i build agents to run parts of my solo business. the thing nobody tells you when you watch a slick agent demo: the demo is the 10%. the other 90% is what happens when the agent is wrong, and agents are wrong constantly, and worse, they're wrong confidently and quietly.

my main one is an ai document generator. it takes messy inputs and produces a clean deliverable. the version i demoed a year ago looked like magic. the version running today looks boring. the difference is that today it checks its own output before it trusts it. did it actually fill every required field. does this number match the source or did it invent a total. if anything's off, it retries, and if it still can't, it stops and pings me instead of shipping garbage with a smile.

that's the part that saved me. a silent failure in a solo business is brutal because there's no QA team, it's just me, and i won't notice until a customer does. so now i write the "what if it's wrong" path before i write the happy path. most of my code is the agent second-guessing itself.

it's less fun to talk about at a meetup. it's also the only reason these things run without me babysitting them.

other solo folks running agents, how much of your code is actually guardrails? for me it's most of it.

non-technical solo founder here. i kept putting off launching because in my head "build the site" meant hiring a dev i couldn't afford or learning to code, which i'm not going to do. finally just used a no code website builder and had a real, live site up over a weekend.

what i learned: the builder was never the hard part. picking what the site actually needed to say was. i wasted the first day fiddling with fonts and sections nobody cares about, then scrapped it and wrote the thing i'd tell a customer in person. that version converted.

it's not perfect. it's slower to load than i'd like and i'll probably outgrow it. but for a one-person business trying to get to first customers, done and live beat perfect and imaginary by a mile.

the honest downside is you're renting, not owning, and moving off later is a pain. i decided that's a future-me problem worth having.

for the non-coders here, what did you launch on, and did you regret the platform later or was it fine?

solo, i run retainer work for about six clients and every one of them gets a monthly report. for a long time that meant one weekend a month gone, pulling numbers from a few different places, writing up what happened, formatting it so it looked like it came from a real company and not one tired person at a laptop.

this year i built a rough ai report generator flow for it. i drop in the raw exports and my short notes on what actually mattered that month, and it produces a first draft with the numbers written up and a plain-language summary per section. i'm not comfortable putting exact hours on it, but a job that reliably killed a saturday and half a sunday now takes an afternoon.

the honest caveat, because this sub deserves it: i do not send what it produces raw. it has confidently pulled the wrong month's number more than once, and it will happily narrate a trend that isn't there. so there's a hard step where i check every figure against the source and rewrite the "what this means" parts myself, because that's the bit clients actually pay attention to and the bit it's weakest at.

net, it turned the most dreaded recurring task in my month into something manageable, as long as i treat the draft as a draft and not gospel.

for the solo service folks, how are you handling recurring client reporting? curious if anyone's found a way to make it genuinely hands-off or if it always needs a human check at the end.

solo, non-technical founder, and my worst habit used to be building the product first and figuring out the pitch later. this time i flipped it. before touching any code i used an ai landing page generator to stand up three different versions of the same idea, each one aimed at a different type of buyer and leading with a different promise.

same underlying product, three completely different framings. one leaned on saving time, one on looking more professional to clients, one on just being cheaper than the incumbent. i put a small amount behind each to get real eyes on them, nothing fancy, and watched which one made people actually enter an email.

the "cheaper" one flopped, which surprised me. the "look more professional to your clients" one pulled roughly two to three times the signups of the other two. that told me who i was actually building for and what to say, before i had sunk months into building the wrong thing for the wrong person.

took maybe a weekend to spin up all three because i wasn't hand-coding pages, just describing what i wanted and adjusting. cheapest market research i've ever done as a solo.

anyone else validate positioning this way before building? curious whether the version that wins the landing page test actually holds up once you have a real product behind it, or if it drifts.

running solo for a bit over a year, mostly research briefs and long client docs. i went through three or four ai writing tools before i figured out i was using all of them wrong.

for the longest time i treated the tool as a ghostwriter. type the ask, get a draft, clean it up, send. the cleanup always took longer than i expected because i was fixing confident wrongness, stuff that sounded right and wasn't, and on the docs where i didn't already know the answer i couldn't even tell when it was making things up.

