avi retweetledi
avi
536 posts

avi retweetledi

I've spent 2.54 BILLION tokens perfecting OpenClaw.
The use cases I discovered have changed the way I live and work.
...and now I'm sharing them with the world.
Here are 21 use cases I use daily:
0:00 Intro
0:50 What is OpenClaw?
1:35 MD Files
2:14 Memory System
3:55 CRM System
7:19 Fathom Pipeline
9:18 Meeting to Action Items
10:46 Knowledge Base System
13:51 X Ingestion Pipeline
14:31 Business Advisory Council
16:13 Security Council
18:21 Social Media Tracking
19:18 Video Idea Pipeline
21:40 Daily Briefing Flow
22:23 Three Councils
22:57 Automation Schedule
24:15 Security Layers
26:09 Databases and Backups
28:00 Video/Image Gen
29:14 Self Updates
29:56 Usage & Cost Tracking
30:15 Prompt Engineering
31:15 Developer Infrastructure
32:06 Food Journal
English
avi retweetledi

We just raised $500M at an 11B valuation 🎉
To celebrate, we’re giving away 1,000 free credits so you can test our platform.
For the next 6 hours, comment “11B” below and we’ll DM you the credits (must follow) 👇
ElevenLabs@ElevenLabs
We raised $500M at an $11B valuation to transform how people interact with technology.
English
avi retweetledi

girl sitting next to me at a coffee shop had her laptop open
saw she was in a gumroad dashboard. couldn't help myself.
"you sell stuff online?"
"yeah templates"
she looked maybe 20. hoodie. airpods. nothing special.
"how's that going"
"pretty good"
"like a side hustle thing?"
"i mean it pays my rent"
"how much you making if you don't mind"
"last month was like $19K"
i actually laughed. thought she was joking.
"from templates?"
"yeah. canva templates for real estate agents."
"real estate agents?"
"they need social media content but don't know how to make it. i made 50 templates they can edit. charge $47."
"and that makes $19K?"
"i have three packs now. different styles. they buy one then come back for the others."
"how'd you even find this"
"my mom's a realtor. she asked me to make her some posts. her realtor friends saw them. they all wanted them. figured i'd just sell it."
"how many followers you got"
"like 1,900"
"you make $19K with 1,900 followers?"
"i don't sell on twitter. i post in realtor facebook groups. there's like 200 of them. i just share free tips and mention my templates."
"you're in 200 facebook groups?"
"took a weekend to join them all. now i just copy paste the same post in 10 groups a day. takes 20 minutes."
"that's the whole strategy?"
"that's the whole strategy."
she went back to her laptop.
i sat there doing math in my head.
this girl found where realtors already hang out. made exactly what they need. posts in groups they're already in.
no algorithm. no viral content. no "building an audience."
just showing up where buyers exist with something they want.
i've been trying to crack twitter for 14 months
she skipped the whole game and went straight to revenue
the buyers already exist somewhere
you don't need to attract them
you need to find them
English
avi retweetledi

The Founder Fellowship is open.
Don't waste this unprecedented moment of opportunity building something small. Find your global max.
Due Feb 1. blog.southparkcommons.com/spc-founder-fe…
English
avi retweetledi
avi retweetledi
avi retweetledi

