u/Warm-Reaction-456

In my last post about the 60k dead real estate leads, I mentioned in one line that the voice agent tells people it's an AI in the first few seconds. That line probably deserved its own post. Of everything in that build, it's the decision I see people building voice agents go back and forth on the most.

Here's the opener word for word:

"Hi, this is an AI assistant calling for {realtor} at {brokerage}. You asked about homes in {area} a while back and he wanted me to check in. Is now an okay time?"

Why we did it: the client's name is on every one of those calls. If someone figures out halfway through that they've been talking to a bot, they feel tricked. In a market where everyone knows everyone, that hits his reputation. If they find out in the first sentence, the worst case is a hang-up. If they find out late, you lose the lead, and maybe a couple of their friends with it.

So what happened? 50% hung up in the first 10 seconds. On its own that number doesn't tell you much because people hang up on unknown numbers all the time. Compared to the client's old calls from human callers or a test batch without the disclosure it was lower

Most of the people who stayed on fell into four groups.

A lot of them just carried on like it was any other call.

A bunch asked "wait, is this a real person?" a few seconds after being told lol.

A few spent the first minute trying to trip it up with random questions.

And some were way more honest than they'd ever be with a salesperson. They'd say straight up that they already bought with someone else or that they weren't moving at all. A human caller almost never hears that.

That last group is why I'd keep the disclosure even if it cost us some pickups. When you're sorting through tens of thousands of people, a clear no is worth a lot.

A few things I'd tell anyone building one:

Say it in the first sentence. If the AI part comes out after a question, it sounds like a confession.

Offer a human right away. Something like "if you'd rather talk to him directly, I can have him call you" takes a lot of the hostility out.

Once you've disclosed, drop the fake human stuff. Breathing sounds and filler words from something that just told you it's an AI are creepier than a voice that's just clean.

Check your hang ups against a baseline. Without one you'll blame the disclosure for hang ups that were going to happen anyway.

I'd still rather lose a few pickups than have a lead find out halfway through.

This is going to sound like I'm talking myself out of work but I have been sitting on it for a while so whatever.

Quick context first… I've run an agency for about 8 years so I get a front row seat to what happens when a business adds AI, which projects turn into something that runs every day and which ones turn into a demo the owner shows his friends and never touches again.

The pattern is not what the guru videos tell you. The businesses that get real money out of this are almost never the ones that call an agency first. They're the ones where the owner or someone who's been there long enough to know where the bodies are buried automated one small ugly piece of their own day before talking to anyone. Then they call us with a list. That list is worth more than any discovery call I've ever run.

Because when you hand me a brief that says "automate our onboarding" I'm going to build you the generic version. Form comes in and the data lands in the CRM and a welcome email goes out. It works fine. It's also the exact thing every other agency would have built because from the outside that's all onboarding looks like. What I can't see is that your ops person hand checks every order over 2k because of something that went wrong in 2021 or that your best clients all come through one referral partner who needs a different intro. You know that stuff. I don't and that's where the actual money is. No one is going to find it for you in a 45 min call.

The other thing I see constantly is the unfair comparison. Someone sets up a support agent over a weekend, runs it against a support process they've been tuning for six years, and announces on LinkedIn that AI doesn't work lol ok. How long did you spend training your last support hire. How many times did you correct them in the first month. You gave the human a year and the bot an afternoon. No one puts this in the course but if you can't write down how the job gets done in steps a new hire could follow, it can't be automated by me or anyone else. The clients with written SOPs get a working automation in about a week. The ones without get a demo.

Same with the AI sales stuff. Everyone wants an AI setter that calls every lead the second they opt in. Would you have a human call every single one? Probably not, you'd qualify first. Cheaper doesn't mean it works. If your sales process is a mess the AI just runs the mess faster. We built one of these last year for a client with no real follow up cadence and it worked technically and did nothing for revenue. That one was on us for not pushing back harder before we started building.

A few smaller things I've picked up that I don't see anyone saying.

Stop putting "AI" in front of things you sell. We tested this in our own proposals. "AI powered onboarding" closed worse with owners over 45 than "your onboarding goes from 3 days to same day." No one cares what tool you're running. They care that it's faster and that they don't have to think about it. I don't tell clients what CRM we use either.

The gut feeling thing is mostly a checklist you haven't written down. Every time an owner tells me "I just know which leads are worth quoting" I make them walk me through the last ten. It's always the same four or five things. How fast the founder replied to the first email whether they've paid an agency before that kind of stuff. Once it's written it's a scoring prompt and it runs before you wake up.

The stuff that works first is boring. Anywhere a person looks at something and makes the same yes or no call 50 times a day. Invoice matches the PO or it doesn't. Ticket is a refund or it isn't. That's what the big companies automated first too, fraud checks and contract review, not marketing. If your first automation is "write my LinkedIn posts" you picked the wrong one.

If you want to build something yourself, take the transcript of whatever tutorial you're watching, paste it into an AI, say "help me build this" and then screenshot your screen every time you get stuck and paste that in too. That loop is how non technical people are getting things built right now. It's more useful than any 2k course and it costs nothing.

And the proof thing. The internet is about to be full of AI generated advice and AI avatars and AI case studies. In B2B nobody is going to trust any of it without a real track record behind it. So start recording your calls and keeping your numbers now, because "we did this for a client and here's what happened" is going to be the only thing that cuts through in a year or two.

Hire an agency, sure, we're not going anywhere. But the owner who shows up with one automation they built badly themselves gets ten times more out of us than the one who shows up saying "do the AI thing." You're not too busy for this btw. You're busy with stuff that matters less, everyone is.

TLDR: The businesses getting real results are the ones where the owner automated one piece of their own day first and gave the AI the same training runway they'd give a new hire. If you're waiting for a tech guy to do it for you, you get the generic version.