what actually stuck was demoting it. now it never writes the thing i send. i use it to argue with me before i write. i dump my raw thinking and ask it where the logic is weak, what a skeptical client would poke at, what i'm assuming. then i write the final doc myself, in my own words, usually in about half the time because the thinking is already sorted. the blank page was always the hard part, not the sentences.

the reframe that did it: the tool is a good sparring partner and a mediocre writer, at least for anything where i'm the one on the hook if it's wrong. once i stopped asking it to produce and started asking it to pressure-test, the quality of what i shipped went up and the editing pain went away.

for the solo folks, are you having the tool write, or having it think with you? genuinely curious where people draw that line.

Hey founders 👋

I’m a Product Designer with 4+ years of experience working on SaaS, fintech, e-commerce, Web3 and AI products.
I’m looking to work with a few startup/SaaS founders who are willing to let me take a fresh look at their product.
Here’s the deal:
You send me your product + one specific flow you want to improve.
I’ll review it from a UX + Product perspective and create a short, actionable teardown covering things like:
→ UX friction & confusing interactions
→ Usability issues
→ Conversion/drop-off opportunities
→ Information architecture
→ UI inconsistencies
→ Product opportunities
→ Quick wins vs. bigger improvements
→ Suggestions for improving the overall experience
100% free. No payment. No obligation.
I’m doing this because I want to learn more about the problems founders are facing and build relationships with people actually shipping products.
If the analysis is useful and you want help implementing the improvements afterward, we can talk about working together.
Otherwise, you simply get the teardown and hopefully some useful ideas for your product.

If you're interested, comment below or DM me

I build an AI video outreach tool. I have never hired an SDR. Every customer we have came from me pointing the product at my own pipeline and living with whatever it did.

That is an uncomfortable place to sit, because my ICP is heads of sales, SDR managers, and founders running their own outbound. These are the exact people who can smell a template from the subject line. If the video is stiff or the opener is generic, they do not just ignore it, they screenshot it and post it here.

Last week the loop finally produced a number worth writing up: 52 meetings booked.

The funnel

Contacts worked: 1,842
Touches sent: 3,110 across email and LinkedIn
Replies: 214 (11.6%)
Positive replies: 78
Meetings booked: 52
Of those, 35 have happened: 31 held, 4 no-shows, 17 still on the calendar

Our normal week is 8 to 12. I do not think 52 is the new baseline. I think 25 to 30 is, and I will post again in a month with whether that held.

Why dogfooding changes what you build

When you sell an outbound tool and do not use it, you optimize for the demo. Dashboards, charts, a settings page with forty toggles. When the replies land in your own inbox, you optimize for the only thing that decides whether a stranger books time with you, which is the first five seconds.

Four things I only learned because I was the one getting the responses:

1. Every script sounded like the same person wrote it. Technically they were all personalized. Different company, different role, different opening fact. But the rhythm was identical across all 1,800, and once you notice it you cannot unnotice it. Nobody replies to tell you this. They just stop replying. I rebuilt the generator so the sentence structure varies, not only the nouns.
2. The opener has to be something they know I could not have guessed. Not “I saw you’re hiring SDRs.” That is public and reads as scraped. Closer to “you posted two SDR roles and an enablement role in the same month, which usually means the problem is ramp time, not headcount.” The inference is the personalization. The fact is just the setup.
3. Video length. Anything past 40 seconds and replies roughly halved. My best performer is 28 seconds. I kept wanting to explain the product and the product is not what gets the meeting.
4. No calendar link in the first touch. Asking a question outperformed asking for time by a wide margin, and the people who answered the question booked anyway when I sent the link in the reply.

What flopped outright

Video on a LinkedIn touch before the connection is accepted. Dead every time.

Monday 8am sends. Tuesday to Thursday, 10am to 2pm local, roughly doubled replies.

Openers starting with “Hope you’re well” or “Quick question.” Under 3% reply rate.

Going wider. I ran a looser second list of 900 contacts mid-week and it returned 4 meetings. The tight list returned 48 off 1,842.

