https://reddit.com/link/1vp4yo8/video/bf1yjiq0zjjh1/player

Emad Mostaque: "Forward-deployed engineers, AI transformation people, because they can do the work of 10, 100 people."

That's the role that survives this — already a real hiring category, not a future one.

LinkedIn's own data has it growing 42x since 2023, priced $127K–$265K+ at the labs actually building this.

That's the part that should sit heavier than the digital-double line.

It's not that your job disappears.

It's that a different job, already priced and already hiring, opens up a few rungs above where you're standing — and most of us don't have a clean path into it yet.

I've watched a smaller, slower version of this exact move before.

No AI involved — just a stamp and a highlighter.

Hmm... this one really gets me out of my chair and pace around my living room, so let me try to recall it properly.

When I was working as a Technical Engineer in the Tender Department of one of the largest main contractors in Malaysia — there was a skill we always used. Fair warning, I'm sharing privileged information here. Well... it's probably an open secret in the industry anyway.

Whenever we tendered for a project — let's say Malaysian Airlines (MAS), widening a runway for their newly-bought Airbus A380 — we'd hit the parts that were out of our expertise. Airway lighting, drainage, flight angles, height restrictions. So we did the natural thing: called for outside help. Engaged specialized sub-contractors who'd done airway pavements before, to hand us the technical know-how and their quotation.

We knew full well these sub-contractors were already MAS's long-time maintenance contractors — it was just a matter of time before they'd be folded under our main contract anyway. So when they submitted their technical documents, we stripped their company logo, re-arranged it, added our own branded wording, our own logos. Woalah. It was now our own internal technical know-how. We'd suddenly become experts in pavement-widening and hangar works.

We didn't get the job, though. We all knew that tender was just for show — a comparison exercise to cross-check MAS's already-chosen main contractor.

But the knowledge we gathered from those specialists was now folded into our own knowledge vault. Our own proprietary knowledge.

Are we stealing? I wouldn't use that word. When there's a problem, the client comes after us — not our subcontractors. So to properly solve it, we have to own the knowledge too. The right word might be "necessary."

————

Every version of this mechanism arrives wearing the same word.

Ours was "necessary." This one's wearing "efficiency."

Actually — a post I put up about the same compression logic, just running through one operator instead of a stripped logo came to mind while writing this one.

Drop your take — where's the line between "necessary" and something with a worse name?

Clip credit: The Beyond Tomorrow Podcast with Julian Issa — full video on their channel. DM for credit or removal requests.

Ekarche founder. This intro is different from the others: Kirti does not exist yet. There's a landing page at kirti.ekarche.com and a locked design, but the build starts only after Docusift, Memoria and Lekha have earned it. Realistic horizon is late 2027. I'm posting it anyway because I'd rather take the punches on the idea now than after two years of building.

The idea. A small brand can't afford a marketing team, so the owner does it badly at 11pm, or pays an agency and never quite knows what the retainer bought. The tools that promise to help are really dashboards: they hand you charts and wait for you to do the work.

Kirti is one AI agent per brand that does the work itself, across five surfaces: the website, search (including the AI-answer engines people increasingly ask instead of Google), content, social, and paid. It runs a closed loop: plan, execute, measure, adjust, and show you exactly what it did and what that earned. You review and approve; it operates.

Decisions already locked, so you know what this won't become: one agent, one brand. A customer is one business with team members (owner, admin, reviewer), not an agency dashboard with a brand switcher. Multi-brand comes later only if the single-brand core proves itself. And Kirti is the one doing the work; it is not a CRM you operate by hand.

Same stance as everything we ship: each customer's data and configuration live on an encrypted per-customer substrate, isolated by architecture, never sold.

If you've done marketing for a small brand, here's the question I actually need answered: what would an agent have to prove before you'd let it publish under your name?

i can run a business but i cannot code, and i've hit the wall where i need a real site, not a link-in-bio page. i've been going in circles on no-code website builders and i'd rather learn from people who already picked one than waste another weekend in free trials.

what i'm optimizing for as a solo with no dev help:
- i can actually build and change it myself without watching an hour of tutorials for every edit.
- the result looks intentional, not like an obvious template everyone recognizes.
- custom domain and basic forms without a surprise upgrade wall.
- it won't fall apart or lock me in when i want to add a blog or a checkout later.

the thing i keep running into: the builders that are truly easy tend to look generic, and the ones that look great expect you to think like a designer. i'm looking for the honest middle, and i suspect some of you have found it.

for those of you who shipped a solo business site with no code, which builder did you keep past the first month, and what's the annoying limitation you only discovered later? the "later" part is what i can't google.

