Ahsan Sheikh

A Cyclist, proud HD Biker, Fisherman and a Cyber Security Freak @ Global Financial Services, New York

[Nikki Siapno @NikkiSiapno]

SSO vs OAuth vs OIDC vs SAML

𝗦𝗦𝗢 is a user experience, not a protocol. It lets users log in once and access multiple apps without re-authenticating; providing seamless access across tools. It relies on protocols like SAML or OIDC.

𝗢𝗔𝘂𝘁𝗵 is for authorization. It lets apps access user data or services without sharing credentials. It controls what an app can access, not identity.

𝗢𝗜𝗗𝗖 is an authentication layer on top of OAuth 2.0. It verifies user identity and provides user info via ID tokens (usually JWTs). It’s the standard for login + identity in modern apps.

𝗦𝗔𝗠𝗟 is an older, XML-based authentication protocol used for enterprise SSO. It’s still widely used in legacy and enterprise systems, though newer applications increasingly adopt OIDC. It’s powerful but more complex than OIDC.

If you remember one thing: OAuth = access, OIDC = identity, SAML = enterprise SSO, SSO = the experience.

Learn more here: https://t.co/sNCN5cdt6V

What else would you add?

——

♻️ Repost to help others learn system design.

➕ Follow me ( Nikki Siapno ) + turn on notifications.

[Vishwanath Patil @patilvishi]

Hashing ≠ Encryption ≠ Decryption ≠ Encoding
I still see these terms used interchangeably, but they solve very different problems.

✅ Hashing → One-way fingerprint (password storage, integrity checks)
✅ Encryption → Locks data with a key to keep it secret
✅ Decryption → Unlocks encrypted data using the correct key
✅ Encoding → Changes data format for compatibility, not security
⚠️ Base64 is encoding, not encryption.

If you are building APIs, authentication systems, or secure applications, knowing the difference is essential.

Saved this as a quick handwritten cheat sheet for developers. 👇

[Akanksha @Akankshaku46881]

🚀 Want to break into AI without spending a fortune?

Here are 11 FREE AI courses to level up your skills in 2026—from Prompt Engineering and RAG to LLMOps and AI Agents.

From Prompt Engineering to AI Agents, learn from the best: Google, OpenAI, AWS, Microsoft, and Harvard.

[Python Programming @PythonPr]

7 Layers of the Agentic AI Stack

[Crypto Rover @cryptorover]

WOW! 🇺🇸 Over 200 organizations unite to call on our government to pass the Clarity Act.

It's TIME! 🚀

[Coder Juba @ahmed_juna18733]

How To Design A Claude. (md) That Actually Works

[CoinDesk @CoinDesk]

NEW: @JPMorgan, @Citi and @BankofAmerica are building a shared blockchain network to give bank deposits crypto-like speed and programmability in direct response to the stablecoin 'threat', targeting a mid-2027 launch.

[Khushi AI @Mannu0100]

How to Master Claude Code 📚📘

[Elora khatun @elora_khatun]

Everyone is talking about MCP.

Almost nobody is talking about the architecture patterns that make AI agents production-ready. ⚡

If you’re building serious AI systems in 2026, these 5 MCP server patterns matter more than prompts:

Tool Servers
AI takes actions through APIs, databases, workflows, browsers, automation tools.

Resource Servers
Inject structured context into agents:
docs, files, vector DBs, internal knowledge.

Prompt Servers
Turn prompts into reusable infrastructure:
versioned, parameterized, maintainable.

Gateway Servers
Central control layer for:
routing, auth, observability, rate limits, orchestration.

Proxy / Bridge Servers
Connect old enterprise systems with modern AI agents without rebuilding everything.

The real shift:
We’re moving from:
“AI chatbot apps”
to:
“AI operating systems.”

The next generation of AI engineers won’t just write prompts.

They’ll design modular agent infrastructure. 🚀

Bookmark this before MCP becomes standard everywhere.

Follow me @elora_khatun for more AI IDEA.

[Whale Factor @WhaleFactor]

🐋 WHALE WATCH: $ONDO might be one of the most important crypto bets for the next cycle.

While everyone is chasing memes and AI Ondo is focused on bringing Wall Street on chain.

=> What is Ondo?

It tokenizes real world assets (RWAs) like:

=> US Treasuries
=> Bonds
=> Securities
=> Yield bearing financial products

The goal ? Make traditional finance accessible on blockchain.

=> Founded by Nathan Allman, a former Goldman Sachs digital assets executive.

Ondo was built with one mission:

Bridge TradFi and Crypto.

=> The numbers:

• Total Supply: 10B $ONDO
• Circulating Supply: ~4.8B
• Market Cap: ~$2B
• FDV: ~$4B

Still early compared to the size of the market its targeting.

=> The biggest catalyst?

=> Ondo Chain

An institutional grade blockchain designed specifically for tokenized assets.

Think Wall Street infrastructure built on crypto rails.

=> Smart money is already involved.