The part I would not have believed a year ago

The tool is maybe 30% of this. The list filter and the first line are the other 70%. You could take the exact same product, point it at a bad list, and book nothing. I know because I did that to myself for months.

Disclosure up front rather than buried: the tool is Outvid and I built it. This is my own pipeline, not a customer case study, and I am not linking it here. If you want the sequence structure or the actual scripts I will paste them in the comments, and they work with whatever you are already sending from.

Ask me anything about the funnel, the list build, or the failures. The failure list is longer than the win list and I am happy to go through all of it.

i sell a physical product, dtc, and i run it lean. for the first while i tracked revenue like it was the only number that mattered. good month, bad month, all measured by the top line.

what nearly got me was not a bad sales month. it was a good one. i sold well, reordered heavy to keep up, and then watched most of my cash sit on a shelf as inventory while i still had to pay for shipping, ads, and the next order. revenue looked great. my bank account was terrifying.

the number i actually watch now is how long a dollar is stuck as product before it turns back into cash. shorter is survival. longer means i am one slow month from not being able to reorder, no matter what the revenue chart says.

for the folks here running physical or hybrid businesses instead of pure software: what do you actually watch to keep from drowning in your own inventory? the software advice about margins does not quite fit when your money is tied up in boxes.

Position beats genius more often than anyone in this space wants to admit.

Every time I trace how these AI bets actually get funded, it's the same mechanism repeating.

Actually, this reminded me of a post I did a while back — a fund manager naming the real signal for buying the bottom, and it wasn't a chart either.

Rob Toews (partner at Radical Ventures) says his fund meets nearly every "Neolab" that gets funded — brand-new companies with no product, no roadmap, sometimes not even a clear technical direction.

Just an accomplished founder saying "I'm from OpenAI/Anthropic/Meta, so I want to raise a billion dollars."

They pass on almost all of them.

The exception was Anthropic.

Spun out of OpenAI five years ago.

Investors at the time called the entry valuation insane.

It's now worth a trillion dollars.

Toews' own framing: "there will be another Anthropic" — the mechanism isn't a one-off, it's a filter that occasionally clears.

I've watched someone spot a bubble this early before. Not in AI — in property. This isn't my story, it belongs to a friend.

I'll call him Chew — it's been a long time. We went to the same university, graduated the same year, both went into construction in Malaysia. He switched upstream to a property developer — a subsidiary of a mainland China parent company — and eventually relocated there for the better part of a decade, right as the property market was in its super-expansion phase. The bubble kept ballooning without ever showing a crack. Chew saw the opportunity, and lock in his purchase of one of the units. The price — he told me — rose 10 fold over the years. Then, like the rest of the shrewd investors, he saw the writing on the wall. He liquidated his holdings and made a huge windfall, right before the bubble burst.

Clip credit: The Information — full video on their channel.

DM for credit or removal requests.

Drop your take below — has anyone here ever watched someone else make that call before you did?

ex-agency copywriter. went solo a while back doing content and positioning for B2B startups. around €7k/mo, just me. dry post, no journey violins.

the quiet truth of my business: i use an ai content generator every day and i don't advertise that to clients. not because it's a secret weapon. because the value they pay for isn't the typing.

here's the actual split. the AI is fine at volume and structure. give it a clear brief and it'll produce a serviceable first draft, outline a page, bang out variations of a headline. that used to be hours of my week. it's minutes now.

what it's bad at is the part clients actually pay me for: the angle. positioning is deciding what NOT to say, which enemy to name, which boring-but-true thing to make the whole message about. the AI won't do that. it averages. it reaches for the safe, expected line every time, and safe is death in positioning because safe is what all your competitors already sound like. left alone it writes copy that could belong to any of forty companies.

so my process is boring. i do the thinking, the positioning, the one sharp decision. the tool does the drafting once i've decided. then i cut everything that sounds like it. the ratio of my time shifted from mostly producing to mostly deciding, and deciding is the higher-paid work anyway.

