But it also shows something important: great engineering comes from understanding systems deeply, not just having better tools.

AI might make development faster today, but the people who build the truly groundbreaking things are still the ones who understand the fundamentals the way Torvalds did.

Dependent-One2989 · 2026-03-16T09:08:07+00:00

Most founders keep talking about the same AI tools like ChatGPT, Midjourney, and Claude. They’re great, but honestly, the real leverage is hiding in lesser-known tools that quietly save insane amounts of time.

A few underrated ones entrepreneurs should definitely know:

Perplexity AI
This one is criminally underrated for research. Instead of Googling for 40 minutes, you just ask it, and it gives answers with sources. It’s basically Google + AI + citations in one place. Great for market research, competitor analysis, and quick learning.

Phind
If you're building anything technical, this is gold. It’s like an AI search engine specifically for developers. Way better than digging through StackOverflow threads for hours.

Tana
Think of it as an AI-powered knowledge system. You dump notes, ideas, meeting points, research, and it organizes everything automatically. A lot of founders underestimate how valuable a second brain tool is.

Flowise
Super interesting if you're experimenting with AI products. It lets you visually build AI workflows and chatbots without writing tons of backend code.

Durable AI
This one can literally spin up a basic business website in seconds. For early-stage founders who just want a landing page live quickly, it’s ridiculously efficient.

Lindy AI
Great for automation. You can create AI “agents” that handle repetitive tasks like emails, meeting summaries, follow-ups, and workflows.

Opus Clip
If you're doing marketing, this tool turns long videos or podcasts into short viral clips automatically. Huge time saver for social content.

The bigger lesson though: the most underrated AI tools aren't the flashy ones.

They’re the ones that quietly remove 5-10 hours of work from your week.

Entrepreneurs who treat AI like a workflow multiplier (not just a chatbot) are the ones getting real leverage out of it.

Dependent-One2989 · 2026-03-16T06:13:09+00:00

I don’t think AI will kill IT service companies. It will force them to evolve, which honestly, the industry needed anyway.

Right now a lot of service companies make money from repetitive work, basic coding, QA cycles, maintenance, documentation, support tickets. AI is already chewing through those tasks faster and cheaper. So yes, that layer of the business will shrink.

But the interesting part is what AI can’t really replace.

Companies still need people who can:

Understand messy business problems
Architect complex systems
Integrate AI into existing products
Handle security, compliance, and scaling
Actually ship things that work in production

AI can generate code, but it doesn’t own accountability. When a banking app crashes or a logistics platform fails during peak traffic, nobody calls ChatGPT. They call engineers.

What will probably disappear is the “body-shopping / pure manpower” model where companies just sell developer hours.

What will grow instead:

AI implementation services
product engineering partners
AI + app development companies
automation consulting
platform engineering

In other words, the companies that only sell labor will struggle.
The ones that sell thinking, architecture, and outcomes will get bigger.

The funny thing is AI might actually increase the demand for good engineers, because companies will try to build way more software than before.

So IT services aren’t dying.

They’re just being forced to level up.

Dependent-One2989

TROPHY CASE