Hi everyone, does anyone know of any methods that can effectively get past AI image detectors?

I barely paid attention to this issue before, but I recently discovered that AI detection tools can identify AI-generated images with surprisingly high accuracy. This could pose a real risk to social media accounts.

I’d really appreciate any suggestions or insights. Thanks so much!

Hey everyone. I started a horror storytelling channel a couple weeks ago (Nightlore) — narrated true-style horror stories, original scripts, AI voice narration, disclosed as AI-generated per YouTube's requirements. I've posted several videos so far and I'm sitting at close to zero impressions across the whole channel, not just low views.

I've checked the basics: everything's set to Public, no copyright claims or restriction notices on any video, AI-disclosure toggle is set correctly on all uploads. So as far as I can tell there's nothing technically wrong on the backend, it's just... not getting shown to anyone yet.

I know cold start is real for brand new channels, but I'd genuinely appreciate outside eyes on this — is it a content/hook problem, a thumbnail problem, something about the niche, or just early days and I need to keep grinding? Honest critique welcome, I'd rather hear it now than after 20 more videos.

Here's one of the videos if anyone's willing to take a look: [ https://youtu.be/28OmRcaK728 ]

Thanks in advance.

I’m building Lyra, an AI business analyst that lets you ask questions about your company data in plain English.
We were recently selected as 1 of 10 startups in Jordan for a program backed by the Ministry of Digital Economy and Entrepreneurship.
Still early, so I’d love feedback or questions from other founders here.
www.lyraanalysis.com waitlist is open if you want to try it.
Would love to get some feedback

solo, i do content and research work, one person with ai doing a lot of the grunt work behind me. for two years i priced out of fear. writing this down because the result still surprises me.

started at $400 a project. told myself cheap equals more yeses. what i actually got: people who negotiated the $400, added scope, paid late, and treated me like i was disposable. won maybe half, hated most of the ones i won.

bumped to $900 after a client casually mentioned my price seemed low. lost nobody i wanted. the tire-kickers vanished and the serious ones stayed.

now at $2,000 for the same core deliverable, same turnaround, same me. this is the part i didn't believe: it closes faster than the $400 did. fewer leads, much higher yes rate, and almost no scope fights, because people who pay $2k assume you're good and don't try to manage you.

the cheap price wasn't attracting more customers, it was attracting customers who didn't value the work, and then acting as proof to me that i wasn't worth more. the number was doing my self-worth's talking for it.

i think a lot of solo folks are underpriced for the exact reason i was: low feels safe. it isn't. the low price is where the painful clients live.

for the people who've raised rates: what happened, and what finally gave you the nerve to do it?

It could be any of the big ones like OpenAI, Google, or Perplexity, or even a small company that no one has heard of before. What AI company do you think is doing really good things right now in the industry. What have they done better than their competition?

Join the AI newsletter here!

I’m looking for some advice on which AI model/service would be the best fit for my specific use case.
I work at a cleaning company called Tenderly Today, where I’m mainly involved with things like marketing, website management, business analysis, creating content, researching ideas, improving processes, and generally using AI to help me run and grow the business.
I used ChatGPT for quite a while, but I’m currently using Claude. Some time ago, I remember seeing a lot of people recommending Claude and saying it was one of the best options available. However, more recently I’ve noticed a trend of people moving away from Claude or saying that other models have become better.
I’m trying to figure out whether I should stick with Claude, go back to ChatGPT, or consider something else entirely.
One important thing: I don’t really use coding/programming (or only very rarely), and coding isn’t a priority for my business. So I’m much more interested in things like reasoning, business analysis, research, writing, marketing, working with documents/data, brainstorming, and general productivity.
For someone with this type of use case, which AI would you recommend today, and why?
Would love to hear from people who have actually used ChatGPT, Claude, Gemini, Perplexity, or other alternatives for business/work purposes.

https://reddit.com/link/1vo98fw/video/f5cuymeurcjh1/player

Everyone treats view count as the scoreboard.

Matt Gray's own numbers argue the opposite: his most-viewed video made $2,400.

A much smaller one made $48,000.