how to actually "build something people want"
YC says it, everyone repeats it, but nobody tells you HOW.
here's the exact playbook:
1/ for B2B startup ideas → G2 and Capterra reviews
go to any popular B2B tool's review page.
filter by 1-2 star reviews.
ctrl+f for: "doesn't have", "wish it could", "missing", "can't"
example patterns i've found:
- "great tool but doesn't integrate with X" → build the integration layer
- "too complex for small teams" → build the simple version
- "costs $500/month for one feature we need" → unbundle that feature
a find from yesterday:
37 reviews complaining that a major CRM doesn't have WhatsApp integration.
that's a $10k/month opportunity right there.
2/ for B2C services → Reddit complaints
search reddit for: "[topic] + frustrating", "hate when", "wish someone would"
goldmines:
- r/mildlyinfuriating (daily pain points)
- r/entrepreneur (business problems)
- niche hobby subreddits (passionate users = paying users)
actual examples that became businesses:
- "hate calling restaurants to check wait times" → nowait (sold for $40M)
- "frustrated with splitting bills" → venmo
- "annoying to schedule meetings" → calendly
pro tip: sort by comments, not upvotes.
high comments = heated debate = real problem.
3/ for automation opportunities → Upwork job posts
people are literally paying others to do repetitive tasks.
search upwork for: "weekly", "monthly", "ongoing", "repeat"
patterns to spot:
- "need someone to format podcasts weekly" → auto-editing tool
- "looking for VA to schedule social posts" → scheduling automation
- "data entry from PDF to spreadsheet" → extraction tool
if 100+ people are paying $20/hour for it, they'll pay $50/month to automate it.
4/ for B2C mobile apps → App Store reviews
this is the holy grail for app ideas.
go to top apps in any category.
read the 1-star reviews.
look for the same complaint 20+ times.
what you'll find:
- "wish there was a feature for X" → build it
- "love this app but hate the ads" → paid version opportunity
- "perfect except no offline mode" → your differentiator
- "was great until they removed X feature" → bring it back
real example:
meditation app with 500+ reviews saying "no offline mode"
someone launched similar at $4/month → $50k MRR in 6 months
5/ the validation formula
complaints + frequency + willing to pay = validated idea
how to check:
- 30+ people with same complaint = real problem
- they're already paying for alternative = willing to pay
- existing solution has obvious flaw = opportunity
6/ turning user complaints into products
DON'T: build exactly what they ask for
DO: solve the underlying problem better
example:
complaint: "Notion is too complex"
bad solution: simpler Notion clone
good solution: focused tool for their specific use case
7/ speed is everything
when you find a pattern of complaints, move fast.
others are seeing the same data.
week 1: validate with 10 potential customers
week 2: build MVP
week 3: launch to the complainers
week 4: iterate based on feedback
remember:
every complaint is someone saying "i would pay for this to not suck"
every negative review is a product feature written by your future customer
every "i wish" is an invoice waiting to be sent
stop brainstorming by doomscrolling and start reading what people hate.
the internet is literally telling you what to build.
you just have to listen.

English
avi retweetledi
avi retweetledi

If I were a16z, yc, or sequoia, I’d be aggressively investing in startups that are building novel ways to collect and annotate real-world data.
> Billions of hours of driving data
> Factory workers interacting with appliances and heavy machinery
> Audio segmentation with deep dialectical and cultural understanding
> Wet-lab experimental data
> Continuous collection and annotation of agent traces at compute scale
When we built LLMs, most of the data already existed on the internet. We just had to scrape, clean, and scale. But as we move toward world foundation models, the bottleneck is high-quality, real-world, well-annotated data.
And annotation quality matters. There’s a massive difference between:
“Apple on a tree”
and
“Ripe apples on a tree. The wind is blowing at 2 miles per hour. The temperature is around 18°C.”
The question is simple. How much of the world can you actually capture?
Today, LLMs know that apples fall because of gravity, not because they understand causality, but because they understand language correlations extremely well. Understanding the causal structure comes next.
If I were building towards that future, I’d anchor data collection in India and other South and Southeast Asian regions. I’d deploy hardware, collect thousands of hours of human activity data, health signals, and vitals, and run annotation pipelines continuously. Day and night.
If I were a16z, I’d fund founders to do this.
I might just have the urge to do it myself.
English
avi retweetledi
avi retweetledi

4 predictions in 2026:
1. Humanoid robots will perform unsupervised, multi-day tasks in homes they’ve never seen before - driven entirely by neural networks. These tasks will span long time horizons, going straight from pixels to torques
2. Electric vertical takeoff and landing (eVTOL) aircraft are fully piloted, built conforming to FAA standards and will start demonstrating end-to-end validation missions in cities
3. Daily AI usage will shift: people will move beyond text chatbots to highly multimodal systems. Voice agents with persistent memory will become common - which will push AI closer to the synthetic human intelligence we’ve imagined in sci-fi
4. Over the past 10 years, school shootings have increased roughly 10x. In 2026, the first full scanning system capable of detecting weapons from a 20-foot standoff will be built and beta-tested in a K–12 school
English
avi retweetledi
avi retweetledi
avi retweetledi

Paying $3 for a Dollar: The Rational Irrationality of Venture Capital
docs.google.com/document/d/1S7…
English
avi retweetledi

We’re making robots more capable than ever in the physical world. 🤖
Gemini Robotics 1.5 is a levelled up agentic system that can reason better, plan ahead, use digital tools such as @Google Search, interact with humans and much more. Here’s how it works 🧵
English