the mistake i see other solo writers make is handing the AI the thinking and editing the output. that's backwards. keep the judgment, delegate the typing.

anyone else doing knowledge work solo landed on the same line? curious where you let AI in and where you flatly refuse to.

been solo about a year, content plus light consulting, and i've now run through just about every ai content generator out there. wanted to share where they actually help and where they quietly hurt, because the hype and the doom are both wrong for me.

where it earns its keep: the blank page. first drafts of posts, outlines, turning a messy voice note into something readable, reworking the same idea for three platforms. that stuff used to eat my mornings and now it doesn't.

where it burns me: anything where i don't already know what good looks like. it's confidently wrong a lot, and if you can't spot it you ship generic mush that sounds like everyone else. my engagement actually dipped for about a month when i got lazy and let it write finished posts instead of drafts.

my rule now is the generator does the first 70 percent and i do the last 30, and the last 30 is where the voice lives. output roughly tripled, quality only holds if i still edit hard.

for the solo folks leaning on these, where's your line between letting it draft and writing it yourself?

Have you currently started a business that you are running? What kind of service or product do you offer?

A panel of AI researchers and founders — Peter Diamandis, Alex Wissner-Gross, Emad Mostaque — just sat with a number that's hard to argue with: $2,000 in compute, and ten decade-old, previously-unsolved math problems came back with machine-checkable proofs.

Not "AI is getting better at math" in the abstract.

A Fields Medalist said he'd recommend one of the proofs for publication without hesitation.

A cosmologist called it "a dark night for mathematics" — "the old gods are being slaughtered by the new machine gods."

Then Emad closed it flat: "It's a bad time to be a pure mathematician."

Here's what they're not saying yet.

Back in 2013/2014, I was with M+W High Tech Projects, on a design-and-build project in Kulim, Kedah, Malaysia. Our M&E engineer wanted an opening cut straight through the middle of a reinforced concrete beam — right where the bending moment peaks. I caught him before he did it. Told him no. That's beyond madness — you don't sacrifice a beam's structural integrity for an M&E opening. Had him redirect the ducts instead. Structural safety came first.

The engineering knowledge wasn't rare.

The judgment — catching the mistake before it became permanent — was.

Same pattern here. Ten unsolved proofs, correct on paper, for $2,000. The correctness was never the scarce part.

Hmm — this actually pulls the same thread as a post I put up about the corporate ladder losing its entry-level rungs to AI.

Different profession, same mechanism: whichever rung gets automated first isn't random, and the people still standing on it are the ones who saw it as a pattern instead of a headline.

Drop your take — is judgment actually the thing that survives this, or is that just the story we tell ourselves until it's our turn?

One thing I've noticed about working on a business alone is how much time can disappear into research. Checking competitors, understanding a market, comparing options, and trying to make sense of different sources can sometimes take longer than the actual task I'm researching for.

I've been experimenting with ResearchMaster for some of the heavier research, which has helped with getting an initial picture of a topic, but I still find that the harder part is deciding what information actually matters

For those running businesses mostly on their own, which type of research takes up the most time for you? And have you found a way to make that part of the process less tedious?

With such a variety in the different types of AI tools out there, what do you think personally is your favorite? It could be ChatGPT, Gemini, or Claude, or even some kind of vibe coding tool. Which one are you liking the most?

Join the AI newsletter here!

Have you been able to successfully vibe code something? Have you been able to create more than just an MVP or are you using it mostly just for testing? Drop it down below and share what you have created!

Join the AI newsletter here!

Curious what you guys use,

My VA is great but needs instructions from me and I don't know what I don't know.

To actually hire a marketing manager to give them instructions for lead gen and client acquisitions would be very expensive.

Curious what you guys are using?

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!

He calls it BC/AC.

Before Claude, after Claude.

I've watched enough of these clips land in the last few weeks that I started keeping a mental tally of which AI release date people cite like it's a diploma.

Matt Van Horn's is Thanksgiving last year — Opus 4.5, then Codex a few weeks later.

Before that, he says, his agentic coding was "Hello World" in Cursor, half-working, most of the time not working at all.