I hear this line in every founder circle. Meanwhile Unicommerce does about ₹180 crore in ARR all of it from India with enterprise clients paying ₹10 to 12 lakh a year. It has been profitable for most of its life with no US market to lean on.

I run an AI agency and I spend my weeks on calls with Indian business owners, selling them automation. So their story reads to me like my own client calls at a thousand times the scale. 6 things from it that match what I see on the ground.

Firstly, Your competitor is Excel. About 85% of this market still runs on spreadsheets and WhatsApp groups and one overworked ops person. When I pitch, the thing I'm replacing is almost always a habit that has worked well enough for years. So half the sale is education.

Secondly, people only pay for results. Show an owner going from 30 orders a day to 4,000 with the same 3 people and price stops being the conversation. Show them a dashboard and they'll literally squeeze you on every rupee and it's fair.

Thirdly, the customization fear is mostly a myth. I was warned that Indian clients demand endless custom work. What they actually want is something that fits how they already operate without a 3 month setup. Build for one type of business and its specific mess and the custom requests mostly disappear.

Fourth, no one hands you a market here. You gotta build one. Unicommerce started at a million shipments a year and is at a billion now. Solve one painfully specific problem properly and let the rest grow around it.

Fifth is that DON'T fight on price. The leader in their space charges about 50% more than everyone else and still dominates because that margin pays for a better product. A price war has no bottom.

Lastly AI is only killing the plain vanilla work. If you use AI to get clients results they couldn't get before then there has never been a better time to be in this business.

India pays.... You just have to prove it first

The standard advice is to build a first version fast, launch it and iterate on customer feedback. 10 years ago that did work. Building was expensive and customers had few options, so they'd put up with a half baked beta. Now building is cheap and every problem already has a dozen products chasing it and a customer who doesn't get value in the first session doesn't become your early adopter. They ghost you and switch. So you never hear why it failed.

I run an AI agency and some of those owners then want to turn the system into a product and they almost always show up with the same plan: hire developers, build the thing & see what happens.

Products mostly fail because the problem wasn't big enough. That's the first thing to test and you don't need a working product to test it. You need a demo and most people build, then demo, then try to sell. That's exactly where they get stuck. Instead flip it: demo, sell, build. What a customer actually buys is the demo and the promise behind it. Every crowdfunding campaign works this way and so does every pre order you've ever placed.

Package that demo into an offer, whether that's a landing page or a 15 minute call and you get to test the riskiest assumptions in any business at once. Is the problem painful enough to earn attention? Does your way of solving it land? Will they pay enough for this to be a business?

First demos flop though. You're still guessing at what customers want and you only get so many pitches before people stop taking your calls. The trap at this stage is leaning on analytics. Metrics can confirm noone's buying. They can't tell you why. The way out isn't a better landing page. It's a better grip on the problem and that comes from discovery conversations where you don't pitch at all. The goal is to understand the customer's problem and communicate.

Understanding it that deeply gets you two things. Designing the right solution becomes much easier and selling becomes easier because when you can describe someone's problem better than they can, they assume you must have the right solution too.

Put those together and you have an offer people can't refuse. The rule is simple... If you can't get enough people to buy, you don't get to build until you've fixed the offer.

TLDR: a half baked v1 gets ghosted now, not iterated on. Run 20 to 30 discovery conversations until you understand the problem better than the customer does. Turn that into a demo and an offer. Sell it and build only once enough people have bought.

You had a good idea, you built it and it went live to zero signups or to 40 signups where not one person logged in twice. Now you're questioning the features, the pricing, the design, everything at once and that spiral is the real problem. Each reason a launch dies has its own symptoms and its own fix.

I run an AI agency and a decent number of those owners try to turn the first system into a product, which means I get a front row seat every time a launch goes quiet. It's almost always one of these…

1. You're solving a problem nobody is desperate about. Demos end with "oh, that's nice" People agree they have the problem then explain why this isn't the right time to fix it.The fix is having more conversations and not more features. Ask whether they'd pay a specific amount today if it worked perfectly. Listen for how often the problem hits, how much it hurts and whether you're even talking to the person who controls the budget. If any of those is missing, the credit card stays in the wallet.
2. You don't know who it's for. The giveaway is signups from 6 unrelated industries, feedback that conflicts instead of clustering and a homepage that could describe any product on earth. Pick one ideal customer, two or three at most and describe them in one sentence. Commit to that person for 90 days. Rewrite the homepage, the emails and the sales call for them only, then watch trial to paid and churn.
3. You built too much. You keep telling yourself you're not ready to launch and the early users who do get in say it's complicated and they don't know where to start. It's a buffet with no signature dish, usually because some competitor has 40 features and you're scared of being judged against them. Cut it down to one clear path from signup to the first moment the thing clicks, then launch to 50 people from your list instead of all of them. Aim for 35 to 50 % of signups reaching that first success.
4. Onboarding kills the momentum. They sign up, poke around and vanish, so usage falls off a cliff after day one. Replace blank screens with sample data or a template, add a short setup checklist and do onboarding by hand for your first 10 or 20 customers. Record sessions and watch 5 new users struggle. It will show you exactly where they leave. (One warning: from the outside this looks identical to reason 1, and you can't tell them apart without talking to people. So talk to people)
5. You shipped and forgot distribution. All your traffic came from one launch post and posting about it five more times produced nothing because posting on social media is not marketing. Pick one or two real channels and run small experiments and if you've spent years building a network instead of an audience, this is the moment to ask it for introductions.
6. You over promised. The complaint is "it doesn't do what I expected," followed by refund requests and a couple of reviews that sting because they're fair. This one is easy to fall into right now, since "AI will handle all of it" is a very easy sentence to put on a homepage and a very hard one to deliver. Read your homepage next to what the product actually does today and tighten until they match then call it early access and promise one painful problem solved.

