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horloko b
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I've created a full guide on how to build automated knowledge pipelines for your workspace with Claude Cowork and Notebook LM
This covers 7 workflows that turn your emails, docs, and research into
meeting prep briefs, slide decks, weekly research & other work materials
It's yours for FREE
Like + Comment "WORKSPACE" and I'll DM you the full guide
No opt-in, no BS

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horloko b retweetledi
horloko b retweetledi
horloko b retweetledi
horloko b retweetledi

horloko b retweetledi
horloko b retweetledi

2026 онд AI сурахын тулд их сургуульд төлбөр төлөх шаардлагагүй боллоо. Дэлхийн шилдэг 10 сургалт ҮНЭГҮЙ болсон гэдгийг мэдэхүү. 💸
Яг одоо эхлүүлж болох шилдэг 10 ҮНЭГҮЙ сургалт (Линкүүдтэйгээ):
1. Google AI Essentials (Суурь ойлголт)
🔗 coursera.org/learn/google-a…
2. AI for Everyone (Техникийн бус хүмүүст)
🔗 coursera.org/learn/ai-for-e…
3. Stanford Machine Learning (Andrew Ng-ийн домогт хичээл)
🔗 coursera.org/learn/machine-…
4. Meta Generative AI Fundamentals
🔗 coursera.org/learn/generati…
5. IBM AI Engineering Foundations
🔗 coursera.org/professional-c…
6. Open-Source LLMs with Hugging Face
🔗 huggingface.co/learn
7. LangChain for LLM App Development
🔗 deeplearning.ai/short-courses/…
8. Claude code in action
🔗 anthropic.skilljar.com/claude-code-in…
9. MLOps Fundamentals
🔗 madewithml.com
10. Intro to Generative AI with Google
🔗 skills.google/paths/118/

Русский
horloko b retweetledi
horloko b retweetledi
horloko b retweetledi

PYTHON is difficult to learn, but not anymore!
Introducing "The Ultimate Python ebook "PDF
You will get:
> 74+ pages cheatsheet
> Save 100+ hours on research
And for 48 hrs, it's 100% FREE!
To get it, just:
1. Retweet
2. Reply "Send"
3. Follow @Ayzacoder (so I can DM)
Bookmark this post as well- you will receive it directly in your DM within 48 hours.

English
horloko b retweetledi

Everyone says automation is "no-code."
It's not.
It's low-code pretending to be accessible.
You still need to understand:
→ JSON structures
→ Webhook configurations
→ API authentication
→ Error handling logic
→ Node parameters
That's not "no-code." That's coding with a visual interface.
Real no-code means one thing: English in, automation out.
Synta is the first tool that actually delivers this.
Not "AI-assisted building" where you still debug for hours.
Not "simplified interface" where you still need to understand technical concepts.
Actual plain English → Working n8n workflow.
I've tested every MCP, every AI tool, every "automation assistant."
The n8n MCP? Still requires you to understand n8n.
Synta? Understands n8n for you.
The difference is brutal:
n8n MCP: "Here's some code that might work if you configure these 17 parameters correctly"
Synta: "Here's your working workflow. It's already in your instance."
If you can describe a process in English, you can automate it.
No exceptions. No learning curve. No bullshit.
This is what no-code was supposed to be from day one.
Comment "ACCESS" and I'll send you:
→ The MCP application link
→ How to check if you got access
If you didn't get MCP, the main Synta site is still incredible for true no-code automation.
The gap between "I want this automated" and "it's automated" just disappeared.

English
horloko b retweetledi

LLMs can now automate almost everything you do:
- Build a full business
- Run a marketing agency
- Create apps from scratch
…and literally hundreds more tasks.
But most people still have no idea how to use them properly.
Comment “AI” and I’ll DM you my full AI Mastery Guide
(300+ expert prompts + automation tools).

English
horloko b retweetledi

Gemini 3 has a capability most people don't even know exists.
it's not the 1M tokens.
it's not the multimodal processing.
it's something else entirely.
And it's the reason I built 3,000+ prompts specifically for Gemini 3.
Everyone talks about Gemini's specs:
→ 1 million token context
→ Native multimodal inputs
→ Deep Think mode
→ Agentic workflows
But they're missing what happens when you combine these features.
The secret is persistent systems thinking.
Gemini 3 doesn't just process large contexts.
It maintains coherent reasoning ACROSS those contexts while simultaneously:
- Analyzing images
- Reading documents
- Planning multi-step workflows
- Adapting based on previous outputs
This creates emergent capabilities that don't exist in other models.
I built 3,000+ prompts that exploit this.
Each prompt is built around this core insight:
Gemini 3's real power isn't WHAT it can process.
It's HOW it connects everything together.
The library includes:
✓ 3,000+ production-ready prompts
✓ Organized by difficulty (beginner → advanced)
✓ Real use cases for each prompt
Like, RT + reply "GEMINI" and I'll DM you the guide.
(Must be following so I can DM)
Skip this and keep wondering why your Gemini results feel the same as ChatGPT.
Or grab the library and start using the capability everyone's missing.

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