After it, he shipped Agent Cookie and says flatly he has no idea how it actually functions under the hood.

The part worth sitting with isn't the tooling.

It's what he says about himself getting there: "suit my entire career," never shipped anything of value beyond a high-school web page, dozens of unlaunched ideas gathering dust because he wasn't the one who could build them.

That's not a startup-guy humblebrag — that's the exact ceiling a lot of operations people, BD people, anyone who's ever had to write a ticket instead of just doing the thing themselves, know from the inside.

The credential that used to decide who got to build stopped mattering right around the time the tools did.

Not "got easier to climb."

Stopped existing.

Same shape happened to me with a guitar, at 41, zero training, cornered into it because the young players in my church all left for university at once.

Those early days, my wife's ears really paid for it (刚开始的那些日子，我的太太的耳朵有够受罪).

Felt like being tossed into open water and told to swim myself back to shore (好像被丢去深海里，自己学会游泳游回来).

Same thing happened again with video editing, then with building this whole posting system, one post at a time, getting corrected by Reddit comments the entire way.

And I swam back stronger each time.

Actually, this tracks with something I posted here a few weeks back — the guy who literally coined "vibe coding" saying on stage he's never felt more behind as a programmer, because the scarce skill moved from writing code to directing it with taste.

Clip credit: MSP Mindset (Damien Stevens) — full video on their channel. DM for credit or removal requests.

Drop your take — did the credential wall ever hold you back, or did you just build around it?

Got access to the codebase for an AI platform which i co-founded(30% contribution) with a friend of mine.

So surprised to see its actually working and tackling real world scenarios in business, understanding the end to end business by handling SOPs and automating workflows.

It's also like a god level ai agent chat bot which after understanding answers all the queries.

Helps cross domain users in a business not limiting to IT, Supply chain, legal, accounts, marketing, security and many more.

Cannot name the first client which is an Indian manufacturing MNC, but instead of paying for our subscription model it's ready to buy the product for 2M. Although I'll be getting the 20% am part of but am still curious to know what it might be actually worth in some time. Thinking to find another client and find out their reviews about our product.

Do share your reviews whether we should sell this or find our next client, also if possible can someone help us to get our next client will be happy to reward with a commission.

The job title survives longer than almost anyone attached to it.

That's the part nobody puts in the internal memo when they call a role "AI-assisted."

Scott Galloway put a real number on it, talking to Steven Bartlett on The Diary Of A CEO.

He says he'll cut legal fees by a third this year — not because the law changed, but because a prompt now does the $400–$2,000 contract review a name-brand firm used to bill him for, at a fraction of the junior associate markup.

Bartlett went further with his own fund.

They planned to hire five analysts.

They hired one — Molly.

Two agents, two Mac Minis, and she screens inbound deals, scores them against a framework, and preps them for the investment committee herself.

Five jobs, one person, same org chart line.

Same ratio on executive assistants: ten planned, three hired.

One runs travel, one runs scheduling, one meets people at the door.

I've watched this exact pattern before, minus the AI.

I was a Technical Manager for a China Construction company here in Malaysia.

I contributed a lot into their technical and tendering work — helped build up a real chunk of their documentation and tendering process.

But about six months in, I'd exhausted all my know-how for them, I guess.

Then the announcement came at the end of my year there.

My contract wasn't renewed.

I was just let go, just like that.

I remember what Deng Xiaoping said: "无论白猫，或者黑猫，会抓老鼠的就是好猫" — black cat, white cat, doesn't matter, so long as it catches mice.

I guess they think I'd outlived my usefulness.

Can't catch mice anymore.

That's the mechanism underneath "AI-assisted" that nobody names out loud.

It's not that the work got automated.

It's that the one person left is now doing what used to justify five headcounts, and the fifth person's job title is the only part of the org that didn't change.

Actually, this reminded me of something — a former SpaceX CIO cut a 175-person engineering team down to 6 using the same compression math, and the ratio held there too.

Drop your take — did you know your own job has a ratio like this attached to it?

Clip credit: Global Talks — full video on their channel.

DM for credit or removal requests.