TLDR: a dead launch has six causes with different symptoms, so diagnose before you fix. Rebuilding features when the real problem is that nobody's desperate or that noone's seeing it, is how you lose a year.

This post is going to be a bit longer than usual but it's worth the scroll :)

I run an AI agency and I sit across from owners every week who've been pitched "AI automation" 3 times that month and still can't tell me what any of it means. Not their fault because the pitches are usually vague on purpose. This post is the foundation and once you've read it you should be able to sort any pitch that lands in your inbox.

Automation is old. The AI part is new.

An automation is a system that does a task without you touching it. Someone fills a form on your website, their name and email land in a spreadsheet and it sends emails and Slack alerts. There's no thinking involved, it just moves things from one place to another. Still useful because it meant nobody got hired to do the tiny annoying stuff.

Then generative AI showed up in late 2022. Suddenly the automation could handle the parts that used to need a human brain. It can read an email and it can pull names and phone numbers out of a 40 page document. It can write a follow up that sounds like you wrote it or take the pile of reports you've been avoiding and hand you one page. That's the whole difference. This stuff makes decisions.

Every pitch you'll ever hear fits into one of these 3 points.

Conversational AI is anything that talks to people. The chatbot on your website, the voice agent that answers or makes calls.

AI tools are where a person presses a button and the AI does one job faster than they could have. AI workflow automation is the third point and the one people mean when they say "AI automation." Something happens or a scheduled time arrives, a whole chain of steps runs, AI makes the calls a human used to make and no one is involved. A workflow can have a voice agent and a tool inside it and still run end to end on its own.

The rest of this post is about that third point.

The six parts of every automation. However fancy the demo, every automation is an assembly line with six pieces.

The filter is the bouncer. It decides what gets through, so maybe only the emails that say "urgent" or only leads with a budget over ten grand.

The intelligence layer is the AI itself and it's the only new piece here. You tell it how to think with a prompt which is just written instructions.

The actions are the work (Sending the email, updating the record, posting to Slack)

The formatter is the cleanup between steps so the next one gets data in the shape it expects. It's boring and it's where half the bugs live. The output is the finished thing, whether that's a message to your team, an updated file or a document ready to send.

One real system, end to end.

I'll use lead qualification, because every business with a website form has this problem, not everyone who fills it out belongs on a call. If you're an accountant who only works with doctors and a builder fills it in, that call is a wasted hour.

Without automation, a rep reads each submission, decides if it's worth pursuing, researches the company, makes the call and writes a proposal. That's hours every week and the lead waits a day to hear anything. The research on speed to lead is brutal because replying immediately instead of the next day moves your close rate by something like 7 to 9 times.

Built properly, it goes like this.

The lead fills a short form. It's short on purpose, because every extra field costs you submissions. AI qualifies them instantly against the same things you'd check yourself, budget, industry, that kind of thing.

If they qualify, they get a booking link by email within a minute, your sales channel gets a plain English Slack summary of who they are and the record is stamped with when they were contacted.

Then a voice agent calls. Before it dials, the system does a quick web search on their company so the agent can open with "I saw you're focused on X." It asks the two or three discovery questions your best rep would. If they don't pick up, it detects voicemail and falls back to the email path. The call gets transcribed and summarized and whether they were interested gets logged.

If they were, AI writes a custom proposal from the call summary, drops it into your template, sends it as an e-sign document and you get notified when they open it and again when they sign.

What nobody puts in the demo.

Platforms change their interfaces and models get deprecated and sometimes you break it yourself. Even people who do this full time spend a big chunk of the week troubleshooting. Whoever builds yours has to stick around to maintain it.

Also know what you're buying because three different things get sold under this label. Education means someone explains it to your team. Consulting means someone tells you where in your business it would help. Implementation is the one where someone builds it and keeps it running

Where to start? Not with the coolest demo. Pick the process where you can name the person who does it and say how many hours it takes them each week. That's your first automation.

TLDR: automations have existed for a decade, AI made them able to read and decide instead of just move data. Every one is six parts: trigger, filter, AI layer, actions, formatter, output, and any vendor should be able to point at all six. A real system runs a whole chain with no human, like form to qualification to voice call to proposal to e-sign. It will break and needs maintaining. Start with the process where you can name the person and the hours.

This post is going to be a bit longer than usual but it's worth the scroll :)

I run an AI agency and I sit across from owners every week who've been pitched "AI automation" 3 times that month and still can't tell me what any of it means. Not their fault because the pitches are usually vague on purpose. This post is the foundation and once you've read it you should be able to sort any pitch that lands in your inbox.

Automation is old. The AI part is new.

An automation is a system that does a task without you touching it. Someone fills a form on your website, their name and email land in a spreadsheet and it sends emails and Slack alerts. There's no thinking involved, it just moves things from one place to another. Still useful because it meant nobody got hired to do the tiny annoying stuff.

Then generative AI showed up in late 2022. Suddenly the automation could handle the parts that used to need a human brain. It can read an email and it can pull names and phone numbers out of a 40 page document. It can write a follow up that sounds like you wrote it or take the pile of reports you've been avoiding and hand you one page. That's the whole difference. This stuff makes decisions.

Every pitch you'll ever hear fits into one of these 3 points.

Conversational AI is anything that talks to people. The chatbot on your website, the voice agent that answers or makes calls.

AI tools are where a person presses a button and the AI does one job faster than they could have. AI workflow automation is the third point and the one people mean when they say "AI automation." Something happens or a scheduled time arrives, a whole chain of steps runs, AI makes the calls a human used to make and no one is involved. A workflow can have a voice agent and a tool inside it and still run end to end on its own.

The rest of this post is about that third point.

