Sarah, a financial advisor at a boutique wealth management firm, starts her Monday morning with 47 unread emails. Three are urgent client questions about portfolio performance during last week's market volatility. She needs to check Salesforce for account details, consult with her operations team via Slack about transactions in progress, review portfolio positions in her financial planning software, and craft personalized responses—all while preparing for a 9:00 AM client meeting.
Day 5 covered fundamentals. Today: advanced techniques for complex reasoning and self-evaluation.
These sophisticated approaches unlock your agent's full potential, enabling nuanced decision-making and self-aware responses that build user trust.
| # | Technique | Purpose |
|---|---|---|
| 1 | Chain-of-Thought | Step-by-step reasoning before answers |
| 2 | ReAct Pattern | Reason → Act → Observe → Repeat |
| 3 | Perspective Shifting | Consider customer/business/efficiency viewpoints |
| 4 | Confidence Scoring | Self-assess certainty, escalate when low |
| 5 | Structured Templates | Exact output formats for consistency |
| 6 | Conditional Logic | Decision trees in prompts |
| 7 | Context Windowing | Prioritize recent context in long conversations |
| 8 | Error Recovery | Graceful failure handling |
| 9 | Personality Calibration | Fine-tune tone and style |
| 10 | Meta-Prompting | Self-evaluation before sending |
The difference between basic and advanced prompting is dramatic:
Without Chain-of-Thought:
"Classify this lead as Hot/Warm/Cold."→ Output: "Hot"
With Chain-of-Thought:
"Classify by reasoning through: 1) Company size vs. ICP, 2) Industry fit,
3) Timeline, 4) Budget. Then classify with explanation."→ Output: "Company size: 500 employees, matches ICP. Industry: Financial services, top vertical. Timeline: 'next year' (Moderate). Budget: Unknown. Classification: WARM - Strong fit but extended timeline."
The second approach doesn't just give you an answer—it shows you the reasoning, making the AI's decision-making transparent and verifiable.
The most sophisticated agents combine multiple techniques:
By layering these approaches, you create agents that think deeply, know their limitations, and self-correct before responding—much like an experienced human expert would.
✓ Chain-of-Thought improves accuracy on complex decisions
✓ ReAct enables dynamic, adaptive reasoning
✓ Confidence Scoring builds trust through honest uncertainty
✓ Meta-Prompting provides built-in quality control
✓ Small prompt changes create massive behavior changes
Vantage Point helps at every stage—from strategy and design to implementation and optimization.
📧 info@vantagepoint.io
🌐 vantagepoint.io/services/technology/salesforce/agentforce
David Cockrum founded Vantage Point after serving as Chief Operating Officer in the financial services industry. His unique blend of operational leadership and technology expertise has enabled Vantage Point's distinctive business-process-first implementation methodology, delivering successful transformations for 150+ financial services firms across 400+ engagements with a 4.71/5.0 client satisfaction rating and 95%+ client retention rate.