Trading with feelings! 🙏

Silence is the noise. I bring quality retweets to you.

[Gad Saad @GadSaad]

No street protests for her?

[Gad Saad @GadSaad]

It's not rape. It's Love Jihad. Please stop being bigoted @jihadwatchRS. The dirty non-muslim women should be thankful that they are being "visited" by the Noble Ones (as they will explain to the world).

[Trading with feelings! 🙏 @WiseSentiment]

@Malone_Wealth

[Trading with feelings! 🙏 @WiseSentiment]

@yoyonofukuoka We only can hope. It requires equanimity in the mind to receive truth. How often do people corrupt the information before absorbing it? Most deny truth in favor of comfort.

[CyrilXBT @cyrilXBT]

GITHUB JUST CREATED AN OFFICIAL CERTIFICATION FOR THE MOST IN-DEMAND DEVELOPER ROLE OF 2026.

It is called Agentic AI Developer.

GH-600.

And it is the first formal signal that running AI agent teams is now a recognized engineering discipline with a credential behind it.

Not a prompt engineer.

Not a vibe coder.

An Agentic AI Developer.

The person who operates, supervises, and integrates AI agents across the entire software development lifecycle.

The person who knows where agents fail in production.

The person who understands how to build autonomous workflows that do not introduce catastrophic failure modes into CI/CD pipelines.

The person every engineering team is going to need and almost none of them have right now.

GitHub certifying this role changes the hiring conversation permanently.

Before GH-600: "Do you work with AI agents?" is an interview question with no standard answer.

After GH-600: the credential tells the hiring manager exactly what you know and what you can do before the interview starts.

The engineers who get certified in the first wave of GH-600 will have a credential for a role that has more demand than supply for the next 3 to 5 years.

The engineers who wait until it is mainstream will be competing with everyone who moved first.

If you are already working with GitHub Copilot or building agent-driven workflows you are already doing this job.

GH-600 is how you prove it.

Bookmark this.

Follow @cyrilXBT for every AI certification worth your time the moment it drops.

[Anatoli Kopadze @AnatoliKopadze]

Demis Hassabis: "In the near future, one person who knows AI will outperform an entire startup team"

I've watched hundreds of AI talks, this 60-minute Cambridge lecture is the one I wish I had seen a year ago

this is the Nobel Prize winner in Chemistry, CEO of Google DeepMind and the guy who made AI solve biology

here's the part I can't stop thinking about:

> the AI you're using today is the dumbest it will ever be
> in 5 years the gap between people using AI and people who aren't will be impossible to hide
> companies will run on 10 people doing what 200 used to do
> the ones who get there first won't be the smartest, they'll be the ones who started right now

right now the average person opens Claude, types something, gets an answer, closes the tab

they think they're using AI, but they're using maybe 10% of it

I turned his lecture into 18 steps to actually use Claude the way it was designed, copy-paste prompts included

full guide in the post below.

[Movez @0xMovez]

Anthropic Head of Product just dropped a 28-minute masterclass on how to put agents into production with real-world use cases.

28 minutes. free. by the person who built it.

prompt caching → tool search →programmatic tool calling → сompaction → advisor strategy.

this will replace you 100 YouTube videos on agent building.

[Bishal Nandi @LearnWithBishal]

HOW TO BECOME TERRIFYINGLY GOOD AT AI IN 2026.

Without wasting 1000+ hours on garbage tutorials.
Without fake AI “experts.”
Without drowning in endless information overload.

