Muchos aseguran, que desde hace varios aรฑos existe un arma capaz de provocar terremotos y cambios climaticos de manera artificial. Y cada vez que ocurre una catastrofe como el #TerremotoTurquia, afloran las teorรญas de conspiraciรณn.
ยฟMITO O REALIDAD? ๐ค
[Hilo] ๐งถ
#HAARP
1/22
Como cuando a un rescatista de EEUU le vale medio quiรฉn es Diosdado Cabello, y lo expone.
No se sabe el contexto exacto de este intercambio de palabras, pero Diosdado parece bloquear la tarea del equipo estadounidense de rescate:
"Yo te ayudo a empujarla".
El rescatista le insiste en que hay una persona allรญ quien necesita ayuda:
"ยฟNo quieres que ayudemos a nadie mรกs allรญ?".
Cada apariciรณn de este rรฉgimen ratifica el estorbo deliberado que representan en este momento y los 30 aรฑos que tienen secuestrando el poder.
Video Cortesรญa.
Outrage is growing in Venezuela after a video surfaced appearing to show the regimeโs feared Interior Minister, Diosdado Cabello, preventing members of a U.S. rescue delegation from assisting Venezuelans.
Another new exciting announcement from Google: The Agentic Resource Discovery specification.
We've been wondering how agents will know where to find resources on the web and this is it!
ARD allows tools and services to be securely shared and connected. It helps agents know:
โชWhere the right capability lives
โชWhich capability it should use
โชHow to verify if the capability is safe
It relies on Catalogs (an organization will publish a catalog that describes its available capabilities) and Registries (a search engine for the agentic web.)
ARD provides a cryptographic layer for verification and trust of agents.
Coding gets you hired.
But these skills help you grow.
The best engineers are not only the ones who write clean code. They understand systems, communicate clearly, debug deeply, manage cost, think about security, and build software that works in the real world.
Here are 15 tech skills beyond coding:
โ ๐๐ฃ๐ ๐๐ฒ๐๐ถ๐ด๐ป
Design clean APIs that are scalable, usable, maintainable, and easy to integrate.
โ ๐ง๐ฒ๐ฐ๐ต๐ป๐ถ๐ฐ๐ฎ๐น ๐ช๐ฟ๐ถ๐๐ถ๐ป๐ด
Write clear documentation that improves onboarding, collaboration, and knowledge sharing.
โ ๐๐ถ๐ ๐ ๐ฎ๐๐๐ฒ๐ฟ๐
Use advanced Git workflows to prevent mistakes and simplify team collaboration.
โ ๐ฆ๐๐๐๐ฒ๐บ ๐ง๐ต๐ถ๐ป๐ธ๐ถ๐ป๐ด
Understand dependencies, trade-offs, and how different parts of a system interact.
โ ๐ฆ๐ค๐ ๐ข๐ฝ๐๐ถ๐บ๐ถ๐๐ฎ๐๐ถ๐ผ๐ป
Write efficient queries that improve performance and reduce cost.
โ ๐๐ฒ๐ฏ๐๐ด๐ด๐ถ๐ป๐ด
Find root causes faster instead of guessing through errors.
โ ๐๐น๐ผ๐๐ฑ ๐๐ผ๐๐ ๐ ๐ฎ๐ป๐ฎ๐ด๐ฒ๐บ๐ฒ๐ป๐
Optimize cloud spend before it quietly hurts profitability.
โ ๐๐๐๐ผ๐บ๐ฎ๐๐ถ๐ผ๐ป
Remove repetitive work and reduce human error.
โ ๐ฆ๐ฒ๐ฐ๐๐ฟ๐ถ๐๐ ๐๐๐ฎ๐ฟ๐ฒ๐ป๐ฒ๐๐
Catch vulnerabilities before they reach production.
โ ๐ข๐ฏ๐๐ฒ๐ฟ๐๐ฎ๐ฏ๐ถ๐น๐ถ๐๐
Use logs, metrics, and traces to understand system health.
โ ๐๐ฎ๐๐ฎ ๐ ๐ผ๐ฑ๐ฒ๐น๐ถ๐ป๐ด
Structure data so analytics and application development become easier.
โ ๐ก๐ฒ๐๐๐ผ๐ฟ๐ธ๐ถ๐ป๐ด ๐๐๐ป๐ฑ๐ฎ๐บ๐ฒ๐ป๐๐ฎ๐น๐
Understand connectivity, latency, routing, and performance issues.