The six parts of every automation. However fancy the demo, every automation is an assembly line with six pieces.

The filter is the bouncer. It decides what gets through, so maybe only the emails that say "urgent" or only leads with a budget over ten grand.

The intelligence layer is the AI itself and it's the only new piece here. You tell it how to think with a prompt which is just written instructions.

The actions are the work (Sending the email, updating the record, posting to Slack)

The formatter is the cleanup between steps so the next one gets data in the shape it expects. It's boring and it's where half the bugs live. The output is the finished thing, whether that's a message to your team, an updated file or a document ready to send.

One real system, end to end.

I'll use lead qualification, because every business with a website form has this problem, not everyone who fills it out belongs on a call. If you're an accountant who only works with doctors and a builder fills it in, that call is a wasted hour.

Without automation, a rep reads each submission, decides if it's worth pursuing, researches the company, makes the call and writes a proposal. That's hours every week and the lead waits a day to hear anything. The research on speed to lead is brutal because replying immediately instead of the next day moves your close rate by something like 7 to 9 times.

Built properly, it goes like this.

The lead fills a short form. It's short on purpose, because every extra field costs you submissions. AI qualifies them instantly against the same things you'd check yourself, budget, industry, that kind of thing.

If they qualify, they get a booking link by email within a minute, your sales channel gets a plain English Slack summary of who they are and the record is stamped with when they were contacted.

Then a voice agent calls. Before it dials, the system does a quick web search on their company so the agent can open with "I saw you're focused on X." It asks the two or three discovery questions your best rep would. If they don't pick up, it detects voicemail and falls back to the email path. The call gets transcribed and summarized and whether they were interested gets logged.

If they were, AI writes a custom proposal from the call summary, drops it into your template, sends it as an e-sign document and you get notified when they open it and again when they sign.

What nobody puts in the demo.

Platforms change their interfaces and models get deprecated and sometimes you break it yourself. Even people who do this full time spend a big chunk of the week troubleshooting. Whoever builds yours has to stick around to maintain it.

Also know what you're buying because three different things get sold under this label. Education means someone explains it to your team. Consulting means someone tells you where in your business it would help. Implementation is the one where someone builds it and keeps it running

Where to start? Not with the coolest demo. Pick the process where you can name the person who does it and say how many hours it takes them each week. That's your first automation.

TLDR: automations have existed for a decade, AI made them able to read and decide instead of just move data. Every one is six parts: trigger, filter, AI layer, actions, formatter, output, and any vendor should be able to point at all six. A real system runs a whole chain with no human, like form to qualification to voice call to proposal to e-sign. It will break and needs maintaining. Start with the process where you can name the person and the hours.

I run an AI agency and we find the one expensive, repetitive process inside a business and build a system around it so the company doesn't have to go hire an AI team. Do enough of these and you start noticing the same handful of processes bleeding money in almost every company. These are the five we build most (in order of return, smallest first)

No. 5 The Monday report that writes itself

Nearly every owner I meet spends Sunday night or Monday morning chasing numbers. They spend about 2 hours per week updating CRM sales and accounting numbers and the numbers that are already outdated (minimum two hours of work a week)

What we build pulls from each system on a schedule, writes a one page summary in plain English, flags anything that moved more than it should have and drops it in your inbox. The only real AI in it is the writing and the flagging. Everything else is plumbing.

No 4. Sales calls that update the CRM on their own

Your sales calls happen. Then the notes live in the rep's head, the CRM gets updated on Friday if at all and the follow up goes out 3 days late.

So, record the call, transcribe it, have the model pull out the next steps and the objections and whatever deal details came up, update the CRM, draft the follow up, create the tasks. The rep reads the draft and clicks send.

No 3. Support triage with a human gate

Somewhere between 60 and 80 % of inbound tickets are the same 20 questions. “Where's my order? Can I change the address?” The automation reads every ticket, answers the ones it's confident about from your own docs and order data and it sends summaries and suggested replies to a human.

The escalation gate is the whole product. Without it you get an AI confidently telling a customer something wrong. We built this for an ecom client.

No 2. Documents that have to match other documents

Invoices to purchase orders, timesheets to contracts, every company has some version of this and it's usually one person's entire week. It breaks the same way every time too. About 90 % of the documents match cleanly, and about 10 % do not.

The automation extracts the fields from both documents, matches them, auto approves the clean ones, and puts the exceptions in a queue with a note on why it couldn't match. This one touches money, so build it properly and log everything and don't let it approve anything above a threshold without a human looking at it.

No 1. Reply to every lead in under 5 minutes

Most businesses reply to a web form or a DM in hours, or the next morning and by then the lead has already talked to two competitors. The automation catches every inbound from every channel (web form, email, DM, missed call) and replies inside 5 minutes with the two or three qualifying questions. Qualified ones get booked straight onto a calendar. The messy ones go to a human with the context attached.

It's the biggest revenue jump we've seen from one automation. You're just finally answering the people who already wanted to buy from you.

Don't start with the coolest one. Start with the one where you can name the person who does the task and say roughly how many hours a week it takes them. Some of these you can do in n8n or Zapier over a weekend. The two that touch money and customers (2 and 3) need real code and logging and a human gate, so build them properly or pay someone to do that for you.

TLDR: 5) a Monday report that writes itself. 4) sales calls that update the CRM and draft the follow up. 3) support triage that answers the repetitive 70 % and escalates the rest. 2) invoice and document matching with an exceptions queue. 1) reply to every lead in under 5 minutes and book the qualified ones. Pick the one where you can name the person and the hours and build that first.

Someone pitched me on partnering last week. He had a "proprietary AI system" for a niche and wanted me to resell it. I watched the demo and told him I could rebuild it in an afternoon with Claude Code and that’s how how he had built it too. So I asked what stops a competitor doing the same thing and he said the prompts.