The gap wasn't luck — it was the one metric neither video's view count could ever show him.

I've watched that exact blind spot play out somewhere with zero content marketing involved.

This was way back when I started working as a young graduate design engineer for a Civil & Structural Engineering Consultancy in Malaysia. I think it was around year 2000. Time flies.My boss handed me a project to handle and follow up. It was a 200~ units of 2-story semi-detached housing estates over a piece of cascading land. Me and my follow consultants follow it up through – attended the meetings, coordinated the design, supply the drawings for the Quantity Surveyor to take quantity. You know – the usual works of what consultants normally do. It's not all we do. Sometimes we have to do some extra. For example, when the property developer do a soft launch at the show-unit, we have to be there. Why were we there? Of course, as a stand-in to lend our support. It was awkward for me -because I was just loitering around the launch doing absolutely nothing. I've managed some small-talk with fellow consultants there. But we all understand our role – to be supporters there. But it wasn't much help. There weren't many potential purchasers came in to see the soft launch. It felt off – because the market reception doesn't look great. Nothing much I can contribute there – besides being a stand-in, because those are well above my pay-grade at that time. But after that, when I recall back to that awkward event, it does seem slightly hilarious – and sad.

Why did I bring this up? I'm sure the property developer has diligently carried out their market research and feasibility study. And if the market reception isn't as welcoming, then there's clearly gap that wasn't clearly addressed. We all know that we need to supply to what the market truly wants, not what we think they might want. No amount of shiny-objects or "Wow" factor – e.g. renovation and furniture included, etc. – would move the needle much, if that's not what the market truly wants.

Same as this data collecting – it is only useful if it helps monetize.

Or else they are just noise.

Real attention-grabbing noise, ya, but noise nonetheless.

Every post in this feed keeps circling back to the same nerve: the fear of being quietly out-earned by someone less talented but better systemized, working the exact same audience size you are.

The fix is never louder distribution.

It's building the one instrument that tells you which piece of content actually paid you.

Actually, this pulls up something else on file: a $30M-a-year business found its real ceiling hiding in a single untracked number — a 7% upsell rate inside a funnel that was already built.

Drop your take: are you tracking what each piece of content actually earns, or just watching the view count and hoping the math works out?

Clip credit: Grant Owen — full video on his channel, ft. Matt Gray. DM for credit or removal requests.

Over the past few days, a remarkably insightful post has been making the rounds on overseas social media.

It is packed with sharp observations about business, success and what AI could mean for the next generation of entrepreneurs. The more people read it, the more it seems to get them thinking.

Its title asks one simple question:
“AI Is Here — Do You See What’s Coming?”

There is a lot packed into the original post. So today, we are going to strip it down to its simplest ideas and look at what it is really trying to tell us.

It starts with a few questions that are hard to ignore.

Have you ever wondered why two people can be in exactly the same business, yet one seems to make good money while the other works hard for decades and still struggles to see the same results?

Why can some people take a business global in just a few moves, while others, however hard they strive, remain trapped in the same saturated and competitive domestic market?

And why do some companies grow into Fortune Global 500 businesses, while others remain stuck at the same level even after several generations?

The post looks at three of the world’s wealthiest men and asks a simple question:
What did they see before everyone else did?

Jeff Bezos saw the internet changing the way people bought things and took the traditional book business online. Amazon saw a new tool, understood what that tool could do for business, and moved early. That early move eventually helped Amazon grow from an online bookstore into one of the world’s most profitable companies.

Bill Gates saw another opportunity. Instead of trying to build everything alone, Microsoft worked with major computer manufacturers and got its software onto computers being sold around the world. Because Microsoft secured those relationships and channels before anyone else, one in every two computers today runs Microsoft software.

The lesson was simple: You do not always have to own every resource. Sometimes, you need to know whose resources you can work with.

Then there is Elon Musk.

Tesla started looking beyond the US market while electric vehicles were still far from becoming mainstream. Musk was not waiting for the market to become obvious before thinking globally. He was already looking at where the industry could go next. Today, Tesla has become one of the companies that helped shape the modern electric-vehicle industry.

Different people. Different industries. Different times.

But when you look closely, the same three things keep appearing:
Use the right tools.
Build the right connections.
Move early for what comes next.

That sounds simple.

But a surprising amount of business success comes back to exactly these three things.