Backers include:

• Pantera Capital
• Founders Fund
• Coinbase Ventures
• Wintermute

Not your average VC lineup.

=> Partnerships matter.

Ondo has been connected with major names across finance and crypto including:

• J.P. Morgan
• Mastercard
• Ripple
• Chainlink

Institutions are paying attention.

=> The biggest risk?

Token unlocks.

Billions of tokens are still scheduled to enter circulation through 2029.

Strong fundamentals dont always beat supply pressure.

=> Why bulls are watching:

• RWA narrative is exploding
• Institutional adoption is growing
• Treasury products gaining traction
• Ondo Chain on the horizon

=> The bet is simple:

If tokenized stocks bonds and treasuries become a trillion dollar market...

$ONDO could become one of the core infrastructure layers powering it.

Are you bullish on $RWA?

$ONDO or $LINK which wins the tokenization race ?

[Ahsan Sheikh @eysheikah]

@Bakkt I have applied online for the Chief Information Security Officer position!

[CryptoDep @Crypto_Dep]

@Mastercard @NYDFS Bullish 🔥
https://t.co/AdFDleTBgs

[Chainlink @chainlink]

Mastercard and Chainlink are enabling 3.5 billion cardholders to purchase crypto directly onchain.

@Mastercard’s global payments network + Chainlink’s industry-standard oracle platform = A secure, seamless onchain experience for billions

[Mastercard @Mastercard]

Breaking news! Mastercard has been granted a BitLicense by the New York State Department of Financial Services (@NYDFS), advancing our commitment to secure and compliant digital asset innovation. 🗽🎉

Learn more: https://t.co/3aNHu3uwx6

[Vivek | Cybersecurity @VivekIntel]

Not sure what Cyber Security includes: This one image explains all 👇

[Ahsan Sheikh @eysheikah]

@Ai_Vaidehi Is there a video you recommend that illustrate these instructions?

[Vaidehi @Ai_Vaidehi]

How to learn Claude in 5 days:
(this will save you 2 hours a day)

☀️ DAY 1: Set up the basics

Goal: Get Claude to give you personalized answers.

→ Pick your mode (Chat, Code, or Cowork)
→ Turn on Memory
→ Write 3–5 lines about your role in Personal Preferences

Now Claude knows who it's talking to.

☀️ DAY 2: Build your first project

Goal: Stop repeating yourself.

→ Create a project for one recurring task
→ Write your instructions once
→ Upload your reference files

Claude now knows your context before you say a word.

☀️ DAY 3: Build your first Skill

Goal: Stop re-explaining yourself every single chat.

→ Go to Settings → Customize → Skills
→ Click "+" and describe a task you repeat often
→ Upload it — Claude loads it automatically from now on

Write it once. Claude runs it every time.

☀️ DAY 4: Connect your tools

Goal: Stop copy-pasting between apps.

→ Connect Gmail, Google Drive, or Slack via Connectors
→ Let Claude work inside those apps directly

No more switching tabs. No more manual handoffs.

☀️ DAY 5: Delegate your work

Goal: Set up an automation.

→ Schedule a recurring task (weekly Slack summary, daily brief)
→ Let Claude read, work, and deliver — on its own

That's not a tool. That's a system.

Five days. One setup.
Then it runs itself.

Do this instead of scrolling:

1. Save this post (you'll come back to it)
2. Start Day 1 today (takes 10 minutes)
3. Run the full 5 days this week

Structured. Compounding. No excuses.

[Dhanian 🗯️ @e_opore]

AI Agent Concepts to Master before Interviews ✅

1. Python Programming Fundamentals

2. APIs & HTTP Requests

3. Prompt Engineering Techniques

4. Large Language Models (LLMs) Fundamentals

5. AI Agent Architectures

6. Retrieval-Augmented Generation (RAG)

7. Vector Databases (Pinecone, FAISS, Weaviate)

8. Embeddings & Semantic Search

9. Memory Management in AI Agents

10. Function Calling & Tool Usage

11. Multi-Agent Systems

12. Autonomous Workflows & Planning

13. LangChain & Agent Frameworks

14. OpenAI API & AI SDKs

15. AI Model Fine-Tuning Basics

16. Event-Driven Agent Systems

17. Async Programming for AI Agents

18. Agent Security & Guardrails

19. Context Window Optimization

20. AI Cost Optimization & Token Management

21. AI Observability & Logging

22. Agent Evaluation & Benchmarking

23. Databases for AI Applications

24. Backend Development for AI Agents

25. Real-Time Communication (WebSockets, Streaming)

26. Deployment & Scaling of AI Agents

27. Docker & Kubernetes for AI Systems

28. CI/CD for AI Applications

29. AI System Design & Scalability

30. Building Production-Ready AI Agents

📘 Recommended Ebook for Deep AI Agent Mastery
👉 https://t.co/sv0fSvM3JV

[Alex Xu @alexxubyte]

How does SSH work?

[SimpleChain @SimpleChain_RWA]

Tokenize Real-World Value:
· Industrial Assets
· Supply Chain Finance
· Revenue Rights