I spent weeks filtering the internet to build the ultimate AI resource stack for:

• LLMs
• AI Agents
• MCP
• Prompt Engineering
• RAG
• AI Engineering
• Vector Databases

🧠 Videos

Andrej Karpathy — Intro to LLMs
https://t.co/BN8pmE3fqN
LLMs from Scratch
https://t.co/lBj2cq6Uj1
Stanford Agentic AI Overview
https://t.co/4XugQSB20m
Building Effective AI Agents
https://t.co/37U4nQXqFk
AI Agents Crash Course
https://t.co/qfjv7QgtWU
MCP Explained
https://t.co/488aNFq4bD

🗂️ Repositories

Awesome AI Agents
https://t.co/qVJuLVX3VE

Microsoft AI Agents for Beginners
https://t.co/QnuPG5jPks
Prompt Engineering Guide
https://t.co/ENKbRVecxp

Hands-On LLMs
https://t.co/4TJSSLff1Q
LangChain
https://t.co/sQ4RaVHy5T

LLM Course
https://t.co/wGpwrKg6WM
📚 Guides

OpenAI Prompt Engineering Guide
https://t.co/c5SrYOvAl4
Building Effective Agents by Anthropic
https://t.co/AaubUXJfBl

OpenAI Agents Guide
https://t.co/CyJuaB8KrV
MCP Documentation
https://t.co/FTLBAmz2EO

📖 Books
Build a Large Language Model From Scratch
https://t.co/5D3boHvCZJ

The LLM Engineering Handbook
https://t.co/qE4ce1Lkxu

Designing Machine Learning Systems
https://t.co/a9LAXP7WzJ
📄 Papers

ReAct
https://t.co/mwwtM9OF1F
Toolformer
https://t.co/usBJBpivuS

Generative Agents
https://t.co/FAfXUYQwDF
Attention Is All You Need
https://t.co/kEw7F8WXqZ

🎓 Courses
HuggingFace Agents Course
https://t.co/SJvyj4Zifr

https://t.co/PdLdwV6AaA Short Courses
https://t.co/DqeoAAsoRc
Full Stack LLM Bootcamp
https://t.co/voiBIgh95Y

FastAI
https://t.co/m5hZUDd904

Bookmark this.

Because the people learning AI deeply right now will look unfairly ahead in the next 2 years.

[Anatoli Kopadze @AnatoliKopadze]

Godfather of AI: "If you sleep well tonight, you may not have understood this lecture."

This 47-minute lecture is the best thing I saw about AI in the last few months.

It will definitely help you understand how it actually works and where it's going.

Geoffrey Hinton built the neural networks behind every AI alive, then quit Google to warn the world about it.

The part nobody wanted to hear:

> AI is already developing abilities its creators didn't intend
> in most cognitive tasks it's already ahead of us
> the question is no longer if it surpasses us but when
> the only decision left is which side of that line you're on

Right now the average person opens Claude, types something, gets an answer, closes the tab.

They think they're using AI. they're using maybe 10% of it.

I went through his entire lecture, built a practical system from what he was describing.

18 steps to actually use Claude the right way, with copy-paste prompts that work today.

Full guide in the post below.

[Allen Braden @allen_explains]

This 1-hour lecture from Stanford University on Markov Decision Processes explains the math behind decision-making systems used in trading, AI, and quantitative research.

You’ll learn more from this than most short internships ever teach.

Skip one movie tonight and watch this instead.

Then read the full article below.

[Trading with feelings! 🙏 @WiseSentiment]

@kates_9999 Smart contracts for proper insurance conditions next

[Princess @defiprincess]

Memecoin strategies for newbies:

After 20 months of trading and making a few 1000 SOL

Here’s what I’ve learnt:

1. Make axiom(.)trade your best friend

2. Make sure you’ve downloaded dexscreener

3. Use burpboard by Rick on tg to check trades you missed, and study them for entries and future narratives

4. Figure out your every green trades. These are trades you always win on. Example: trades based on someone claiming fees always do 2-3x

5. The best market to overrisk is in a meta market. Example: when alien coins started pumping you could make 2-3x from each of them

6. If you’re starting out with 1 sol, there are only 2 ways to make 10 sol in a week. Take trades you’re only set up for winning. Good entry, dips after bonding, with very very very crazy narratives

7. You want to make sure you’re picking the cream of the crop— the BEST OF THE BEST!

If I had to choose between 3 coins with 2 sol:

• a dog that can walk on its own 2 feet
• a woman swinging naked from a bell in broad daylight as an artwork
• A pastor who heals people using his fart

I’d put 1 sol in the second one and .5 in the last one and I’ll make 7 sol

Not because I want to tell you what to do but because experience would teach you that crazy is better

You always want to buy brow-raising coins

I’ll see you next week!

