🔬 How It Actually Works

Deep dives into the tools you use every day

Every Saturday
  1. #21

    How WebSockets Work Under the Hood for Realtime AI

    Understand the WebSocket handshake, frames, heartbeats, reconnects, and backpressure—and when realtime AI needs WebSockets instead of SSE or WebRTC.
  2. #19

    How Database Indexes Actually Work — B-Trees, Hash Indexes, and When to Use Them

    Indexes make queries fast. But how? B-tree structure, index scans vs sequential scans, composite indexes, and when indexes hurt performance.
  3. #17

    How Docker Containers Work — and Why AI Workloads Stress the Boundaries

    Understand namespaces, cgroups, image layers, GPU access, and isolation so you can debug and secure containerized models and AI agents.
  4. #15

    TLS Security for AI APIs, Agents and Model Services

    Secure AI traffic with TLS: certificates, service identity, gateways, MCP connections, streaming responses and practical failure diagnosis.
  5. #14

    Rate Limiting AI APIs: Tokens, Requests, Quotas, and Cost Control

    Design AI API rate limits across requests, tokens, concurrency, tenants, and budgets. Covers token buckets, provider quotas, queues, 429 handling, and cost controls.
  6. #13

    How Prompt Caching Works — And Why It Saves You 90% on AI API Costs

    Prompt caching lets you reuse processed context across API calls. How it works, which providers support it, and how to implement it.
  7. #13

    Managing AI API Keys and Secrets From Local Development to Production

    Manage AI provider keys, agent credentials, and application secrets across local development, CI, containers, serverless platforms, and production rotation.
  8. #12

    How Transformers Actually Work — A Visual Guide for Developers

    The transformer architecture powers every modern AI model. Here's how attention, embeddings, and feed-forward layers work — explained without a PhD.
  9. #12

    How Git Merge vs Rebase Actually Works (With Visual Examples)

    Merge creates a commit. Rebase rewrites history. Here's what actually happens to your commits with each approach, when to use which, and why teams fight about it.
  10. #11

    How Embeddings Work — The Math Behind Semantic Search, Explained Simply

    Embeddings turn text into numbers that capture meaning. Here's how they work, why 'king - man + woman = queen', and how to use them in your apps.
  11. #11

    How Docker Networking Actually Works Under the Hood

    Bridge, host, overlay, none — Docker networking modes explained with diagrams and real examples. Why your containers can't talk to each other, and how to fix it.
  12. #11

    SSH for AI Servers, GPU Machines and Self-Hosted Models

    Understand and secure SSH access to AI infrastructure: host verification, keys, bastions, automation, port forwarding and least privilege.
  13. #10

    How Tokenizers Work — Why 'strawberry' Has 3 Tokens

    Tokenizers split text into pieces AI models understand. BPE, SentencePiece, tiktoken — how they work, why they matter, and why token counts surprise you.
  14. #10

    DNS Architecture for AI Services and Distributed Applications

    Understand recursive DNS, authoritative records, caching and service discovery for AI gateways, model endpoints and production infrastructure.
  15. #6

    How CORS Actually Works (And Why Your Request Gets Blocked)

    CORS errors are the most frustrating part of web development. Here's exactly what the browser does, why preflight requests exist, and how to fix it properly.