โ ๐ฆ๐๐ฎ๐ธ๐ฒ๐ต๐ผ๐น๐ฑ๐ฒ๐ฟ ๐๐ผ๐บ๐บ๐๐ป๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป
Explain technical ideas clearly so teams stay aligned.
โ ๐ฃ๐ฒ๐ฟ๐ณ๐ผ๐ฟ๐บ๐ฎ๐ป๐ฐ๐ฒ ๐ง๐๐ป๐ถ๐ป๐ด
Improve speed, scalability, responsiveness, and user experience.
โ ๐๐ ๐ง๐ผ๐ผ๐น ๐จ๐๐ถ๐น๐ถ๐๐ฎ๐๐ถ๐ผ๐ป
Use AI tools to speed up research, coding, debugging, and workflows.
Code is only one part of engineering.
The real advantage comes when you understand the systems around the code.
Save this if you are growing as a developer, engineer, or tech professional.
Most people are using AI.
Almost nobody is actually getting good at it.
They open ChatGPT, type a question, get an answer.
Call it "using AI."
But there's a massive difference between using a tool and mastering it.
I see this all the time with founders and operators I work with.
They're not bad at AI.
They're just stuck at Level 2 when the real leverage starts at Level 5.
I spent years on this.
The people compounding the fastest aren't prompting better.
They're operating at a completely different tier.
Here's the full breakdown of what each level actually looks like:
โ Level 1: AI Awareness.
You understand what AI is, how LLMs work, and where the limits are.
Most people skip this.
Big mistake.
โ Level 2: AI User.
You're prompting, summarising, researching.
Saving time.
This is where 80% of professionals sit right now.
โ Level 3: AI Power User.
You know few-shot prompting, prompt chaining, structured outputs.
You're building repeatable systems, not one-off queries.
โ Level 4: AI Creator.
You're using APIs, triggers, logic flows, and integrations to create actual AI-powered assets across text, image, video, and audio.
โ Level 5: AI Automation Builder.
You're connecting workflows with tools like Zapier, Make, and n8n.
RAG, memory systems, tool calling.
This is where time starts multiplying.
โ Level 6: AI Agent Builder.
You're building agents that plan and act.
Full stack with frontend, backend, database, and LLM layers working together.
โ Level 7: AI Engineer.
Python, deployment, evaluation.
You're shipping production AI apps, chat systems, SaaS tools.
โ Level 8: AI Architect.
Security, governance, monitoring, cost control.
You're designing enterprise-grade systems at scale.
โ Level 9: AI Researcher.
You're working on transformers, RLHF, alignment, safety, fine tuning.
Pushing what's actually possible.
Most professionals will get real business value by reaching Level 5 or 6.
You don't need to become a researcher.
But you do need to move past "I use ChatGPT sometimes."
The infographic maps every level.
Save it.
Come back to it in 90 days and ask yourself which step you've climbed.
If this kind of content is useful to you,
The rest of my posts are in the same vein.
Worth a follow if you're building seriously with AI.
Pass this along to someone on your team who's been meaning to level up their AI skills.
They'll get it immediately.
Where do you honestly think you sit right now on this scale?
Curious what you say.
Major life hack: Don't complain, ever. Nobody likes a complainer. They drain the energy of everyone around them. It's exhausting spending time around someone who constantly complains about things outside their control. If itโs within your control, go do something about it. If itโs not, youโre just wasting energy thinking about it. Complaining gives too much power to the thing. Take back that power.
๐"I published a completely blank website.
โ white page, zero visible content. But seven layers of structured data underneath: JSON-LD, llms.txt, Ed25519-signed entity claims.
Within 36 hours it became the no. 1 cited source in Perplexity. ChatGPT cited it independently - > No human ever saw content on that page."
How SQL Really Processes Your Query
When you write an SQL query, the database does not read it from top to bottom the way we do. SQL is declarative. You describe what you want, not how to get it. Behind the scenes, the engine follows its own logical sequence to produce the final result set.
Understanding this internal flow explains why some queries behave unexpectedly, why aliases fail in certain clauses, and why performance tuning starts with the right filters at the right stage. Once you know the execution flow, writing accurate, predictable, and optimized SQL becomes much easier.
This concept is especially important for anyone working with joins, aggregations, filters, or analytical queries. It bridges the gap between โquery writingโ and โquery thinkingโ.
Save this for revision and revisit it whenever a query output doesnโt look the way you expected.