Topic
Prompt Engineering for Agentic Systems
14 posts on prompt engineering for agentic systems — part of ai agents & automation on the n4n AI blog.
System prompts vs tool descriptions: what guides agents
Practical analysis of system prompts vs tool descriptions: where to place agent policy and callable contracts, with real code examples, for portable LLM agents.
ReAct prompting explained: reasoning plus acting
ReAct prompting interleaves reasoning with tool actions in an LLM loop. This guide explains the pattern, shows a Python implementation, and debunks myths.
Prompting Claude Opus 4.5 for long-horizon agent tasks
Step-by-step guide to prompting Claude Opus 4.5 agents for long-horizon tasks: state schemas, tool contracts, loop control, and verification that holds.
How to structure multi-step instructions for AI agents
Practical guide to structuring multi-step instructions for AI agents: explicit steps, schemas, planner-executor pattern, failure handling, and testing.
How to prompt agents to ask clarifying questions
Practical steps to prompt agents clarifying questions in production systems, with code patterns for intent detection, dialogue state, and verification.
How to prompt agents for self-correction and retries
Learn how to prompt agents self-correction retries with structured feedback loops, explicit error handling, and runnable code for reliable LLM agents.
How to prevent prompt drift in long agent conversations
Practical steps to stop prompt drift in long agent conversations: enforce system prompts, compress context, and verify with eval harness.
Few-shot examples in agent prompts: when they help
Practical guide to using few-shot examples agent prompts effectively in LLM agents, with code, pitfalls, and an actionable step-by-step path.
Designing prompts for multi-agent handoffs
Practical guide to designing prompts for multi-agent handoffs: structured contracts, sender/receiver prompts, authority boundaries, and testing patterns.
Chain-of-thought vs ReAct: which prompting style wins
A practical head-to-head comparison of chain-of-thought vs ReAct prompting across cost, latency, ergonomics, and real agentic use cases.
Writing tool descriptions that AI agents actually follow
Learn how to write tool descriptions that AI agents reliably follow, with concrete schemas, code examples, and a test loop for function-calling systems.
Writing prompts that reduce hallucinated tool calls
Practical prompt engineering techniques to reduce hallucinated tool calls prompting in LLM agents, with runnable code examples and verification steps.
How to write system prompts for autonomous AI agents
Practical steps to engineer system prompts for autonomous agents, with tool contracts, error handling, and testable code for reliable agent behavior.
How to prompt agents for reliable tool use
Practical steps to prompt agents for tool use reliably, with structured schemas, explicit policies, and verifiable code examples for engineers.
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