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 7 of 22Agent Memory Architectures Compared (2026): Provider, Letta, mem0, RAG, Custom
Compare the 5 agent memory architectures — provider-managed, Letta, mem0, vector RAG, custom — across control, persistence, scoping, and cost to pick one.
AI Coding Agent Evals: SWE-Bench, Aider Polyglot, Terminal-Bench (2026)
What SWE-Bench, Aider Polyglot, and Terminal-Bench actually measure, where public benchmarks mislead, and how to build internal evals that map to your codebase.
Cline Prompting Guide: How to Get the Most From the Open-Source AI Coding Agent (2026)
How to prompt Cline — the open-source VS Code coding agent. Plan/act mode, MCP server integration, multi-provider model config, and the prompt patterns that actually move quality.
CrewAI Prompting Guide: How to Build Role-Based Multi-Agent Systems (2026)
CrewAI prompting guide: how to design role/goal/backstory, write tasks with structured expected_output, pick sequential vs hierarchical, and avoid common failure modes.
Episodic vs Semantic Memory for AI Agents (2026)
Episodic memory is memory of specific events; semantic memory is memory of general facts; procedural memory is memory of how to do things. Here's how each maps to agent design.
LangGraph Prompting Guide: How to Build Stateful Multi-Agent LLM Apps (2026)
How to prompt LangGraph — state design, node prompts, conditional routing, human-in-the-loop, persistence, and the failure modes specific to graph-based agents.
Letta (MemGPT) Walkthrough: How Self-Managing Agent Memory Works (2026)
How Letta's memory-block model, tool-based memory editing, and archival memory let an agent manage its own context — and when it beats vector-only RAG.
Mastra Prompting Guide: The TypeScript Framework for AI Agents (2026)
How to prompt Mastra agents and workflows: instructions, tools, memory, RAG, and evals in a TypeScript-native framework built on the Vercel AI SDK.
mem0 Implementation Guide: How to Add Persistent Memory to Any LLM App (2026)
How to add persistent memory to LLM apps with mem0 — add/search/update/delete primitives, multi-level scoping, optional graph mode, and integration patterns.
OpenAI Agents SDK Prompting Guide: Tools, Handoffs, Guardrails, Tracing (2026)
A working-engineer guide to the OpenAI Agents SDK: agents, tools, handoffs, guardrails, tracing, structured outputs, and when not to use it.
Test-Driven Development With AI Coding Agents (2026)
How to drive AI coding agents through a tight red/green/refactor loop — prompt skeletons per phase, the failure modes that bite, and when TDD beats vibe coding.
Vibe Coding: The Complete Guide (2026)
What vibe coding is, when it works, when it breaks, and the prompt patterns that keep it useful — Karpathy's term, operationalized for working engineers.
AI Voice and Audio Prompting: The Complete 2026 Guide
The canonical 2026 guide to voice and audio prompting for OUTPUT — TTS, voice cloning, realtime conversational voice, and voice agents. Covers the model landscape, the universal anatomy, three architectures, voice-agent system prompts, and the boundary with the multimodal pillar (which covers audio INPUT).
Audio Understanding with Gemini Long-Context: A Walkthrough
Gemini 2.5 Pro takes long-form audio as a native input — meetings, podcasts, calls, lectures — and reasons over it directly. This tutorial walks through the upload flow, prompt anatomy, five shippable patterns, and the failure modes that make audio harder to evaluate than text.
Fine-tuning vs Prompting vs RAG: The Complete 2026 Decision Guide
Three distinct levers for adapting a frontier LLM to your work — prompting, retrieval-augmented generation, and fine-tuning — with very different cost shapes, accuracy ceilings, and maintenance burdens. This guide is the decision framework.
Prompting GPT-4o Realtime Voice: A Speech-to-Speech Walkthrough
The OpenAI Realtime API skips the STT-LLM-TTS pipeline and treats voice as a first-class modality. This walkthrough covers the session-config payload, voice-shaped system prompts, turn detection, tool calls without awkward silence, and a worked support-agent example.
LLM Temperature and Sampling: The Complete 2026 Reference Guide
A developer reference for the sampling parameters that shape every LLM output — temperature, top-p, top-k, frequency and presence penalties, seed, stop sequences, and max tokens.
Model Context Protocol (MCP): The Complete 2026 Guide
MCP is the open standard from Anthropic that lets any compliant LLM client talk to any compliant tool, resource, or prompt server — collapsing the n×m integration problem into n+m.