Motion Designer | Testing AI tools daily |AI updates daily Helping creators use AI without sounding like AI Content tips, design & marketing insights.
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an 18 year old guy has sold his app for approximately $250,000,000
what Zach has done with Cal AI is a masterclass in building and scaling a business
Cal AI has been acquired by MyFitnessPal 🚨
Henry and I started Cal AI as 17-year old high school students with one mission: make calorie tracking easier with AI.
In just 18 months, we’ve helped millions of people lose millions of pounds. And we broke $50m in ARR along the way.
We are at an incredible inflection point in history where ANYBODY can build a product that can improve lives and make millions.
As founders, we get a lot of praise. The truth is that this would not have been possible without our incredible 30+ person team. We are so proud of what this team has accomplished, and are thankful to everyone that has been instrumental in Cal AI’s development and success.
Cal AI will continue as a separate app from MyFitnessPal. The combined team will share resources to continue helping people achieve their fitness goals!
Most “AI writing signs” articles list stuff like:
– Overuse of transitions
– Balanced, overly diplomatic tone
– Generic conclusions
But humans do that too in corporate environments.
Sometimes it’s not AI. It’s just LinkedIn brain.
How to never sound like an AI. But yourself:
1. Don't write any prompt. Instead, go to Wikipedia.
2. Search "Signs of AI writing."
3. Open the full article. Read nothing.
4. Do Ctrl+A. Then Ctrl+C. Copy the entire page.
5. Open a Google Doc. Paste everything in it.
6. Don't edit. Don't summarize. The full thing.
7. Rename the Google Doc as "anti-ai-writing style."
8. Click File → Download → Markdown (.md)
9. Go to Claude.ai.
10. Don't type your prompt yet.
11. Click the '+' button. Upload your .md file first.
12. Start every chat with this prompt (copy & paste):
Prompt:
"Read the uploaded file. It contains every known pattern of AI writing I want to avoid. Apply these as rules to everything you write for me. Do NOT start writing yet - ask me clarifying questions first."
Wall Street just got open-sourced.
Someone plugged Claude directly into the stock market.
Not a demo.
Not a “finance chatbot.”
A real, live financial data pipeline.
It’s called Financial Datasets MCP Server.
And once connected, Claude can:
→ Pull income statements, balance sheets, cash flow
→ Fetch real-time stock + crypto prices
→ Analyze historical data across any range
→ Read breaking company news
→ Compare valuations with actual numbers
Ask:
“Is Apple cheap right now?”
And it answers with real financial data.
Not guesses. Not hallucinations.
Hedge funds pay $50k/year for Bloomberg.
Now your AI assistant has similar raw access.
For free.
This changes who gets to analyze markets.
#AI #FinTech
Europe might win in applied AI for industry before it wins in flashy chatbots.
Manufacturing, robotics, energy optimization — that’s more aligned with its strengths than consumer AI hype cycles.
You can literally see this in Cursor usage patterns.
Early users lived in Tab Complete.
Then Agent exploded.
Now the heavy hitters mix modes — quick edits in Tab, scoped tasks to Agent, big refactors staged carefully.
It’s not about replacing one. It’s about sequencing them.
Cool chart showing the ratio of Tab complete requests to Agent requests in Cursor. With improving capability, every point in time has an optimal setup that keeps changing and evolving and the community average tracks the point. None -> Tab -> Agent -> Parallel agents -> Agent Teams (?) -> ???
If you're too conservative, you're leaving leverage on the table. If you're too aggressive, you're net creating more chaos than doing useful work.
The art of the process is spending 80% of the time getting work done in the setup you're comfortable with and that actually works, and 20% exploration of what might be the next step up even if it doesn't work yet.
NotebookLM already maps sources and extracts key points.
Layer Gemini summarization + Obsidian for structured notes and you’ve basically built a private knowledge refinery.
Raw info in. Distilled insight out.
this russian guy found a way to learn anything 10x faster🚨
saved 1,460h
NotebookLM + Gemini + Obsidian
dumps any source > AI strips duplicates > keeps only what u don't know yet
20 YouTube videos on the same topic
each one repeats the same 20% of information
this bundle removes the other 80%
what used to take a month > 15 min
yt: zproger
Look at Etsy.
Thousands of nearly identical planners.
The ones making money usually already have TikTok, Pinterest, or email traffic pushing into them.
Product is step one.
Audience is step zero.
I just unlocked a 500-person company for $200/month.
No hiring.
No meetings.
No overhead.
I installed every plugin on Claude’s Cowork platform.
Now I can:
– Pull live web data
– Generate reports
– Analyze spreadsheets
– Ship code
– Automate research
In minutes.
The craziest part?
You don’t “manage” it.
You just… do things.
We’re entering an era where leverage > headcount.
What would you build if ops wasn’t your bottleneck?
#AI #Startups
When OpenAI dropped function calling updates, whole no-code automation startups quietly panicked.
When context windows expanded, memory-layer companies felt it.
Documentation isn’t “just docs” when capability shifts are embedded inside.
Handling something like a major Bitcoin ETF while also being an aggressive trading powerhouse?
That’s influence layered on influence.
Flow visibility alone is worth a fortune in edge if you know how to model it.
And the modeling today isn’t human intuition. It’s systems.
Jane Street made $10 billion in trading revenue in a single quarter.
For scale reference- thats more than Goldman, JP Morgan, Citi, or Bank of America managed in the same period
They got banned from India’s stock market last year for manipulating a national index. They seized $570 million and called them “not a good faith actor that deserves to be trusted”
Today they’re being sued for insider trading that helped trigger the $40b Terra collapse.