Quick context on why I care… I run an AI agency and we find the one expensive, repetitive process inside a business and build a system around it so the company doesn't have to hire an AI team. Anyone with the same tools can copy every workflow I've ever shipped, including the ones I charge five figures for. I've made peace with that because the workflow was never really what they were paying for.

What they're paying for is that ik where the breakage is. One client was losing somewhere around 20 hours a week matching invoices to purchase orders. The cause turned out to be a single supplier who puts the PO number in the email subject and nowhere else. I found it by sitting in their office for 3 weeks watching someone do the job. A competitor can copy the workflow but they can't copy those three weeks

The other thing you can't copy is the year after. Version 1 works fine on demo data. In production it hit a couple 100 exceptions in the first month and 12 months on the system is maybe 20% AI and 80% accumulated notes on how this one business behaves. Supplier formats that change without warning, approvals that happen over WhatsApp instead of email, that kind of thing. None of it is in the prompt and most of it isn't written down anywhere except in my head and a very long Notion page.

When the software breaks at 2am, someone gets called. Businesses pay for that person to exist and the software is almost incidental. Clients say they could get it cheaper but they still use it because last time it broke I'd fixed it before their team noticed.

The one I didn't expect to matter this much is distribution inside a niche. Client one introduces you to client two. What isn't a moat: your prompts, your model choice, your tool stack, anything you'd put on a slide with a lock icon next to it. All of that is an afternoon away from anyone who wants it and the models change underneath it every quarter anyway.

So if you're an agency, stop selling workflows. Sell the fact that you know where their money is leaking and that you'll pick up the phone when it breaks.

Your moat has to be data you accumulate or integrations that hurt to rip out or distribution you own. Most of us don't have a moat the way investors mean the word. We have a head start and a relationship. That's fine, it's been the agency model since long before AI. The mistake is pretending the afternoon is the asset and pricing it like one.

TLDR: anyone with a coding agent can copy your AI workflow in an afternoon, mine included. What holds up is knowing where a business is losing money, a year of its edge cases, being the one who gets called when it breaks, and referrals inside one niche. Prompts and tool stacks aren't a moat. Price the relationship and not the afternoon.

I know how that sounds. I've done this math with enough clients so I'm fairly confident in it.

The pitch arrives about once a month and does not change. (Open models are good now. The API bill is annoying) The free model is better, so buy a machine, run it and stop paying rent. That's the part that tricks people.

What they miss is that the rented option improves at the same rate. Whatever makes a local model good enough this month shows up on a dozen hosting providers a few weeks later and all of them undercutting each other on price per token. Open weights means the file is free. Somebody with 10000 GPUs will run that same file for you cheaper than your one card can because their card is busy all day and yours is busy for about 50 mins.

Better models also burn less compute per job. A smarter small model matches invoices faster and in fewer retries, which sounds good until you notice it means the box is now busy forty minutes a day instead of fifty. Utilization is basically the whole argument for owning the hardware and every model release chips at it a little more.

The bit people underestimate is that the box stops improving the day it arrives. The model that justified the purchase gets replaced in six months by one that needs more memory than the card. You're either running last year's paid model on a machine or renting the new one anyway. Most people do both and they pay twice.

And depreciation costs roughly 390 bucks per month regardless of whether the machine is busy or not. Rent charges you for the minutes you use. The box charges you for the month no matter what. If the workload runs an hour a day, that gap is the whole business case and nothing else really matters.

Last month I did this for a parts distributor. His rented model costs 170 bucks a month and was busy 17 hours out of 720. He would have paid about $390 a month before power and before the contractor called when the closet went quiet and he still thinks the resale value is wrong.

The pushback I get most is lock in. What if the provider raises prices? with a closed model that's a real concern. With open weights, you can move the same model to a different host in an afternoon and there are always three of them undercutting whoever you're on.

So when does buying make sense? When the data can't leave the building (legally or contractually) Or when the card would be busy most of every day which for a back office process basically never happens and for a product doing continuous inference sometimes does. In either case just buy it. Just put "control" or "capacity" on the slide and take the word "savings" off because that's not what you're getting.

TLDR: a better local model is also a better rented model, and rented prices keep falling. Better models also need less compute per job, so the box sits idle more as the field improves and it costs the same per month either way. Buy when the data can't leave the building or you'd actually saturate the card. Otherwise rent and stop calling the box a saving.

I need to get this off my chest because it's been building for months.

Every other video in my feed now is some 18 or 19 year old kid saying he's doing $200k, $300k a month from his AI automation agency. By selling to small businesses apparently. And it's mindboggling to me because I know it's a lie, I know it's deliberate, and I know exactly who it's hurting.

Some context so you know I'm not just bitter. I've run an Agency for about 8 years now, we started with SaaS MVPs, GTM and recently transitioned to AI Automations. And its not a side thing for me.

Here are my actual numbers. A bit over $120k in that first year of building AI Automations. The best month I ever had was $35k. Once. Most months land somewhere between $10k and $15k. That's with a full pipeline and me working on it every single day.

I'm telling you that so you have a reference point. That's a full year in with paying clients. And it's a tenth of what these kids claim on a slow month.

I've worked with small businesses. I promise you they are not paying a teenager $300k a month for automations. A small business owner will push back on a four figure retainer. They'll ask you to explain it to their tech savy small kid first (this has happened to me once lol). That's the reality of that market.

And think about it for one second. If you were doing $300k a month in automation work you would not have time to film a YouTube video and ask me to sign up for your newsletter. It does not make sense. The companies I've seen actually doing that number are real companies with sales teams and long sales cycles and people who've been in B2B for a decade. The kid with the ring light and the Notion template is not one of them.

Is it possible to make that much? Sure. Maybe 0.1% of people who try. And the ones who do don't look anything like these videos.