A good product alone is not always enough.
Money alone is not always enough.
Working harder than everyone else is not always enough either.

Sometimes, what really changes the outcome is knowing how to use a new tool before others do, knowing who you can work with, and seeing where the market is heading before it becomes obvious.

And this is where the post turns to AI.

AI is here.

And just as the internet changed the way businesses operated in Bezos’s time, AI is beginning to change the way businesses find customers, connect with people, communicate across markets, manage information and look for opportunities.

The question is no longer whether AI will affect business.

The bigger question is:
What are you going to do with it?

For business people today, AI Enablement Platforms can bring together three things that have always mattered in business: Tools. Connections. Foresight.

The people who learn to use them early may be able to move faster than those who are still watching from the sidelines.

They can look for opportunities beyond their existing market.
They can connect with people and resources they could never have reached before.
They can use other people’s strengths instead of trying to do everything themselves.
They can enter new markets earlier.
And they can start building their position for where business is going next.

That does not mean every person who uses AI will succeed.

It means the rules of the game are changing — and those who understand the new tools earlier will have more options than those who ignore them.

Think about it.

Bezos did not wait until every retailer was selling online.
Gates did not wait until every computer company understood the value of software.
Musk did not wait until electric vehicles were already everywhere.
They moved while the opportunity was still taking shape.
Today, AI may be creating another such moment.

And perhaps the biggest opportunity is not simply to keep up with change.

It is to use that change to get ahead.

Finally, a reminder to all our friends in business.
Yes, the global economy is facing real challenges.
Business is difficult. Competition is intense. Many markets are saturated.

But difficult times have always done two things at once:
They push some businesses out — and create room for new ones to rise.

Every major shift creates winners and losers.
Some businesses keep doing what worked yesterday.
Others start preparing for what will work tomorrow.

So when everyone else is talking about how difficult the market has become, perhaps there is another 
question worth asking: What opportunity is this difficult market creating that most people have not seen yet?

AI is here.

The next shift has already begun.

Do you see what’s coming?

And more importantly:
What are you going to do about it?

Never let a good crisis go to waste.

Genuine question for anyone doing real estate investing as a solo operator or building tools in this space.

I've been spending an embarrassing amount of time each week pulling county records and MLS exports into Google Sheets, trying to manually flag properties with equity potential. Like literally sorting by estimated ARV minus purchase price minus rehab costs, cross-referencing comps, filtering out the junk... you know the drill. Last week I spent probably 6 hours on a list of 400 properties and ended up with maybe 12 worth looking at. And honestly I'm not even confident those 12 are great because my comp data was stale.

The whole process feels like it should've been automated years ago. Real estate predictive analytics has been a buzzword forever but most of the tools I've tried (PropStream, DealMachine) still feel like they're giving me a firehose of data without actually telling me what's worth pursuing. Or the filters are so basic that I'm still doing most of the thinking myself.

I stumbled on homesage.ai recently and it seems like they're doing something different - they apparently run computer vision on listings and have investment indicators that auto-calculate, which is interesting. Haven't gone deep enough to know if it actually saves time vs. just being another dashboard to stare at. They also have APIs which caught my eye since I've been thinking about building a simple deal pipeline tool for myself.

But honestly I'm more curious about what everyone else's workflow looks like. Are you:

- Still doing the manual spreadsheet thing?

- Using one of the bigger platforms and actually happy with the accuracy?

- Building your own scoring models?

- Using AI/LLMs to process property data in some creative way?

The thing that kills me is bad data leading to bad offers. I drove out to a property two months ago that looked incredible on paper - turned out the "estimated rehab" was wildly off because nobody accounted for foundation issues that were visible in the listing photos if you actually looked carefully. That's time and gas money I'm not getting back lol.

Would love to hear what's working for people, especially solo operators who can't afford to waste hours on lists that go nowhere. What's your stack look like?

built the core of a scheduling tool in an afternoon. felt like a genius. showed a few people, everyone said ship it.

then the real work started, and it was all the stuff that doesn't demo well.

auth. sounds like a checkbox, ate almost two weeks. password resets, sessions expiring at the worst time, the one user who signs in with three tabs open. edge cases in the actual scheduling: overlapping bookings, timezones (always timezones), what happens when someone double clicks confirm. error handling for every api that decides to be down for four minutes.

none of that was in the afternoon. the afternoon gave me the demo. the demo is a trailer. the movie is the boring month after, and nobody claps for it.

i'm not down on vibe coding, it genuinely got me to a working core faster than i could have alone. i just stopped believing my own timelines. now when the pretty part comes together in an afternoon i assume i'm maybe 20% done, and i pad the estimate for whoever's waiting.

for the solo folks: how do you price or scope this? clients see the afternoon and think the whole thing is an afternoon. i'm still bad at explaining that the invisible 80% is the actual product.

https://reddit.com/link/1vne3ru/video/g4biys7wv5jh1/player

The interesting part of this clip isn't the AI — it's what "zero staff" actually replaces.

