🌿 3х Founder → growth, bootstrap, $600k ARR, no VC, $0 marketing, and 💵 3 exits. Building @flowmapp ⚡️ @FoundbaseHQ + @aaplyHQ
Joined January 2009
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- Followers26.8K
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🎉 Product of the Day N1 🥳
Thank you to everyone who gave a little bit of your attention 💚
Your participation and support is our greatest strength.
@flowmapp's main asset is the people and community around the product.
And I'm very happy that so many people from all over the world helped it happen.
Kudos to @ProductHunt and #buildinpublic communities.
🙌
AI made generating marketing assets almost free:
- landing pages
- videos
- copy
- images
Now everyone can produce everything
And most founders still can't get their first 100 customers
PRODUCING STUFF WAS NEVER THE PROBLEM
сlaude can write job post
now it can find candidates for it 🤯
hiring for founders sucks:
(spending 3 days checking GitHub and trying to find the right people in linkedin)
my mate Jason just released a game-changer
OpenSource LinkedIn Recruiter:
> paste a job post into your AI agent
> it finds candidates
> ranks them based on their actual work
> gets their contact details
all for around $0.19 per candidate!
for founders and small teams, this is where AI agents start making real sense
check this:
Introducing OpenSource Recruiter for Claude
- Paste any job post → 50 ranked candidates
- Personal email + mobile, $0.20/candidate
- No $170/mo seat, no 30-InMail limit
- 0% markup, fully open source
Try it at treg.to/recruit
Repo link below 👇
Most AI agents are built to save companies time
Vene is building one to save families time:
It helps schedule follow-up appointments, get test results to the right specialist, and follow up on paperwork the insurer needs before it can approve care.
I think some of the most valuable AI agents won't be the ones doing impressive things
They'll be the ones taking care of human everyday life
🤝 Paid partnership
Today, I'm launching Vene: your AI advocate for healthcare.
I used to spend a dozen hours a week managing care for my dad, a disabled veteran, and my mom, who has a severe autoimmune disease. Healthcare was a full-time job for my family.
Our goal is to end the burden of care for every family:
When you're sick, or caring for someone who is, the hard part is everything after the hospital: the referral that never arrives, the test result nobody calls about, the bill that makes no sense, and everything in between.
For my dad, he spent hours on the phone to book an MRI. When he showed up, they told him to his face that insurance had stopped covering it. Then insurance told him to call a list of other offices and get the paperwork sent over himself, and he ended up giving up.
That’s why we’ve trained Vene to handle the toughest aspects of healthcare:
- Coordinating several specialists at once
- Challenging surprise bills and treatment denials
- Catching missed follow-ups and care gaps
My mom uses Vene to coordinate her primary care and endocrinologist, automatically refill and renew her prescriptions, and manage my little sister’s dental appointments.
They were my first users, and now over 5,000 families use Vene, and we're deploying it to another 50,000 patients across provider networks in the US.
My Playbook to distribute AI startup from $0 to $30k MRR:
❇️ 1 - Founder-led
→ pick one very specific audience
→ post daily on X
→ post weekly on Reddit
→ share demos, use cases & customer stories
→ turn every feature into 5-10 pieces of content
→ engage with potential customers every day
(your first distribution channel is YOU)
❇️ 2 - Community Engine
→ find 20-30 creators in your niche
→ build relationships before asking for anything
→ get your product into the hands of real builders
→ turn their feedback into content
→ make it easy for users to share what they built
(word-of-mouth beats any growth hack)
❇️ 3 - Launch Machine
→ every major feature deserves a new launch
→ build a list of 100 people who can amplify it
→ personally DM founders, creators & communities
→ coordinate early engagement with your network
→ repurpose every launch across 5+ channels
(one launch is an event, repeated launches are a strategy)
❇️ 4 - Retention
→ onboard the first 100 customers personally
→ talk to users who cancel
→ talk to users who buy
→ double down on features people actually pay for
→ turn happy customers into case studies
→ ask for review
→ ask for public mentions
→ feature your clients (they will repost)
$30k MRR is about building a distribution
this is marketing
it should be done daily
when I see founders posting ARR growth charts like this
jesus, when is it my turn?
it's been 10 weeks of 50% week-over-week growth with pancake.ai
no matter how many startups you’ve built, the next one still makes you feel like a beginner. there’s always something you’ve never done before that you suddenly need to figure out.
jumping out of a plane, trying to break a guinness world record. it's all fun!
but the best part is still realizing you’ve built something other people think is worth paying for.
more to come!
wtf this is actually insane:
> new 40B AI coding model called Flint
> runs locally on your MacBook or RTX hardware
> 125+ tokens/sec on MacBook at short contexts
> open weights under Apache 2.0
> no API bills, no token limits
> built from scratch in under 4 months
> AI helped design and improve the AI itself
crazy what @recursive_si are doing:
AI builds better AI
🤝 Paid partnership
Introducing Flint, @Recursive_SI’s first model: a fast local coding model built with our automated research system, the Eureka Machine.
• Best-in-class fast local coding
• Up to 2x faster than comparable models: 125+ tokens/sec on a MacBook Pro, 150+ on RTX Spark
• Built from scratch in under 4 months
Private, unmetered intelligence on your own machine. Open weights available now on @huggingface, run it locally on your favorite framework or try it for free on @opencode or @pidotdev.