What actually pisses me off is what this does to the market. This is an incredible field. Every business is going to need some kind of AI in it and there's real money in building that. And then someone who's serious about it watches one of these videos, quits their job and makes $0 for three months and decides they're the problem. The kid who sold them the dream lost nothing. That's the part I can't get over.

I'm only writing this because people keep DMing me the same question. Is this real, have you ever made this much. And I'd rather answer it once in public than keep typing the same reply.

So here's the answer. They're lying. I'd bet money on it and I'm saying that from experience. If you want that kind of money out of this industry it's going to take years of hard work, same as any other industry. There's no lottery ticket in here.

Rant over. Be careful who you learn from.

TLDR: a year running an AI agency full time, best month $35k and most months $10-15k. The teenagers claiming $300k a month from small businesses are lying and it's hurting people who actually want to do this.

Ok so this started as a joke experiment and then it worked, so now it's a process.

Quick context so you know where this is coming from. We're an AI agency. The whole pitch is we find one expensive, repetitive problem inside a company and put AI around it so they don't have to hire a full time AI team. Which means our own outbound has to work or we don't eat. No SDRs and no outbound agency, we DM people ourselves. This is the workflow we use to get our clients.

Last month one of these got an actual reply, with a question in it, from a company doing about $400M. That is not a company that needs to reply to a small shop. We'd been sending them as a casual test and after that reply we made it the default.

I'm aware this reads like the exact kind of post I usually roll my eyes at. You can go do it in an hour and see for yourself though.

The core idea is dumb simple. Buying is psychological. You can stack 30 tools on top of a message that's aimed at the wrong person with the wrong framing and it still dies in the inbox. So before any writing happens we make Claude work out a few things about the decision maker that almost everyone skips:

How old are they. A 28 year old head of ops and a 58 year old COO do not respond to the same message and pretending otherwise is how you get ignored by both.

Who actually owns the budget. In a 50 person company the person who feels the expensive problem every day is usually a director and the C-suite just signs. Everyone DMs the CEO anyway.

How long they've been in the seat. Six months means they're still building the playbook and still shopping. Four years means they're locked in and you'll have to pry them out.

What's their stack. If they're still running 2021 software, the repetitive problem is probably sitting right on top of it.

What's changed lately. They posted a job for an in-house AI hire or a new ops exec came in or a launch is about to bury some team in manual work. Any of that means the problem is getting expensive right now.

What are they posting about. If a COO is suddenly posting about AI adoption, someone above them asked what the plan is and you want to be in the inbox that week.

We tuned all of this for what we sell. Swap the signals for yours.

Setup is small. Claude with the Gamma connector switched on, plus a LinkedIn account. No agent framework and no 30 tool stack. Everything below is just what we ask Claude to do, in order.

Step 1. Don't buy anything. LinkedIn settings > data privacy > get a copy of your data > tick connections. They email you a CSV in a day or two. Your existing network is a better list than anything you'd scrape and you already have a reason to message them.

Step 2. Find what the buyer actually wants. Paste your offer in one paragraph plus who you're targeting (title and company size, industry if it matters) and ask Claude for the real problem underneath the surface complaints and why they'd buy this week instead of next quarter. Push it past the obvious answers, the first pass is always generic. This is the raw material for everything after.

Step 3. Turn that into a person. Ask it to build a full persona from the same targeting. The words they use. What they're scared of at work. What they actually care about versus what they post. You want it to read like a human instead of a job title.

Step 4. Get your openers. Give it the offer plus the persona and ask for 8 different ways to open a conversation, each one built off something specific in the persona. None of them should be the "quick question" template every SDR on earth is running right now. If one of them is, throw it out.

Step 5. The meme deck. This is the part that gets replies. Ask Claude to look up [company], find the expensive repetitive problem, write one meme tied to that exact pain and build a 5 slide Gamma deck around it. Slide 1 is their problem. Slides 2 to 4 are how you'd put AI around it, laid out clearly enough that they could take it to their own team if they wanted (most don't). The meme sits in the middle. If the deck comes back sounding like a pitch, tell it to make it about them and cut the about us stuff. That one line fixes most of it. The logic is a founder is scrolling, half doubting your DM, and then hits something that makes them stop for a second. That second is the whole game.

You can plug in Apollo or whatever and run this on a list. Don't. Do 5 by hand first. Claude will screw up one every few decks and you want to catch that while it's cheap. Once you've seen 5 good ones you know what good looks like and then you scale.

The DM itself is short. Something like "built this for [company], figured it'd help with [the thing they're dealing with]" and the deck. The deck is the message, the text is just the reason to open it.

Ghosters get a plain meme, no deck. Ask Claude for one tied to the same pain. Some of them come back cringe, tell it to redo it non cringe and it usually does. Something dumb and funny beats "just bumping this" for the fourth time.

That's the whole thing. It looks easy written out. It took 100 hours to get to something that doesn't embarrass us, mostly because the first batch of decks were bad in ways we had to learn from. Try it on 5 people this week and come back and tell me what broke.

TLDR: we're an AI agency and our cold DMs are 5 slide meme decks built with Claude and Gamma. Claude works out the psychology of the decision maker before writing a word. A $400M company replied. Do 5 by hand before you automate anything.

Ok I need to vent about this because I don't think enough people are saying it.

I run a small agency (8 of us, we build agent workflows for a couple of ecom brands and some boring B2B stuff). Been on this sub since it was like 40k members. Back then you'd post a question and get 3 replies and one of them was from someone who had actually built the thing and knew exactly where it breaks. That was the whole value of this place.

Now I scroll the front page and I can't find a single human.

