What AI Agents Are
LLM that uses tools autonomously.
Not just answering – taking actions.
Examples: search web, read files, send emails, execute code.
Types of Agents
Chain agents: fixed sequence.
ReAct: reason then act, iteratively.
Plan-and-execute: plan whole approach first.
Multi-agent: agents talking to each other.
Tool Definitions
Each tool: name, description, parameters.
Description quality determines LLM’s tool choice.
Vague description = wrong tool usage.
Be specific about when to use each tool.
Prompt Engineering for Agents
System prompt establishes role and constraints.
Available tools listed clearly.
Reasoning framework: think before acting.
Format for tool calls specified.
Handling Uncertainty
Agents make mistakes. Plan for it.
Retry logic with backoff.
Fallback to human when stuck.
Confidence thresholds – low confidence = escalate.
Cost Management
Agents can loop expensively.
Set max iterations per task.
Timeout per LLM call.
Budget per task.
Observability
Log every LLM call and tool use.
Trace whole agent execution.
Metrics: success rate, iterations, cost per task.
Tools: LangSmith, Langfuse, Weights & Biases.
Common Failure Modes
Getting stuck in loops.
Calling wrong tools.
Hallucinating tool results.
Losing track of goal.
Solution: constraints and validation at each step.
Production Considerations
Async execution for long tasks.
Job queue for reliability.
State persistence between runs.
Human-in-loop for critical decisions.
Testing Agents
Traditional unit tests don’t work well.
Evaluation datasets: expected outcomes for scenarios.
Regression testing when changing prompts.
Human review of edge cases.
Security
Agents doing actions = risks.
Whitelist allowed actions.
Confirm destructive actions.
Sandbox execution environments.
Rate limit tool usage.
Our Recommendation
Start simple: single tool, single action.
Add tools gradually.
Instrument heavily.
Human review before critical actions.
Expect 3-6 months to production-ready.
Based on Real Projects
This guide is based on our work with:
Further Reading
If this guide helped you, you might also want to read our comprehensive guide on AI Solutions.
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