System Design Basics #21 — Search and Ranking: Finding Things in a Pile of Data

Forward Deployed Engineer #9 — The Spec That Passes the Handoff Test: Turn Discovery Into Something

LLMOps #16 — Migrations, Incidents, and the Feedback Flywheel: Closing the Loop in LLM Ops

System Design Basics #20 — Real-Time Explained: WebSockets, Polling, SSE and Push Notifications

Forward Deployed Engineer #8 — Defining Success Before You Build: The Sentence That Ends Discovery

LLMOps #15 — Agent Ops: Operating a System That Takes Actions

System Design Basics #19 — Distributed Transactions and Sagas: Doing Two Things in Two Places

Forward Deployed Engineer #7 — Discovery III: Patterns, Not Anecdotes — Turn Interview Notes Into Fi

LLMOps #14 — LLM Guardrails: Input Checks, Output Checks, and Failing Safely

System Design Basics #18 — Event-Driven Architecture: Pub/Sub, Streams, and Eventual Everything

Forward Deployed Engineer #6 — Discovery II: How to Run the Interview

LLMOps #13 — Cost, Caching, and Model Routing: Making LLMs Affordable at Scale

System Design Basics #17 — Message Queues: Decoupling Systems With Async Processing

Forward Deployed Engineer #5 — Discovery I: Who Feels the Pain, and Where the Data Lives

LLMOps #12 — Serving and Latency: Where the Seconds Actually Go in an LLM Request

System Design Basics #16 — CDNs and Blob Storage: Serving Files and Photos at Scale

Forward Deployed Engineer #4 — The Anatomy of an Engagement: Day 0 to Day 120

LLMOps #11 — Fine-Tune, RAG, or Just a Better Prompt: Making the Decision Properly

System Design Basics #15 — The CAP Theorem: Consistency vs. Availability, Honestly

Forward Deployed Engineer #3 — The Traits That Actually Predict Success: Why Two Identical Resumes E

LLMOps #10 — Keeping Knowledge Fresh: Sync, Staleness, Deletion, and Permissions in RAG

System Design Basics #14 — Consistent Hashing: Adding a Server Without Moving Everything

Forward Deployed Engineer #2 — FDE vs. Every Other Role You've Heard Of: Where the Line Actually Is

LLMOps #9 — RAG in Production, Part 2: Retrieval Quality

System Design Basics #13 — Sharding and Partitioning: When One Machine Isn't Enough

Forward Deployed Engineer #1 — What Is a Forward Deployed Engineer? The Last Mile Is a Job

LLMOps #8 — RAG in Production, Part 1: The Pipeline Behind One Answer

LLMOps #7 — Observability and Tracing: Seeing Inside a Single Request

LLMOps #6 — LLM-as-a-Judge: How to Judge the Judge (Evaluation, Part 2)

LLMOps #5 — Evaluation, Part 1: How Do You Know Your LLM System Is Any Good?

AI Engineer Interview: Agents #1 — What an Agent Actually Is: and When Not to Build One

LLMOps #4 — Prompt Management: Treating Prompts Like Code

AI Engineer Interview: Context Engineering #4 — When Context Goes Wrong: Poisoning, Handoffs, and De

LLMOps #3 — Nondeterminism: Why the Same Question Gives You a Different Answer

AI Engineer Interview: Context Engineering #3 — Tools and MCP: The Function-Calling Surface

LLMOps #2 — The LLM App Lifecycle: The Gap Between a Demo and a Product

AI Engineer Interview: Context Engineering #2 — Memory: Short-Term, Long-Term, and the 200-Turn Conv

LLMOps #1 — What Is LLMOps? Why Shipping an LLM Feature Isn't Like Shipping Software

Agentic AI Basics #3 — The Context Window: Why AI Remembers Nothing Between Messages

AI Governance #2 — What Can Actually Go Wrong: The AI Risk Landscape

AI Governance #1 — What AI Governance Actually Is — And Why It Stopped Being Optional

System Design Basics #12 — Replication: Copies, Leaders, and Surviving a Dead Server

System Design Basics #11 — Caching: The Single Biggest Performance Lever You Have

System Design Basics #10 — Transactions and ACID: What "It Saved" Actually Guarantees

Trendy #6 — Sandboxing an AI Agent That Executes Code: Why a Container Isn't a Wall

Trendy #7 — Agent Identity and Delegated Authorization: Who Is Your Agent, Really?

Trendy #8 — Memory Poisoning: The Attack That Fires Next Week

Trendy #9 — Open-Weight Frontier Models: Can You Actually Self-Host?

Trendy #10 — Local-First AI: Route 90% of Requests to a Small Model (and Cut Spend ~70%)

AI Engineer Interview: Context Engineering #1 — Context Engineering: The Four Pillars — What the Win

System Design Basics #9 — Indexing and Data Modelling: Why One Query Is Fast and Another Times Out

AI Engineer Interview: RAG #5 — Fine-Tune, RAG, or Just Prompt Better? The Rung Everyone Skips

System Design Basics #8 — SQL vs. NoSQL: Choosing Without the Religion

AI Engineer Interview: RAG #4 — Debugging RAG: "It Gave a Wrong Answer" — The Interview Answer That

Trendy #5 — WebMCP: The Site Hands the Agent Its Tools

System Design Basics #7 — Databases 101: Where Your Data Actually Lives

AI Engineer Interview: RAG #3 — Retrieval Quality: Hybrid Search, Rerankers, and What They Cost

Agentic AI Design Patterns #5 — Parallelization: Sectioning and Voting

Trendy #4 — Spec-Driven Development: The Spec Is the Source of Truth

System Design Basics #6 — Load Balancers Explained: Spreading Traffic Without Dropping a Request