Tag: #prompt-engineering
Writing on GPUs, LLMs, MLOps, Kubernetes — and mindset · 17 posts
What Is Harness Engineering — The Model Is a Fixed Input; What You Ship Is Everything Around It
Two teams use the same model, so why do their agents perform so differently? For most teams the model is a fixed input, and what actually ships is the harness around it: the tool surface, the failure return format, the l
2026-08-12 · 6 min read #llm#agent#harness-engineering#하네스엔지니어링#AI에이전트Inside vLLM (5) — Prefix Caching, and Why System Prompt Design Is Performance
A rundown of when vLLM prefix caching hits and when it misses, based on the official design document. Covers how block hashes chain to the block before them, why only full blocks get cached, how a single timestamp placed
2026-08-12 · 7 min read #vllm#prefix-caching#kv-cache#prompt-engineering#llmDid Context Engineering Replace Prompt Engineering — What's Measured and What Isn't
"Prompt engineering is dead" appears in none of the primary sources that coined the term. Karpathy listed few-shot examples and task descriptions as components of context engineering, and Anthropic called it "a natural p
2026-07-17 · 20 min read #llm#context-engineering#prompt-engineering#long-context#ai-agentHow to Become an AI Engineer in 2026 — LLMs, RAG, Agents, Evals, and a Career Roadmap
The complete 2026 guide to becoming an AI Engineer. From how the role differs from ML Engineer and Data Scientist to LLM APIs, prompt engineering, RAG design, agents, LoRA fine-tuning, vLLM serving, evals-driven developm
2026-07-02 · 26 min read #ai-engineer#career#llm#rag#ai-agentsLLM Observability & Prompt Tools 2026 — Helicone / LangSmith / Langfuse / Braintrust / Athina / Comet Opik / Portkey Deep Dive
The 2026 LLM ops map. Helicone (YC) · LangSmith (LangChain) · Langfuse (open source, Series A) · W&B Weave · Arize Phoenix · Braintrust · Athina · Comet Opik (released March 2025) · Vellum · PromptHub · Portkey AI Gatewa
2026-05-16 · 22 min read #llm-observability#prompt-engineering#helicone#langsmith#langchainDeveloper English in the AI Era: AGENTS.md, System Prompts, RFCs — Writing the English Agents Read
In 2026, the highest-leverage English a developer writes is the English agents read. AGENTS.md / CLAUDE.md context files. System prompts for production agents. RFCs and design docs that humans and agents read together. I
2026-05-14 · 27 min read #developer-english#ai-writing#agents-md#claude-md#system-promptAdvanced Prompt Engineering Complete Guide 2025: CoT, ToT, Self-Consistency, Meta-Prompting
Advanced Prompt Engineering! Chain-of-Thought(CoT), Tree-of-Thought(ToT), Self-Consistency, ReAct, Meta-prompting, Structured Output(JSON Mode), System Prompt design, Few-shot optimization, Prompt Chaining, Evaluation(au
2026-04-14 · 21 min read #prompt-engineering#chain-of-thought#tree-of-thought#few-shot#system-prompt2025 AI Job Roles Complete Map: Every AI Position from Frontier Labs to Enterprise SI
Complete anatomy of the 2025 AI job ecosystem. OpenAI/Anthropic/DeepMind hiring trends, FDE demand up 800%, AI Safety Engineer salaries up 45%, Context Engineer emerges — 15 AI roles with skills, salaries, and career roa
2026-03-23 · 43 min read #ai-careers#job-market#fde#mlops#ai-safetyAI Prompt Engineering Complete Guide: 30 Techniques Every Developer Should Know
From Zero-shot to Chain-of-Thought, Tree-of-Thought, ReAct, Few-shot, and Self-Consistency — 30 prompt engineering techniques for developers with practical examples. How to get maximum performance from Claude, GPT-4, and
2026-03-22 · 25 min read #prompt-engineering#ai#llm#chatgpt#claudeRAG vs Fine-tuning vs Prompt Engineering: The Complete Decision Framework
A practical comparison of RAG, fine-tuning, and prompt engineering from a production engineering perspective, with a concrete decision framework, real cost calculations, and honest gotchas from building these systems in
2026-03-18 · 7 min read #rag#fine-tuning#prompt-engineering#llm#ai-developmentPrompt Engineering 2025: Getting Maximum Performance from Modern LLMs
Even the best model gives poor results with a poor prompt. Six prompt engineering techniques proven in production, with working code for GPT-4o, Claude, and open-source models.
2026-03-18 · 7 min read #prompt-engineering#llm#ai-development#gpt-4o#claudeLLM Application Development Guide: From Prototype to Production
A comprehensive guide to building LLM-powered applications from prototype to production. Covers prompt engineering, RAG architecture, tool use, streaming, evaluation, cost optimization, and deployment patterns for real-w
2026-03-17 · 19 min read #llm#application-development#langchain#openai#prompt-engineeringGemini API in Production: Prompting, Guardrails, Evaluation, and Cost Control
A production guide to building on the Gemini API with practical prompting, tool and schema design, safety handling, evaluation loops, and cost-aware operating patterns.
2026-03-17 · 4 min read #gemini#generative-ai#ai#llmops#prompt-engineeringPrompt Engineering Complete Guide: From Zero-shot to Advanced Techniques
A complete guide to mastering all prompt engineering techniques. Learn Zero-shot, Few-shot, Chain-of-Thought, Tree of Thoughts, ReAct, Self-Consistency, and system prompt design through practical examples.
2026-03-17 · 32 min read #prompt-engineering#llm#chatgpt#claude#aiAdvanced LLM Prompt Engineering: Chain-of-Thought, Tree-of-Thought, ReAct, and Few-Shot Pattern Practical Guide
A comprehensive practical guide covering Zero-shot/Few-shot prompting foundations, Chain-of-Thought (CoT), Self-Consistency, Tree-of-Thought (ToT), ReAct pattern theory and implementation, structured output prompting, pr
2026-03-12 · 21 min read #llm#prompt-engineering#chain-of-thought#tree-of-thought#reactAdvanced LLM Prompt Engineering: Chain-of-Thought, ReAct, and Tree of Thoughts in Practice
A comprehensive guide to advanced LLM prompt engineering techniques. Covers the principles and implementation of Chain-of-Thought, Few-shot, ReAct, Self-Consistency, and Tree of Thoughts patterns with Python code example
2026-03-10 · 15 min read #llm#prompt-engineering#chain-of-thought#react-prompting#tree-of-thoughtsAI Prompt Engineering Complete Guide — Information Retrieval, Image/Video Generation, and Debugging (KR/EN/JA)
Prompt techniques for getting great results from AI, organized by use case: information retrieval, image/video generation, and debugging. Includes practical expressions in three languages — Korean, English, and Japanese.
2026-03-02 · 17 min read #ai#prompt-engineering#multilingual#image-generation#debugging