In 2025, 84% of organizations experienced at least one API security incident. API calls now make up 71% of web traffic, and API breaches leak 10x more data than average security incidents. This video covers the 10 battle-tested security measures that will protect your applications from the most common and devastating attacks. What you'll learn: 1. HTTPS & TLS – Encrypt all traffic, TLS 1.3, certificate verification
2. Authentication – JWTs, token expiration, secret storage, OAuth 2.0
3. Authorization – Authentication vs authorization, BOLA attacks, RBAC
4. Rate Limiting – Token bucket algorithm, preventing brute force & DDoS
5. Input Validation – Schema validation, type checking, preventing overflow attacks
6. Injection Prevention – SQL injection, parameterized queries, NoSQL injection
7. CORS – Cross-origin resource sharing, preflight requests, proper configuration
8. CSRF Protection – Token-based defense, SameSite cookies
9. XSS Prevention – Stored/Reflected/DOM-based XSS, sanitization, CSP headers
10. Security Headers – CSP, X-Frame-Options, HSTS, X-Content-Type-Options Master all 10 measures and you'll block the vast majority of attacks before they ever reach your data. — Timestamps: 0:00 – Introduction: Why API Security Matters 1:38 – Measure 1: HTTPS & TLS Encryption 3:01 – Measure 2: Authentication (JWTs & OAuth) 4:26 – Measure 3: Authorization & BOLA Prevention 6:00 – Measure 4: Rate Limiting 7:31 – Measure 5: Input Validation 9:15 – Measure 6: SQL Injection Prevention 11:05 – Measure 7: CORS Configuration 12:40 – Measure 8: CSRF Protection 14:11 – Measure 9: XSS Prevention 15:52 – Measure 10: Security Headers 17:36 – Your Security Checklist https://www.youtube.com/watch?v=bKfbzxkw8yo

A clear, visual explanation of how Large Language Models work—covering tokenization, embeddings, attention mechanisms, and why these systems are simultaneously revolutionary and fundamentally limited. Perfect for developers, product people, or anyone tired of hand-wavy explanations. https://www.youtube.com/watch?v=uogB5P0zgM8

Your AI is confidently making things up. It cites papers that don't exist, invents statistics, and fabricates sources with perfect confidence. This is the hallucination problem—and it's why you can't ship LLMs to production without a solution. Enter RAG: Retrieval Augmented Generation. Instead of asking the model to remember everything, you give it the right information at query time. The result? An AI that's grounded in truth. In this video, you'll learn: – Why LLMs hallucinate (and why bigger models won't fix it) – How embeddings capture semantic meaning – How vector search finds relevant documents in milliseconds – The complete RAG pipeline from query to answer – Advanced techniques: reranking, hybrid search, query transformation – Why RAG is transforming enterprise AI Timestamps: 0:00 – The Hallucination Problem 0:47 – The Core Insight 1:28 – Embeddings — The Secret Sauce 2:11 – Vector Search 2:53 – The RAG Pipeline 3:34 – Advanced Techniques 4:13 – The Impact RAG doesn't make AI smarter. It makes AI honest. https://www.youtube.com/watch?v=b8YgVI4epPQ