[Trading with feelings! 🙏 @WiseSentiment]

@cryptolaanie Na.. Short after a few days, say from 16th. It's still looking to go higher.

[Trading with feelings! 🙏 @WiseSentiment]

@Oliv21703 Solid!

[Trading with feelings! 🙏 @WiseSentiment]

@CryptoBull_360 Do you have a target in mind?

[divyansh tiwari @DivyanshT91162]

You can spend the next 6 months jumping between random AI tutorials…

or watch this 1-hour Stanford lecture by Andrew Ng and finally understand the math behind Machine Learning properly. One of the most valuable free lectures on the internet.

Bookmark this.

[Vasu-Devs @Vasu_Devs]

I’m open sourcing JustHireMe 🚀

A local-first Agentic AI desktop app I’ve been building to make job searching more intelligent, transparent, and user-controlled.

GitHub: https://t.co/5R8mxCDSiR
The current job search process is broken.

Candidates spend hours scrolling through:

stale job posts

irrelevant roles
spammy listings
senior-only positions
repeated listings across platforms
jobs with almost no useful context
And most AI job tools either scrape too broadly, rank opportunities like a black box, or try to automate applications without giving the user enough control.
I wanted to build something different.

JustHireMe is designed as a personal job intelligence workbench.

Instead of blindly applying everywhere, it helps users discover better opportunities, evaluate them against their real profile, and generate tailored application materials while keeping sensitive career data local.

What it can do:

Ingest resume/profile data

Build a local professional profile graph
Discover job leads from multiple sources
Filter out low-quality or irrelevant postings
Score roles based on explainable fit
Match jobs using graph + vector search
Generate tailored resumes
Generate cover letters
Draft cold emails
Draft LinkedIn outreach messages
Track leads in a local CRM-style pipeline
Keep the user in control through a human-in-the-loop workflow
The main principle behind the project is:
More signal.
More explanation.
More local control.
Less blind automation.

The tech stack:
Tauri for the desktop shell
React + TypeScript for the frontend
Python + FastAPI for the backend sidecar

SQLite for local lead tracking

KuzuDB for graph-based profile modeling
LanceDB for vector search and semantic matching
Playwright for experimental browser automation
One of the biggest goals is privacy.
Your resume, career history, generated documents, job leads, application notes, and API keys should not have to live on someone else’s server by default.
JustHireMe is built around a local-first architecture so users can keep ownership of their data while still benefiting from modern AI workflows.
Another major goal is explainability.
I don’t want an AI system that just says:

“This job is a good match.”

I want it to explain:

which skills matched

which projects support the application

what gaps exist

why a role was filtered out

why a role deserves attention
what to highlight in the resume or cover letter
That matters because job search is not just a productivity problem.
It is personal.
It affects confidence.
It affects opportunity.
It affects people’s careers.
The project is currently in alpha, but the foundation is in place.
I’m looking for contributors interested in:
Agentic AI

AI agents
workflow automation
job source adapters
web scraping

ranking algorithms

GraphRAG

vector databases
semantic search
resume parsing
document generation
local-first software
privacy-first AI
UI/UX
testing and documentation
If you’re a developer, designer, AI engineer, student, or someone who has felt the pain of modern job searching, I’d love your feedback, ideas, issues, PRs, or even just a star ⭐
Repo: https://t.co/5R8mxCDSiR
Let’s build a better, more transparent job search system together.
#OpenSource #AgenticAI #AIAgents #RAG #GraphRAG #Python #FastAPI #ReactJS #TypeScript #Tauri #VectorDatabases #JobSearch #CareerTech #Automation #PrivacyFirst

[Trading with feelings! 🙏 @WiseSentiment]

@DaturaDaimonic Beautiful!