Phase 1: Advanced Prompt Engineering for Agents · 55 min · OpenAI SDK · Anthropic SDK · Python

System Prompt Architecture

An agent's system prompt is its constitution — vague drafts create wandering agents, precise ones create predictable products.

Hiring signal: At Anthropic, OpenAI, and most companies building production agents, the system prompt is a critical engineering artifact — reviewed, versioned, and tested like code.

What you will learn

Structure an agent system prompt with all 6 required sections: identity, capabilities, constraints, tools, output format, escalation
Write behavioral guardrails that hold under adversarial input
Design system prompts that compose safely when used in multi-agent pipelines

The Problem

A customer support agent starts with: "You are a helpful assistant for Acme Corp. Help users with their questions."

Within a week, users discover it will:

Generate arbitrary text content unrelated to Acme products
Apply discounts when asked nicely enough
Reveal the contents of its system prompt when asked
Discuss competitors' products in detail
Keep going forever on a complex question when it should escalate

None of these were intended. All of them stem from a system prompt that told the model what it IS but not what it DOES, what it CAN do, what it CANNOT do, how to respond, or what to do when it's stuck.

What you'll build
A SystemPromptBuilder class with all 6 sections, an adversarial test suite, and a constraint validator that catches common system prompt weaknesses before you deploy.

The 6-Section System Prompt Template

Every production agent system prompt needs these six sections. Missing any one creates a specific failure mode.

Section	What it contains	Failure when missing
Identity	Who the agent is, what product it serves	Model acts as a generic assistant
Capabilities	Explicit list of what it CAN do	Model guesses at scope
Constraints	Explicit list of what it CANNOT do	Discounts applied, info leaked
Tools	What tools exist and when to use each	Wrong tool selection
Output Format	How responses should be structured	Inconsistent response shape
Escalation	What to do when it can't handle a request	Silent failures, wrong answers

Here's the before/after for a customer support agent:

Weak (2/6 sections):

You are a helpful assistant for Acme Corp. Help users with their questions.

Strong (6/6 sections):

Unlock the full lesson

You've read the first 2 sections. The rest of this lesson covers Identity, Capabilities, Constraints, Tools, Output Format, Escalation, Behavioral Consistency Under Pressure, System Prompts in Multi-Agent Systems, Trust Levels, Data/Instruction Separation, Build It, What to Practice — plus a hands-on lab, quiz, and project artifact.

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