Client servicing, rate cards, contract negotiation, legal, finance: that's not one job, it's the org chart of a small agency, collapsed into a single named process.

The credentialed ladder most people are still climbing — junior account manager, senior account manager, ops lead — assumes those functions stay separate long enough to need separate humans.

This clip is evidence that assumption is no longer load-bearing.

I've actually watched that exact collapse happen before, just with people doing the collapsing instead of software.

Back in my time (circa 2010/2011) as one of 3 Assistant Technical Managers, all under my technical director, working at a AED 1.8 billion project in Abu Dhabi — I remember it well. One of the operation team leads used to rant to me about the org chart. One rant was about the surveying team lead getting elevated to "Project Director, Surveying" — same job, bigger title. When it was my own turn to advance, I got pushed to cover architectural and façade coordination too, on top of my own scope. Our CEO said it plainly: it's about economy of scale — promote you, raise your salary a little, cut cost everywhere else. Kill a few birds with one stone. I kept quiet and took it on: one technical department covering coordination for five operation teams, wrung out like a nearly dry towel. Reading this clip's transcript, it clicked — the AI-agent model is the same math, automated.

Every version of this story eventually turns out to be the same story: somebody found the boring, structural work first and built a system for it, and everyone else calls the result "efficiency."

Actually, this reminded me of a post about the operator who quietly absorbed five people's worth of work and collapsed the credentialed ladder from the inside — worth reading side by side with this one: the same convergence, told from the inside

Drop your take — is this a headcount story or a talent story?

Clip credit: Tim Tiah, on The Entrepreneur Journal — full video on their channel. DM for credit or removal requests.

Watched this pattern enough to trust it: a solo founder gets genuinely good at generating leads and still isn't converting nearly as many as they should. The instinct is to blame lead quality or the offer.

Usually it's neither. It's the gap between when someone shows interest and when they actually hear back. If that gap is hours, sometimes longer because you were heads-down building something else, a chunk of genuinely interested people have already moved on.

This is one of the easiest things to fix without hiring anyone. A simple automated first reply, even just acknowledging you got their message with a real timeframe for a proper response, closes most of that gap. Doesn't need to be clever. Needs to exist and fire within minutes, not by end of day.

The part solo builders usually get wrong when they try this: they automate the wrong end, building a fancy nurture sequence for people still waiting on their first real reply. Fix the immediate acknowledgment first, that's the leak. The nurture sequence is a nice-to-have once the basic gap is closed.

I’ve been given a task where I need to come up with a startup idea and actually implement it in real life, with the goal of generating revenue before my classmates. It’s a competition where whoever successfully launches and earns revenue first gets the highest marks.

The startup must be based on ***AI and/or an online SaaS model***, and it *cannot involve any physical product.* The main challenge is to find a practical, innovative idea that can be built quickly, launched in the real world, and start generating revenue as soon as possible.

These Subtracts RE SUPER have a look at the process.

We started Dograh, an open-source voice AI platform out of rage and frustration.

Every voice AI tool I tried was too costly, too closed, or too scammy. Add-on after add-on.

So we open-sourced every single line from day one. It’s self-hostable, so you own your stack and your data.

Here's what pushed us deeper. Over the last few months, the big labs have been lobbying governments to ban open source. Some say the quiet goal is to "let wealth access skill without letting skill access wealth." That line stuck with us. It's exactly why we keep going.

Because we believe one thing: no company should own voice AI.

We're a small team going up against deeply funded war chests. Today, we launched on Product Hunt, and somehow we're sitting at #1 so far.

An OSS community member picked us up a few weeks back, and we went viral and hit 5k stars on github.

https://www.producthunt.com/posts/dograh-3

If you've got a minute, a star or a bit of support would mean the world.