Con Claude puedes reemplazar a 3 empleados. Aquí está la guía definitiva en español.
Prompts, skills, Claude Code, monetización… lo tiene todo.
¡GRATIS solo durante 24h!
Solo:
1. Dale like
2. Comenta "4.6"
3. Sígueme para recibir el DM
Un loco con un doctorado creó una enciclopedia visual interactiva open source para entender cómo funciona la IA, en plan, locura, entren para que vean.
Website: https://t.co/Rg2HICn8RG
Repo en el primer comentario.
Top 10 YouTube channels to learn AI & ML in 2026
1. Andrej Karpathy
https://t.co/RSFn4tYrqk
2. Sebastian Raschka
https://t.co/vfqkB8Jq4O
3. sentdex
https://t.co/x69pFN1N7k
4. StatQuest with Josh Starmer
https://t.co/ASoicNjyWO
5. Jeremy Howard
https://t.co/LkT5a7C3T4
6. Krish Naik
https://t.co/bWbXwJc22I
7. CampusX
https://t.co/4n4mzA2TLo
8. 3Blue1Brown
https://t.co/izVnMMzyKD
9. MIT OpenCourseWare
https://t.co/8aWGE5Fr8v
10. Stanford Online
https://t.co/RAtD6d4q1w
The missing layer in AI Agents was interoperability, now it’s finally solved.
Meet the 7 protocols shaping the Agent Internet 🧠⚡
(Think: HTTP for AI agents)
🔹 MCP – Anthropic
Connects LLMs to tools securely (USB-C for agents)
🔹 A2A – Google
Agent ↔ Agent communication across vendors
🔹 ACP – IBM
Persistent, scalable agent conversations
🔹 SLIM – Cisco
Real-time, low-latency multi-agent messaging
🔹 Agora – University of Oxford
Turns natural language into agent protocols
🔹 ANP
Decentralized agent discovery & negotiation
🔹 AG-UI – CopilotKit
Agents ↔ User Interface bridge
Agents talking to tools.
Agents talking to agents.
Agents talking to users.
Agentic Internet = unlocked.
Next up: Agentic Commerce protocols 👀
Save 💾 | RT 🔁 | Follow for AI Agents 🚀
You've been scammed.
AI course sellers are making $50K/month repackaging these 3 free Anthropic resources:
> Anthropic Academy (Free courses from source)
https://t.co/iPOMivINjH
> Official Skills GitHub (115 active issues, 412 PRs)
https://t.co/s4tBHZaGRd
> Claude Code Subagents Catalog (Plug-and-play agents)
https://t.co/jjlwBtWD1R
Most "Claude experts" are just repackaging these repos and selling them back to you.
Repost to spread awareness, so nobody overpays.
Bookmark this before it gets buried. 🔖
@AtencionProfeco Solicite cancelar una compra y su respectivo reembolso con @WhirlpoolMX desde el 28-Nov-25 y aún no me resuelven. Ustedes me pueden ayudar?
Most people learn data engineering the hard way…
by drowning in jargon they’ve never heard before.
But here’s the truth no one tells you:
Data engineering isn’t hard because of the tools,
it’s hard because of the terminology.
Once you understand the words,
you finally understand the systems.
And once you understand the systems,
everything else becomes 10× easier.
Here’s a quick breakdown of what you’re learning:
1. ETL vs ELT — Know the difference.
ETL transforms before loading.
ELT loads first, transforms later.
Both shape how your pipeline performs.
2. Data Warehouse ≠ Data Lake.
One is for structured analytics.
The other stores raw, semi-structured everything.
Know which one fits your use case.
3. Real-time vs Batch - choose the right processing model.
Not every problem needs stream processing.
Sometimes batch is faster, cheaper, and simpler.
4. Schema matters more than you think.
Star schema, snowflake schema, table schema -
these decide performance long before the query runs.
5. Distributed systems are the backbone.
If your data isn't spread across nodes,
your system won’t scale.
6. Governance isn’t optional.
Catalogs, quality checks, lineage -
these protect your data, your users, and your business.
7. Partitioning & Sharding are lifesavers.
Large datasets die without them.
Small datasets don’t need them.
8. Fault Tolerance & Scalability keep systems alive.
Your pipeline should run even when things break.
Your platform should grow without manual effort.
If you’re in data engineering, analytics, AI, or backend - mastering these fundamentals will put you ahead of 90% of the industry.
Because tools change.
But foundations stay forever.
Which concept do you think every beginner should learn first?
HOLY SH*T...
2,000+ ready-to-use n8n workflows just got leaked.
Covers AI lead gen, content automation, sales & CRM — all plug-and-play.
This would take months (and serious money) to build from scratch.
Comment “N8N” and follow — I’ll DM the full library + setup free.
All Paid Courses (Free for First 4500 People)
𝗣𝗮𝗶𝗱 𝗖𝗼𝘂𝗿𝘀𝗲 𝗙𝗥𝗘𝗘 (PART - 1)
1. Artificial Intelligence
2. Machine Learning
3. Cloud Computing
4. Ethical Hacking
5. Data Analytics
6. AWS Certified
7. Data Science
8. BIG DATA
9. Python
10. MBA
(72 Hours only )
To get-
1. Like & Retweet to get DM
2. Reply " All "
Google Nano Banana Pro 🍌 is crazy good at static ads...
But it only generates one image at a time.
This n8n AI Agent generates 100s of ad variations in minutes, fully automated.
All inside n8n + Nano Banana Pro.
Perfect for DTC brands & agencies who need massive creative volume to test and beat ad fatigue.
Let's be honest:
Manual ad creation takes forever.
You're generating one image at a time, tweaking prompts, downloading files, trying different angles.
And by the time you have enough variations to test, you've wasted hours.
This n8n automation solves it:
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No manual prompting. No one-by-one generation. No wasted hours.
What you get:
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→ Different angles, backgrounds, compositions automatically
→ 4K resolution with perfect text adherence
→ Production-ready static ads for testing at scale
Built 100% in n8n.
Want the complete n8n template?
> Comment "NANO"
> Like this post
And I'll send it over (must be following so I can DM)
Nano Banana Pro + MakeUGC + Veo3 = your AI Ad Factory
This agent pumps out hundreds of ads daily — fully automated.
- No actors
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Just drop in a competitor’s ad → pick an avatar → let AI rebuild it in seconds.
Want the agent + full playbook?
Comment “PRO” and I'll send it for free!
(must be following)