"sign in with Google" for AI agents
→ AgentMail gives AI agents their own email inboxes
→ one API call to create an email address
→ agents can send, receive & reply to emails
→ handle invoices, customer requests & signups
→ 10M+ agent inboxes already created
→ over 1 BILLION emails processed
50x growth in one year
@michaelhyunkim idea on the infrastructure for AI agents:
not every company has an API
but every company has email
🤝 Paid partnership
Today, @agentmail has processed over 1 Billion emails.
A year ago, we processed under 20 million.
So we figured it was time for AgentMail to grow up a little too :)
wtf this is actually insane:
> AI knowledge base for humans + AI agents
> connects GitHub, Slack & meetings
> detects outdated docs when your code changes
> finds contradictions, gaps & duplicates
> automatically updates eligible docs
> gives your AI agents reliable company context
it checks if agents're not learning from outdated knowledge
🤝 Paid partnership
Trillions are pouring into the race to build the first general superintelligence, but leveraging your own specialized know-it-all is now possible as of today.
I built the knowledge systems at @stripe and @uber. Then I helped Anthropic, Metronome, and Graphite build a killer developer experience. Everyone wants Stripe-level quality, but that bar is too low.
Falconer gives you and your customers complete, specialized intelligence: an internal knowledge base and external documentation in one beautiful package. Falconer is the ultimate trust engine to manage your context: self-driving, observable, and agent-friendly.
I co-founded @falconer_ai with @mbenedetto212 and assembled a team of know-it-all builders. We're backed by fellow know-it-alls @thegp, @BoxGroup, @svangel, @karimatiyeh, @benln, @zachlloydtweets, @CeciStalls, @MerrillLutsky, @scottmac, @malthe, and @adamjstevenson, with angels from Anthropic, Stripe, Meta, Cursor, Replit, and more.
Frontier intelligence companies like @FireworksAI_HQ and @⬛⬛⬛⬛⬛⬛; fintech companies like @payabli and @vori; and healthtech companies like @thatch_ai use @falconer_ai because they all share the same vision as us: the knowledge you earn should belong to you.
Now you can know everything, so you can build anything.
okay pretty wild:
1,000 POSTGRES DATABASES on 659 MB of RAM
db for AI agents written in Rust
open source, 100% free, let's test it:
🚨Introducing a new database: PGX 🐘
Postgres for AI agents. In Rust. pgx.dev
One runtime. Thousands of Postgres databases.
⚡ Up to 100× less idle memory
⚡ 1,000 databases in just 659 MB RAM
⚡ Clone a 674 MB database in 85 ms
⚡ ~0.7 MB per idle database
RUST. OPEN SOURCE. FREE.
No containers per database.
No heavyweight instances.
No production baggage.
Real Postgres. Built to be disposable.
xitter.cf/alxshp/status/21100494…
You can vibe code your competitor's features
You can copy landing
You can copy articles
But you can't copy:
- 5 years of trust they've built
- audience they've built
- genuine reviews
- personal brand of founders
- founder's charisma
- their experience and insights
that is a real value in 2026, guys
pretty SMART:
> AI that simulates your target audience
> connects directly to Claude via MCP
> upload ad creatives for testing
> AI personas grounded in real human data
> predicts how segments might react
> explains which ads resonate and why
this can save $10,000 by testing on simulated customers
try: atypica.ai/?via=atypica
Your ad budget goes further when you test the idea before buying the impressions.
Three ad concepts. Same product. One emotional, one focused on features, one built around lifestyle.
Connect Atypica to Claude via MCP, upload your creatives, and explore how your target audience might respond.
Atypica interviews AI personas grounded in real human data to uncover which concepts resonate with different segments, why they prefer them, and what might make them hesitate.
Use those insights to refine your creatives and decide which ideas deserve a paid test. Repeat before each campaign, and you can reduce the budget spent learning avoidable lessons.
Watch the workflow below. Start your research at atypica.ai ↓
Founders on Linkedin: "AI content sounds so generic"
Also founders on Linkedin: "Write a professional post about how I'm revolutionizing the industry"
5️⃣0️⃣ content ideas for founders
(who are building a product but have no idea what to post on X):
- the problem you're solving
- why you started building
- how you got your first user
- how you got your first 10 users
- how you got your first 100 users
- the story behind your product
- your first ugly MVP
- the feature everyone wanted
- the feature nobody uses
- the feature you regret building
- your biggest launch mistake
- your biggest growth mistake
- the marketing experiment that worked
- the marketing experiment that failed
- the channel that brought real customers
- the channel that wasted your time
- the cold DM that worked
- the cold email that got ignored
- the post that brought signups
- the post that got 12 views
- how you found product-market fit
- why users sign up
- why users never come back
- why customers leave
- why customers stay
- what your competitors do better
- what your competitors get wrong
- what users actually want
- what founders think users want
- the biggest myth about your niche
- the most underrated growth channel
- the most overrated growth channel
- your landing page before vs after
- your pricing before vs after
- your first customer interview
- your biggest customer surprise
- how you use AI to build faster
- how you use AI for marketing
- what you automated
- what you still do manually
- your biggest distribution problem
- your biggest retention problem
- building vs marketing
- traffic vs customers
- free users vs paid users
- growth hacks vs real growth
- what you'd build differently
- what you'd do with $0 marketing budget
- what you'd do to get 1,000 users
- what you'd tell yourself 1 year ago
easy
just document what you're already doing