I run the most automated org on earth,
using the AI Agents I built.
@unicornplatform
@indexrusher
@listingbott
@seobotai
@devhunt_
24 startups → https://t.co/1ML5MmAQ7X
17 subscribers
Apr 16 • 7 tweets • 2 min read
The “distribution is the king” crowd is mostly the founders who built an average product, failed & blame distribution.
Marketing is an amplifier, it isn’t magic.
Ofc, u need initial boost to get eyes on your product.
How to get first 100 users if you’re not a marketing genius: 1. Launch on all launchpads
- @ProductHunt
- @devhunt_
- uneed
- @MicroLaunchHQ
- @FazierHQ
- @Peerlist
- launching today
- @tinylaunch
- @IndieHackers
- ctrlaltCC
- simplelister
- @BetaList
- @AppSumo
- Dailypings
Apr 15 • 7 tweets • 2 min read
100% autonomous AI Agents:
1. @seobotai - Blog SEO on autopilot.
- it finds the relevant topics
- performs the research
- has access to real time information
- builds up blog articles
- does internal and external linking and more
Apr 8 • 22 tweets • 5 min read
I'm 36,
At 11, I started my first business.
Over 50 businesses in 25 years, learned a lot.
Here are 21 rules I live by:
1. Enjoy.
It'll consume your entire life.
It'll take a decade on average.
Learn to enjoy the process instead of chasing the outcome.
Apr 4 • 25 tweets • 6 min read
I did it 🥹
Halfway towards my dream of reaching a million users!
- 4 years for 0 -> 25k
- 2 years for 25k -> 250k
- 6 months for 250k -> 500k users
Everything I did to get here
my marketing failures & successes 🧵: 0. @unicornplatform is a website builder for busy founders & small teams.
As I'm bootstrapped, I need cost-effective or free growth strategies.
I've tried 21 growth methods:
Mar 30 • 10 tweets • 2 min read
I'm 100% sure AI & robots will take over almost every job in my lifetime.
I spent quite some time thinking about the future. This prediction is unlike anything anyone else has ever made.
Here's what jobs will survive & what new ones might be created:
1. Ultra-narrow niche expert, aka scientists.
Those who devote their entire life to one thing and get really good at it.
AI is rational; humans aren't. Humans tackle hopeless tasks, hoping for a rare breakthrough that happens by accident. AI is too "smart" to do this.
Mar 27 • 12 tweets • 4 min read
AI can:
> generate UI, sites, logos, banners, images, photos, movies..
> write books, articles
> generate 90-100% of the code
> hear & speak with emotions
indistinguishable from humans
> control robots/cars
None of this was possible 5y ago.
Feels like a dream tbh. Examples 🧵: 1. Robots went from clunky tele operated devices straight to the terminator and skynet phase.
The world soon will be full of them, just like we have iPhones in every pocket or hand today.
Mar 26 • 16 tweets • 3 min read
My simple framework for Startup ideas:
(it has worked for me 20 times)
0) Build an AI Agent that can replace entire professions/jobs/tasks.
It's a super difficult tech challenge, but if you make it, the distribution will be easy.
I've done it with seobot, which replaced my SEO department. Never had a product that grew faster than this one.
Mar 20 • 27 tweets • 10 min read
AI won't replace entire profession, but it's replacing the bottom 20-80% in {translation, design, coding, content, marketing, sales, design, operation, account, law}
Micro teams like mine beat corporations
because AI brings huge leverage for A players
Real examples of AI:
1. AI replaced junior developers for me.
I used @Replit AI agent to build a real tool I needed. Back in 2022, I'd hire someone on upwork and wait a week; today, it took me an hour of prompting to go from 0 to launch. The link:
I build AI Agents to replace office workers, but these demos convince me! All physical labor will be gone to robots, too. (even the world's oldest profession).
Just watch it if you disagree. The biggest robot thread ever (50 demos):
1. Neogamma.
General purpose humanoid robot for home.
Mar 13 • 10 tweets • 2 min read
Building a “SaaS people wanna pay for” is sooooooooo hard 😩
AI made it easier to build things, but it didn’t really change the game the products people wanna pay for and share with friends.
How I build products people love:
(very different from what you’d expect)
1. I validate the idea first. Sometimes it takes me years to go from ides to star building it, because I wasn’t sure if people actually need this.
I pitch it to people on internet, in DMs, at the dinner table and so on. If I don’t get “wow, yeah, I want that”, I don’t build it
Mar 12 • 21 tweets • 9 min read
AI Coding is the new No-Code! It's a fact.
Non tech founder, designers, marketers & anyone can build software now.
Zero entry barrier! No limitations! Super cheap!
But complex apps still need real coders; AI won't replace them til 2030.
19 AI Coding Agents (for non coders):
1. .
Can handle full-stack web, mobile, and desktop apps. Can even build games.
Chinese AI startups: 1/6th of US funding, bad press, sanctions, brain drain, communism, little English proficiency, and no talent influx..
But after using Manus AI, Deepseek, Trae, Kling, Vidu, & Ying, I think the US is in trouble.
