AI Prompt Engineering Blog
Expert guides, tutorials, and insights to master the art of prompt engineering for ChatGPT, Claude, Gemini, and beyond.
Latest Articles
Page 8 of 22Prompt Evaluation: The Complete 2026 Guide to Measuring Prompt Quality
How to actually evaluate prompts in production — the evaluation pyramid, golden sets, LLM-as-judge automation, regression suites, and the observability layer that catches drift before users do.
Prompt Injection Defense: The Complete 2026 Security Guide
Prompt injection is the SQL injection of the LLM era — direct, indirect, and jailbreak variants — and the defenses in 2026 are imperfect but real, layered, and worth building.
Voice Generation Models Compared (2026): ElevenLabs, OpenAI TTS, Hume, Cartesia, PlayHT
Voice generation in 2026 is no longer a one-vendor question — ElevenLabs, OpenAI TTS, Hume, Cartesia, PlayHT, Gemini TTS, and the open-weights tier each win different shots. This tutorial maps the landscape and gives you a per-shot picking framework.
AI Image Prompting: The Complete 2026 Guide
The canonical 2026 guide to AI image prompting — a universal six-slot anatomy, the model landscape (Midjourney V7, DALL-E, Flux Pro, Stable Diffusion, Imagen, Ideogram, Firefly), per-model dialects, advanced control, and how to evaluate outputs honestly.
Multimodal AI Prompting: The Complete 2026 Input Guide
The canonical 2026 guide to multimodal INPUT prompting — sending images, PDFs, screenshots, audio, and video into text models for analysis, extraction, and reasoning. Covers the model landscape, the universal anatomy, per-modality dialects, and honest evaluation.
Prompting Reasoning Models in 2026: o3, Claude, Gemini, R1
How to prompt o3, Claude extended thinking, Gemini Deep Think, and DeepSeek R1 in 2026 — the 6-slot anatomy, per-model dialects, and when to skip them.
AI Video Prompting: The Complete 2026 Guide
The canonical 2026 guide to AI video prompting — extended anatomy for motion, camera, duration, and audio, the model landscape (Veo 3, Sora 2, Runway Gen-3, Kling, Luma, Pika), per-model dialects, multi-shot sequencing, and honest evaluation.
Enterprise AI Adoption: The Complete 2026 Operating Model Guide
The canonical 2026 guide to adopting AI as an operating model — use-case taxonomy, governance, build-vs-buy, budgets, fluency, security and compliance, vendor choice, honest measurement — not what individual prompts each function should write.
Building a Research Agent with the Agentic Prompt Stack: A Layer-by-Layer Walkthrough
Apply the 6-layer Agentic Prompt Stack to build a research agent — Goals, Tool permissions, Planning scaffold, Memory access, Output validation, and Error recovery, each shown with concrete prompt text.
Agentic RAG: A Walkthrough of Retrieval as a Tool Call
Agentic RAG treats retrieval as a tool the model calls on demand, not a fixed first step. This walkthrough contrasts it with linear RAG, traces a multi-hop research agent, and names the control plane that keeps costs bounded.
Assess Your Team's Context Engineering Maturity in 30 Minutes (A Workshop Guide)
A 30-minute self-assessment workshop applying the Context Engineering Maturity Model — diagnostic questions, group scoring, and the one concrete upgrade to commit to next.
Chain-of-Code Prompting: A Walkthrough for Mixed Reasoning Tasks
Chain-of-Code extends Program-of-Thoughts to tasks that mix real computation with qualitative reasoning — the model writes pseudocode interleaving executable code with natural-language 'execute by thinking' sections.
Chain-of-Density Prompting: A Worked Example for Dense Summaries
Walk through Chain-of-Density — iterative rewriting that packs more entities into a fixed-length summary. Shows the 5-iteration process applied to a long source document, with before/after comparison.
Chunking Strategies for RAG: Fixed, Semantic, Recursive, and Parent-Document
Chunking is the single biggest quality lever in most RAG pipelines. This tutorial walks through fixed-size, semantic, recursive, and parent-document chunking on a hypothetical legal-research assistant — with diagnoses, fixes, and failure modes.
Claude Opus 4.7 Prompting Guide: How to Get the Most From Anthropic's Top Model (2026)
A working reference for prompting Claude Opus 4.7 — extended thinking, 1M context, prompt caching, tool use, and the patterns that actually move quality and cost.
Corrective RAG (CRAG): Grading Retrieved Docs Before You Generate
Corrective RAG adds a grading step between retrieval and generation — if confidence is low, the pipeline falls back to web search or query rewriting instead of hallucinating on weak context. A working walkthrough with the three-branch router.
DSPy: An Introduction to Programming Prompts as Functions (2026)
DSPy treats prompts as typed functions — Signatures, Modules, Optimizers — instead of strings to hand-tune. This guide covers when DSPy helps, when it doesn't, and how to think about adopting it.
GraphRAG: When Knowledge Graphs Beat Chunk-Based Retrieval
GraphRAG builds a knowledge graph from the source corpus and uses its structure as retrieval context. This tutorial walks through the pipeline, where it wins over chunk-based RAG, and where it does not pay for itself.