I'm not exaggerating for effect. Every post is the same template. Some guy built an agent and it made a suspiciously round number. Then the lesson he learned. Then a question at the end for engagement. Ok whatever, that's been around forever. But then look at the comments. 20+ replies within the hour and every single one agrees with OP in that soft customer support voice. They all do the "it's not X, it's Y" thing where they reframe something OP didn't even say. And the em dashes. Every comment has em dashes in it. Who on reddit types em dashes? I'd have to google how to make one on my keyboard. Someone who's annoyed and typing on their phone at 11pm does not produce a perfectly balanced sentence with a dash in the middle of it.

And everyone talks like they know everything. Every reply reads like a keynote. Not one person ever says "we tried this and it broke and we couldn't figure out why", which is what actually building this stuff is like 80% of the time btw. The tooling changes every month, anyone who's shipped something real is unsure about most of it. These accounts are never unsure. Never disagree with anything either. Half of them were created this spring and they post at 3am with the exact same energy as 3pm.

And I'll say the part that's going to get me downvoted. The humans that are still here might be worse than the bots tbh. Most of the "agency owners" posting are people with zero clients who just paid 2k for a course on starting an AI automation agency, and they need the fake money posts to be real because otherwise they got scammed. That's the whole economy of this sub. Someone sells the course and the bots make the results look real in the comments so the next guy buys the course. Not one of these people has ever had a client change scope on them at 5pm on a Friday. And half of what gets called an "agent" on here is a Zapier flow with one LLM call in it. The other half is a demo that has never touched production.

And this is the AGENTS sub lol. Everyone here knows exactly how easy this is to do. I'm sure half of you have built a reddit posting bot as a weekend project. Some of you probably have one running right now and are reading this through a summarizer. The tool companies obviously know too, that's why every 4th comment is somebody's product plugged in with the same sentence structure as the last plug.

I don't know what the fix is. I don't think the mods can do much either tbh, not their fault. I just wanted to say it out loud because everyone's acting like this sub is fine and it's a bunch of cron jobs complimenting each other while the 5 remaining humans accuse each other of being bots.

Anyway. Downvote me idc. I already know what the first ten replies are going to look like.

TLDR: this sub is bots talking to bots and the humans left are mostly course buyers who need the bots to be real.

Ok I need to vent about this because I don't think enough people are saying it.

I run a small agency (8 of us, we build agent workflows for a couple of ecom brands and some boring B2B stuff). Been on this sub since it was like 40k members. Back then you'd post a question and get 3 replies and one of them was from someone who had actually built the thing and knew exactly where it breaks. That was the whole value of this place.

Now I scroll the front page and I can't find a single human.

I'm not exaggerating for effect. Every post is the same template. Some guy built an agent and it made a suspiciously round number. Then the lesson he learned. Then a question at the end for engagement. Ok whatever, that's been around forever. But then look at the comments. 20+ replies within the hour and every single one agrees with OP in that soft customer support voice. They all do the "it's not X, it's Y" thing where they reframe something OP didn't even say. And the em dashes. Every comment has em dashes in it. Who on reddit types em dashes? I'd have to google how to make one on my keyboard. Someone who's annoyed and typing on their phone at 11pm does not produce a perfectly balanced sentence with a dash in the middle of it.

And everyone talks like they know everything. Every reply reads like a keynote. Not one person ever says "we tried this and it broke and we couldn't figure out why", which is what actually building this stuff is like 80% of the time btw. The tooling changes every month, anyone who's shipped something real is unsure about most of it. These accounts are never unsure. Never disagree with anything either. Half of them were created this spring and they post at 3am with the exact same energy as 3pm.

And I'll say the part that's going to get me downvoted. The humans that are still here might be worse than the bots tbh. Most of the "agency owners" posting are people with zero clients who just paid 2k for a course on starting an AI automation agency, and they need the fake money posts to be real because otherwise they got scammed. That's the whole economy of this sub. Someone sells the course and the bots make the results look real in the comments so the next guy buys the course. Not one of these people has ever had a client change scope on them at 5pm on a Friday. And half of what gets called an "agent" on here is a Zapier flow with one LLM call in it. The other half is a demo that has never touched production.

And this is the AGENTS sub lol. Everyone here knows exactly how easy this is to do. I'm sure half of you have built a reddit posting bot as a weekend project. Some of you probably have one running right now and are reading this through a summarizer. The tool companies obviously know too, that's why every 4th comment is somebody's product plugged in with the same sentence structure as the last plug.

I don't know what the fix is. I don't think the mods can do much either tbh, not their fault. I just wanted to say it out loud because everyone's acting like this sub is fine and it's a bunch of cron jobs complimenting each other while the 5 remaining humans accuse each other of being bots.

Anyway. Downvote me idc. I already know what the first ten replies are going to look like.

TLDR: this sub is bots talking to bots and the humans left are mostly course buyers who need the bots to be real.

I built a dashboard for a client a few months back. I shipped it and cleared the invoice. 3 weeks later they wanted one new feature so I opened the repo with my AI assistant and asked it to extend the order sync. It read the sync logic, decided my duplicate call was a bug and handed me a cleaner version without it.

And the tool hadn't forgotten any of this. It could see every file and it just read my code and formed its own wrong opinion. Every thread I see about AI coding calls this stuff context loss and tbh I don’t think that’s the diagnosis anymore. The model disagreeing with your context is a separate problem from forgetting because on first read the diff looks like an improvement.

It has been 8 years of me building products for clients and imo the expensive knowledge was never the code. Its stuff like why the retry looks stupid on purpose or which shortcut got approved on a call nobody wrote down. Also, ask the assistant why some piece of code works on 3 separate days and you'll get two or three confident answers that don’t match each other. At that point I’m debugging its memory of my product which is not a job I ever asked for. (I once deleted "dead code" myself that was very much alive, so ig the machine learned from the best.)

