#llm
17 articles tagged llm.
Designing the AI Request Pipeline: 8 Layers Between User Input and Your LLM
A production architecture blueprint for every layer between a user's message and a safe, reliable LLM response — with Spring Boot code you can actually use.
AI Code Review at Scale: How We Use Claude to Review Every PR Before Humans See It
Six months, 4,200 pull requests, and a GitHub Actions workflow that catches real bugs before your team spends a single minute on review. The architecture, the prompt, the cost, and what we learned.
Feature Flags for AI: The Deployment Pattern That Saved Us From 3 Production Disasters
Why LLM features need flags more than anything else you've ever shipped — and the four flag patterns that let us swap models, A/B test prompts, and kill broken AI features in under 60 seconds.
Event-Driven AI: How Kafka Streams Changed the Way We Run LLMs in Production
From blocking HTTP calls to async event streams — the architecture shift that halved user-visible latency, eliminated 3AM pages, and lets us process 2M AI requests a day without hitting rate limit walls.
I Passed the Claude Certified Associate – Foundations Exam: Here's What Actually Helped
A personal account of passing the Claude Certified Associate – Foundations exam — study approach, what the exam is actually like, what caught me off guard, and why this certification is genuinely worth your time.
Agent Memory Patterns: How to Give Your LLM Application a Brain That Persists
Your LLM forgets everything the moment the request ends. Here's how production systems build short-term, long-term, and semantic memory — with Spring AI, Redis, and pgvector examples.
Why Most Enterprise AI Projects Die in Production (And the 5 Patterns That Actually Survive)
I've deployed AI systems to 10,000+ enterprise users across healthcare, logistics, and financial services. The projects that failed didn't fail because of the model. They failed because of decisions made before the first line of model code was written.
CCA Professional Complete Study Guide: Everything You Need to Pass
A comprehensive module-by-module study guide for the Claude Certified Architect – Professional exam. All five modules, every decision table, every framework, all 12 trap patterns, the 42-term glossary, and the 15-item final checklist — in one place.
Claude Certified Architect – Professional: Complete Exam Prep Guide
A detailed preparation guide for the Anthropic CCA Professional exam — all 7 domains with weights, the master pattern behind every module, domain-by-domain breakdown, trap patterns, and a 4-phase study approach.
How I Passed the Claude Certified Architect – Foundations Exam: My Preparation Guide
A first-person prep guide for the Anthropic CCA Foundations exam — the five domains, their weights, what actually appears on the exam, study resources, and the tips that made the difference.
Prompt Engineering Best Practices for Enterprise Teams
Beyond \"be clear and specific\" — the prompt engineering techniques enterprise teams actually ship: system-prompt architecture, few-shot design, retrieval grounding, structured outputs, and iterating with evals.
LLM Observability in Production: Logs, Traces, and Metrics That Matter
What to measure, log, and alert on in a production LLM app — latency, token usage, error rates, retrieval quality — and the tools and patterns to get there.
Vector Database Comparison: pgvector vs Pinecone vs Qdrant
A practical comparison of the leading vector stores for RAG — pgvector, Pinecone, and Qdrant — on scale, filtering, hybrid search, ops burden, and cost, with clear guidance on when to pick each.
LLM Token Budgeting: Sizing Prompts, Context, and Cost
A practical guide to budgeting tokens in LLM apps — how tokens map to cost and context limits, how to estimate prompt size, and the levers that keep spend predictable.
Claude vs GPT for Enterprise: An Honest Comparison
A practical, vendor-neutral comparison of Anthropic's Claude and OpenAI's GPT for enterprise use — reasoning, tool use, cost, data privacy, deployment, and how to actually decide.
Spring AI vs LangChain4j: Which Should You Choose?
A practical, balanced comparison of Spring AI and LangChain4j for building LLM apps in Java — design philosophy, provider support, RAG, tools, and when to pick each.
How to Stream LLM Responses in Spring AI (Server-Sent Events)
Stream tokens as they're generated with Spring AI's ChatClient — a practical guide to SSE with WebFlux and Spring MVC, consuming the stream on the frontend, and handling errors in production.