And because they’re classified as a trading firm and not a hedge fund, they’re exempt from the disclosure rules that would force them to show you how they actually make their money.
This is also the firm that handles BlackRock’s bitcoin ETF, btw
Stop scraping like it’s 2012.
You can use Claude Code to pull live, structured data from any website.
Not a wall of text.
Not messy summaries.
Actual tables you can work with immediately.
Example:
Ask it to find every 2-bedroom rental in a specific neighborhood
posted in the last 48 hours
Extract: – Price
– Square footage
– Listing URL
Across multiple sites.
It returns a normalized table.
Ready for a spreadsheet.
Ready for analysis.
This runs through the Nimble skill.
It searches in real time
handles JavaScript-heavy sites
and returns structured output by default.
If you’re building agents that depend on web data…
This is a 10/10 upgrade.
#AI #BuildInPublic
Prompt engineering is dead.
Anthropic recently released the real playbook for building AI agents that actually work.
It’s a 30+ page deep dive called The Complete Guide to Building Skills for Claude and it quietly shifts the conversation from “prompt engineering” to real execution design.
Here’s the big idea:
A Skill isn’t just a prompt.
It’s a structured system.
You package instructions inside a SKILL.md file, optionally add scripts, references, and assets, and teach Claude a repeatable workflow once instead of re-explaining it every chat.
But the real unlock is something they call progressive disclosure.
Instead of dumping everything into context:
• A lightweight YAML frontmatter tells Claude when to use the skill
• Full instructions load only when relevant
• Extra files are accessed only if needed
Less context bloat. More precision.
They also introduce a powerful analogy:
MCP gives Claude the kitchen.
Skills give it the recipe.
Without skills: users connect tools and don’t know what to do next.
With skills: workflows trigger automatically, best practices are embedded, API calls become consistent.
They outline 3 major patterns:
1) Document & asset creation
2) Workflow automation
3) MCP enhancement
And they emphasize something most builders ignore: testing.
Trigger accuracy.
Tool call efficiency.
Failure rate.
Token usage.
This isn’t about clever wording.
It’s about designing an execution layer on top of LLMs.
Skills work across Claude.ai, Claude Code, and the API. Build once, deploy everywhere.
The era of “just write a better prompt” is ending.
Anthropic just handed everyone a blueprint for turning chat into infrastructure.
Download the guide here: resources.anthropic.com/hubf…
Hey everyone
I'm looking for B2B SaaS ideas something real, something people are actually willing to pay for right now and in the future.
The goal? Hit $30K MRR within 3 months. Ambitious, I know - but I'm committed.
I want something that's not just a trend. Something with real, lasting market demand - where the problem only gets bigger over time, not smaller.
And I'm going to build the whole thing in public, starting right now. Every win, every failure, every lesson , out in the open.
So if you've ever thought "I wish someone would just build this" or you've spotted a gap that nobody's filling yet
Now's your chance to say it. Drop your ideas below. 👇
$180K PM replaced, driving Uber for $45K.
Multiply that by tens of millions of knowledge workers and the GDP numbers look like a fantasy. Ghost GDP is terrifyingly plausible.
I got chills when reading this article.
I've never been more bullish on AI. And I've never been more terrified of what that means.
It's written from the POV of June 2028.
But it's long, so I summarised it for you:
• AI gets good. Companies lay off workers. Margins expand. Stocks rip. S&P hits 8,000. Everyone celebrates.
• But fired workers stop spending. Companies weaken. They buy more AI to cut costs. More layoffs. Less spending. A negative feedback loop with no natural brake.
• The top 10% of earners drive 50%+ of all consumer spending. They're the ones getting replaced. A $180K product manager ends up driving Uber for $45K. Multiply that across every major city.
• Ghost GDP emerges - the economy is "growing" on paper, but the money never reaches real people. Productivity is booming. Wages are collapsing.
• Then it hits housing. $13 trillion in mortgages, all underwritten on one assumption: you keep your job for 30 years. In 2008, the loans were bad on day one. In 2028, the loans were good. The world just changed after they were written.
• S&P crashes 38% from highs. Unemployment hits 10.2%. Markets barely react anymore.
• The punchline: you're not reading this in 2028. You're reading it in February 2026. Every domino they describe has already started falling.
The canary is still alive. Barely.
5 Businesses with the highest failure rates:
1️⃣ Restaurants – 80%
2️⃣ Gyms – 81%
3️⃣ Construction – 40%
4️⃣ Hotels – 90%
5️⃣ Retail stores/small shops – 70-75%
Numbers don’t lie.
Most people start a business thinking: “If I build it, they will come.”
Reality: execution, cash flow, and market fit kill 8/10 ventures.
If you want to survive, study the failures before chasing the hype.
#Entrepreneurship #Business
1 million users × 3% conversion × $6/month = $180k/month.
Multiply by 12, plus ads, plus enterprise — boom, easily a million-dollar ARR
People are surprised that iLovePDF is a million-dollar company and keep asking “how are they even making money?”
It actually makes perfect business sense.
They built something simple that millions of people need every single day; merge PDFs, split files, compress, convert Word to PDF, sign documents, etc. Just everyday problems solved fast.
Now imagine this:
If only 1 million people use the tool monthly and just 2–5% pay for premium at $5–$7/month…
That’s already hundreds of thousands to millions of dollars in recurring revenue.
On top of that, they earn from ads, business subscriptions, desktop apps, and enterprise tools for teams.
This is the power of boring but useful products.
