Recently I made a @Polymarket bot that tracks big bets from newly registered wallets.
I originally built it for myself to help spot unusual activity, but decided to share it for free in case its useful for others too.
The bot is free to follow here: https://t.co/74UltkxFJI
Local LLM in 2026: no longer a toy, but a working tool
Two years ago, the local launch of LLM was a cry of fans and 1 token per second.
Today, Raspberry Pi 5 conducts a normal chat, MacBook Air catches up with GPT-3.5, and used RTX 3090 is almost at the level of GPT-4.
The iron caught up. The tools are ripe.
Why switch to local :
> Complete privacy
> Zero costs after buying iron
> Works without the Internet and censorship
When is the cloud better :
The most difficult tasks so far are for GPT-5.1 and Claude Opus 4.8.
Top tools :
> Ollamafor -> developers and API
> LM Studio -> the best GUI + MLX on Mac
> llama.cpp -> maximum speed
> Jan AI -> maximum privacy
put Ollama + LM Studio right away. They complement each other perfectly.
Local models already cover 80% of everyday tasks. 2026 is the year when private AI on its hardware became a convenient tool.
30 prompts = +$10k per month
No experience required
Most people use Claude as a regular chatbot
Top users give it 30 expert system prompts and get the equivalent of an entire team of specialists.
The author of this article has shared the most useful collection of 2026—30 ready-made system prompts that transform Claude into:
• a tough mentor
• a system architect
• a 10x-level copywriter
• a data analyst
• a product manager
• and 25 more experts
Each prompt has been tested in real-world scenarios. Just copy it—and Claude immediately starts thinking like a pro.
95% will keep asking, “Write me a prompt”
5% will save this collection once and work at a completely different level every day
An Easy Way to Make $10K/Month
Completely Passive
And I’m not kidding
And all of this on those ugly websites nobody talks about
You’ve used them hundreds of times:
PDF to JPG, GST calculator, JSON formatter, Word counter
The author of the article showed how, in 2026, a single master prompt + 11 AI agents build such a website completely automatically.
The 11 agents do everything:
• Find 2,000+ tool ideas
• Analyze weaknesses in Google
• Build a site architecture for 1,000+ pages
• Write SEO metadata, articles, and internal links
• Generate working code (Next.js + Go)
• Plan monetization based on RPM (financial tools yield $30–60)
No code. No team.
Evergreen traffic + AdSense.
95% will read this and keep looking for “viral” ideas
5% will launch 11 agents, build their first MVP in a week, and reach $10k+/month in passive income within 12 months
One workflow — thousands of dollars a month
Most people still manually string together prompts
But Claude can already write a fully functional system on its own
The author of the article has released the most comprehensive 2026 roadmap for Dynamic Workflows in Claude Code
Now, with just one prompt, Claude:
• writes its own JavaScript harness
• launches dozens of sub-agents in isolated contexts
• selects models on its own (Opus / Sonnet / Haiku)
• checks itself, synthesizes the result, and solves the task from start to finish
This solves the three main problems of long-running tasks:
• agentic laziness
• self-preferential bias
• goal drift
Inside: 6 working patterns + a 14-step guide used by Anthropic engineers
95% will continue to copy-paste prompts
5% will set up Dynamic Workflows and start solving complex tasks significantly faster and with higher quality
Once paid $600–$1400 + $2–3 for electricity = saving thousands of dollars a year + complete privacy.
Developers in 2026 massively buy Mac Mini M4 and Apple Stores are emptying.
Not because it's "beautiful".
And because Claude Code ate $170 from one dude in 10 days.
Uber burned $3.4 billion of the AI budget in 4 months.
And Mac Mini M4 costs $599 once + $3 per month for electricity - and you never pay Anthropic, OpenAI and Google again.
80% of tasks (code, review, RAG, documents, email) now run locally through Ollama.
The remaining 20% you leave one subscription for $20.
instead of $459 per month you pay $23.
$350k–$650k a year from neural networks in trading
And this is no joke
Most traders lose money not because they’re bad at predicting market direction.
They lose because they trade without a proper probability framework.
The author of this article has released the most in-depth guide of 2026—how hedge funds (Two Sigma, Citadel, Renaissance) use neural networks to extract an edge even before entering a trade
Key points:
• Neural networks don’t predict the future. They learn conditional expectation—the mathematical expectation of the next move based on current data.
• Direct price prediction almost always fails (non-stationarity).
• You need to work with stationary features (log returns, volatility ratios, momentum z-scores, etc.).
• The best architecture is LSTM + the right training pipeline (walk-forward validation, early stopping, purged CV).
This isn’t “just another prompt.” It’s a full-fledged framework that you can build and run
95% will read this and continue trading on intuition
5% will study this breakdown and start building a real quant edge as early as this weekend