At this pace, China will dominate AI.
Demos:
1. Manus AI.
All-in-one AI Agent (browser operator, deep search/research, MCP, Code Exexution
Mar 6 • 8 tweets • 4 min read
What is MCP & why it's a big (huge) deal:
(model context protocol)
TLDR: MCP makes it possible for AI Tools to use external tools. E.g. Chatbot/IDE/AI-Agent can use Gmail/GoogleDrive/WeatherApp etc.
Detailed explanation for both, tech & non tech people (+demos):
1) AI Tools (chatbots, wrappers, agents, code generator, etc) wanna talk to external systems.
In pre-MCP world, one would have to write code to connect AI tool to the external system via API. Which meant every connection had to be pre-coded.
It also meant that every AI tool had to hard code its connection to every other tool. So if there are 1000 AI tools and 1000 external tools, then 1000000 hard-coded connections via API.
2) MCP is a standard protocol. This means that every AI tool has to implement this once, and then it can connect to thousands of external tools via this protocol.
3) The same goes for external tools. They all have to create an MCP server just once, and all AI tools that support MCP can connect to them.
4) It's a huge deal. Imagine 10k AI tools and 10k external tools now all have to implement MCP just once each. So it's 20k implementations. Versus 10k*10k=100M implementations.
5) This whole thing can also run on the cloud or on local computer.
See demos:1. Claude desktop app uses MCP server to make a screenshot of a given website and converts it into HTML.
MCP allows you to simply provide a URL to the chatbot, instead of youtaking a screenshot and pasting it into chatbot.
Don’t do this until you made $10k with your startup:
> hire employees > paid google/fb ads
> website redesign > registering a company
> outsource > add more features
> refactoring > optimization
> raise VC funding > start a new project
Why:
No employees!
> they can perform well-defined tasks, but at the beginning most tasks need creatively and exploration.
> they don’t care as much as u, they won’t be obsessed by making the product better, listening the users and working their ass off. The customers gonna feel it
Feb 28 • 7 tweets • 2 min read
We hit the wall with LLMs
> Two years ago, GPT4 made AI wrappers & Agents possible.
> Sonnet 3.5 solved the AI code generation.
> I just tried Sonnet3.7, GPT-4.5, O-3, Grok, and Gemini...
> Not impressive. Not even close to gpt3->gpt4 jump
What's next:
1. These won't lead to ASI:
- scaling & training on more GPUs
- training on more data / synthetic data
More progress will come from the application layer: the wrappers, AI agents, and hacks we all hardcode in our apps to compensate for AI limitations.
What to build (the ideas):
Feb 27 • 11 tweets • 2 min read
Every profile here with no followers & no reach thinks it's all about hacks, luck, retweets from big accounts, and the number of followers.
I thought the same for 18 years, until I understood what makes content viral.
The Truth (the TLDR is at the end):
1) The content types:
- 99.9% of it is either boring or not useful.
Even the author doesn't wanna reread it.
- 0.09% is useful/valuable content that's boring or difficult to read.
- 0.01% is the viral content. It makes you wanna share it with a friend, bookmark it, or reply.
Feb 26 • 16 tweets • 7 min read
I'm working on 24 startups simultaneously
(half a million b2b users, multimillion ARR)
No VC funding, employees, calls, office, managers...
Each business is 100% async over chat:
> me: idea, design, UX & marketing.
> comaker: coding, product & support.
Why, how, what: 1. After wasting my best years for a decade in VC-backed space, startup accelerators, conferences, meetings, scrums, I decided to do a hard pivot.
In 2023, I started my bootstrapping journey to build the world's most automated org to democratize startups for everyone
The most complete list ever made:
1.
- it can clone a product when you drop the link to it
- has connections to things like the movie db, hackernews and more
- auth with one prompt
Good if you wanna create functiniing products with just a few prompts.
After seeing these humanoid robot demos, I bet you'll be convinced that all manual labor will be gone to robots.
(even the world's oldest profession will be taken by them).
All 26 humanoid robot demos:
1. NEO Gamma (Humanoid for Home)
(black mirror episode vibes)
Feb 21 • 18 tweets • 5 min read
I extracted the most common failure patterns from my 20-year-long startup journey.
(spoiler: most successful founders have done the same thing, while failed ones did many different things)
Why Startup Founders Fail:
1. Solution looking for a problem.
This one accounts for over 50% of failures I've seen & done. Founders build a solution first and then go to users, pitching it and trying to convince them they have such a problem.
The problem often isn't serious enough to change their habit.
Feb 20 • 8 tweets • 5 min read
Web Agents are automating the entire class of jobs:
> fill out forms (file complaints)
> signup for things (apply for a visa)
> browse web (buy tickets)
> collect data
These AI agents are actually good for humanity - they remove the most boring jobs.
Tools I use to build them:
1. The agents typically translate user goals into browser automation.
I've tried 30+ tools for this (gonna post a dedicated thread on this topic soon). My fav so far is: .
My @listingbott agent heavily relies on these tools.