The fix was that… I just keep a Claude. md in every client repo now.... the do not touch stuff plus the reason behind each weird decision. Write it once and the tool reads it every session.

I was very productive in the first 5 weeks of a client project. I made prompts, added features and the agent shipped it in a week and demos were completed every Friday. I started wondering why I spent years typing code by hand like a medieval scribe.

Then on 6th week the client asked a question about a system with my name on every commit: why do the totals round the way they do? and I had no idea and then I spent the evening debugging my own codebase (Basically Git-blaming myself).

I've been building software for other people for eight years and whatever the contract says, the actual job has always been answering for the code later. The code gets written maybe ten times faster now and I read at the same speed I did last year. So the project didn't get hard because it got big rather the understanding of it turned into the main job. On client work it goes past my own understanding too, since whoever they hire after me will have questions and those questions will have my name attached.

I had been trading codebase literacy for speed without writing the trade down anywhere. What I do differently now is that I read the agent's writing while they were writing and I log the reasoning behind decisions. I also write a line item for the time I read the quotes.

The most expensive thing that I ever typed took 40 secs and literally contained 5 words. A 3 person team asked me whether my product which is built for people who work alone, could add roles and approvals and I typed yeah we can build that. I shipped it in 9 days and felt genuinely proud of the speed which tells you how little I understood what I had just agreed to.

The feature worked and that was the actual problem. Teams started finding the product and teams travel with their own weather, audit trails, admin views, questions about permissions I had never imagined, most of them reasonable, which somehow made it worse. My support inbox changed accent within a month. The homepage still said built for people who work alone but the backlog had stopped believing it a while back. No one really warns you about this part, when a feature request can rewrite your ICP without anyone calling a meeting to approve the change.

I spent the last 8 years building products, so every time I said we can build that, the entire WE who had to live with the consequences was me.

The code was not the expensive part. I have deleted code plenty of times and felt nothing. Deleting a promise has a different name and it arrives with emails. The sentence costs nothing at the moment you say it which is exactly why it gets said so much and the invoice lands on later

What I had treated as a feature decision was a business model decision wearing casual clothes. Roles meant teams and teams meant onboarding more than 1 human and seat pricing I had no answers for, permission edge cases I am still patching on Sundays.

So I built myself a rule, I am allowed to say we can build that only after saying the second sentence out loud on the same call and here is what we would be promising. Most requests do not survive the second sentence….

Startups budget their fear around money and money at least announces itself when it runs low but in case of promises, they don't, instead they compound quietly and in your own voice and I don't really have a fix for that beyond the second sentence.

A few years back a client of mine closed their first real enterprise deal, about 20K for the year. I had built every screen in the deck they pitched with so it felt like my graduation too. Then after a few months in I noticed that the person who signed it had never logged in. I checked the logs twice to be sure and reading logs is literally my job. Meanwhile a customer paying them 500 a month was in every weekday at 9 as if the product was part of her breakfast.

Getting to yes literally took 6 calls I sat in on for demos, a deck that went to version 9, a security questionnaire longer than the codebase I had written and a discount the founder invented on the spot. Across all those hours I think the product was on screen for maybe 20 minutes. So basically we were mostly selling reassurance to people who were never going to open the thing.

Well I spent 8 years building products and it took me quiet long to notice the two kinds of money were telling us 2 different things.

The 500 a month customer never sat through a demo or got a discount and no manager was making her show up. She found the page, worked it out alone, paid a company she had never spoken to and she is still there. The 30 enterprise seats logging in because they were told to, that's attendance data. Her 9am login is the only number in that dashboard I fully trust and I built the dashboard.

The roadmap kept bending toward the big customer the whole time and not because they demanded anything, they never demanded anything but the renewal date did the talking. (I once reordered an entire sprint because someone on their team gave a feature idea a thumbs up emoji)

I'm not saying small customers are the only ones worth having. The 20K paid their runway and my invoices and I like my invoices paid. It just didn't tell us what to build. All of that was sitting at the 500 dollar end of the spreadsheet and for years we had it backwards, plenty of revenue coming in and not much idea what was actually working.

If you are staring at a roadmap rn then it's worth asking who actually wrote it.

Last month I said no to the biggest deal one of my products has ever been offered... a single contract worth about 2 months of my current revenue (for a whole week afterwards it felt like I had committed a small crime against my own bank account) ask list ran to custom features, priority support and a monthly call and the money was real. My reply took 40 mins to write and came out 4 lines long (I counted becoz apparently thats what guilt does).

I get why we chase these man, revenue is the number everyone else can see while margin is the one only you live with. The trap is that good revenue and bad revenue look identical on the day they arrive (difference only invoices you later).

I've spent 8 years building products and the only reason I recognized this deal is that I took its uglier twin a few years back and paid full price for that lesson.

When a customer pays you, the money moves toward you and in that exact same moment capital moves AWAY from you, your hours and your roadmap slots, the only two things a small product runs on. So every customer is a capital allocation decision whether you file it that way or not. Custom work is capital that gets consumed by one buyer once. The same hours put into the core product get invested for every customer you have and every one you haven't met yet.

The uglier twin was a contract that came with custom everything and for 5 months my roadmap belonged to a company that was not mine. My quiet customers waited politely two of them stopped waiting and the contract ended anyway after 8 months…. so I kept the distraction and lost the compounding and that is the whole tuition bill. There is still a feature flag in that codebase named after the company and I just couldn't bring myself to delete it lol

Saying no last month wasn't discipline but.... The math from that first contract had finally sunk in. The 15 hours a month this deal wanted are going into the thing my quietest customers have been asking about all year and that work ships to everyone at once. I still open the old email sometimes and look at the number but growth for me now means the return on my next 100 hours more than the size of the next cheque. Some cheques that read that way are just expenses with good manners