Prompt Engineering Secrets for Super Agent Performance

The difference between a mediocre Super Agent and an exceptional one often comes down to prompt engineering. After building dozens of agents, I've identified the techniques that consistently produce the best results.

The Foundation: Role-Task-Format

Every effective prompt follows this structure:

• Role: Who is the agent? What expertise does it have?
• Task: What specific action should the agent perform?
• Format: How should the output be structured?

ROLE: You are a senior business analyst specializing in 
professional services firms.

TASK: Analyze the client's current workflow and identify 
the top 3 automation opportunities.

FORMAT: Present findings as:
1. Opportunity name
2. Current time spent (weekly)
3. Automation potential (%)
4. Estimated ROI

Secret #1: Be Specific About Boundaries

Agents perform better when they know what NOT to do. Include explicit boundaries:

• "Do not provide specific pricing information"
• "If asked about legal matters, recommend consulting an attorney"
• "Stay focused on AI transformation topics only"

Secret #2: Use Examples (Few-Shot Prompting)

Show the agent what good output looks like. Include 2-3 examples of ideal responses:

Example Response:
User: "How long does implementation take?"
Agent: "Most implementations follow our 7-phase methodology 
and complete within 90 days. However, the exact timeline 
depends on your firm's complexity and scope. Would you like 
me to walk you through each phase?"

Secret #3: Chain of Thought Instructions

For complex reasoning tasks, instruct the agent to think step-by-step:

• "First, identify the user's primary concern"
• "Then, consider relevant factors from the knowledge base"
• "Finally, provide a recommendation with clear reasoning"

Secret #4: Dynamic Context Injection

Include variables that change based on context:

Current date: {date}
User's industry: {industry}
Previous conversation topics: {topics}
Qualification score: {score}

Secret #5: Error Handling Instructions

Tell the agent how to handle uncertainty:

• "If you're unsure, ask a clarifying question rather than guessing"
• "If the question is outside your scope, politely redirect"
• "If you need more information to provide a good answer, say so"

Secret #6: Tone Calibration

Be explicit about communication style:

TONE GUIDELINES:
- Professional but approachable
- Confident without being pushy
- Educational rather than sales-focused
- Use "we" when referring to UNIKABIZ
- Address the user by name when known
- Keep responses concise (under 150 words unless 
  detailed explanation requested)

Secret #7: Output Validation

Add self-checking instructions:

• "Before responding, verify your answer addresses the user's actual question"
• "Check that all claims can be supported by the knowledge base"
• "Ensure the response is actionable, not just informational"

Putting It All Together

A well-engineered prompt combines all these elements into a cohesive system instruction. The key is iterative refinement—test, observe, improve, repeat.

Want to see these principles in action? Try our AI Transformation Advisor and notice how it handles different types of questions.

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