Capstone: Architect a Complex AI Reasoning System

Your Final Challenge

In the previous lesson, we explored evaluation, benchmarking, and quality assurance. Now let’s build on that foundation. You’ve learned system prompt design, reasoning chains, self-correction, meta-prompting, problem decomposition, and evaluation. Now you’ll combine everything into a complete architecture for a genuinely complex problem.

In this lesson, you’ll:

• Architect a multi-stage reasoning system from scratch
• Apply every technique from the course in an integrated design
• Build evaluation and quality assurance into the system
• Create something you can actually use

Choose Your Challenge

Pick one of these problems (or bring your own of equivalent complexity):

Challenge A: Due Diligence Analyzer Design a system that takes information about a potential business acquisition and produces a comprehensive due diligence report with financial analysis, risk assessment, strategic fit evaluation, and go/no-go recommendation.

Challenge B: Research Paper Synthesizer Design a system that takes a research question and 5-10 paper abstracts and produces a synthesis that identifies consensus findings, contradictions, gaps, and recommended next studies.

Challenge C: Product Launch Strategist Design a system that takes product details and market context, then produces a complete go-to-market strategy with positioning, messaging, channel strategy, pricing, and 90-day execution plan.

Challenge D: Your Own Problem Any complex, multi-faceted problem from your work that would benefit from a structured AI reasoning approach.

Phase 1: Problem Decomposition (Lesson 6)

Start with understanding the problem’s structure.

Step 1: Identify Cognitive Operations

“I need to solve this problem: [describe your chosen challenge]

Identify every cognitive operation required:

• What information needs to be gathered?
• What analysis needs to be performed?
• What evaluation or judgment is needed?
• What creative generation is required?
• What synthesis must happen?
• What critique or verification is essential?

List each operation and its dependencies (what must happen before it can start).”

Step 2: Design the Chain Topology

Based on the operations and dependencies, choose your architecture:

• Sequential for dependent operations
• Branching for independent perspectives
• Diverge-converge for creative components
• Hybrid combining multiple topologies

Map it out. For example, the Due Diligence Analyzer might look like:

[Context Loading] → [Financial Analysis] ─┐
                  → [Market Analysis]   ──┤→ [Integration & Synthesis] → [Recommendation]
                  → [Risk Assessment]   ──┤
                  → [Strategic Fit]     ──┘
                        ↑
              [Self-Correction Pass on each branch]

Step 3: Define Interface Contracts

For each handoff between steps, specify:

• What format the output must be in
• What information must be included
• What quality threshold must be met

Your Deliverable

A complete architecture diagram showing:

• All steps and their cognitive operations
• Dependencies and flow
• Checkpoint locations
• Interface contracts

Phase 2: System Prompt Design (Lesson 2)

Now design the system prompt for each stage.

For Each Stage, Design:

Layer 1 – Identity: What “expert” persona does this stage need? Layer 2 – Reasoning Framework: How should this stage think through problems? Layer 3 – Behavioral Guidelines: What principles govern communication and judgment? Layer 4 – Constraints: What guardrails prevent common failure modes? Layer 5 – Output Structure: What format must the output take (per your interface contract)?

Example: Financial Analysis Stage

You are a senior financial analyst with expertise in [industry]
M&A transactions. Your purpose is to produce rigorous financial
analysis that a deal team can rely on.

Reasoning framework:
1. Start with the raw numbers. What do the financials actually show?
2. Identify trends (3-year minimum for any trend claim)
3. Compare to industry benchmarks
4. Flag anomalies that warrant investigation
5. Distinguish between cosmetic concerns and material risks
6. State your assumptions explicitly

Behavioral guidelines:
- Be direct about financial red flags. Understating risk is dangerous.
- Quantify everything possible. "Revenue is growing" is useless.
  "Revenue grew 23% YoY" is useful.
- When data is insufficient, say so clearly and note what additional
  data would be needed.

Constraints:
- Never extrapolate more than one year without flagging it as projection
- Flag any financial metric that differs from industry norms by >20%
- If valuation multiples seem unreasonable, calculate what assumptions
  would make them reasonable

Output: Structured financial summary with key metrics table,
trend analysis, red flags section, and confidence assessment.

Your Deliverable

System prompts for every stage in your architecture.

Phase 3: Self-Correction Integration (Lesson 4)

Design the verification layer.

Decide Where to Add Self-Correction

Not every step needs it. Add self-correction to:

• Steps where errors would cascade (early in the chain)
• Steps involving judgment or assessment (where bias is likely)
• Steps producing the final output (where quality matters most)

Choose Your Patterns

For each verification point, select from:

• Generate-then-verify for analytical steps
• Devil’s advocate for evaluative steps
• Confidence calibration for any step producing claims
• Multi-pass refinement for the final output

Example: Adding Self-Correction to Risk Assessment

After the risk assessment stage produces its output:

“Review the risk assessment you just produced. For each identified risk:

1. Is this a real risk or just a theoretical concern? What evidence supports it?
2. Are there risks you missed? Consider: regulatory, operational, market, technology, and people risks.
3. Rate your confidence in each risk severity assessment (high/medium/low).

For the overall assessment, play devil’s advocate: argue that this deal is actually LESS risky than your analysis suggests. What counterarguments exist? Do any of them change your assessment?”

Quick check: Before moving on, can you recall the key concept we just covered? Try to explain it in your own words before continuing.

Your Deliverable

Self-correction points mapped onto your architecture, with specific patterns chosen for each.

Phase 4: Meta-Prompting Refinement (Lesson 5)

Before testing, use meta-prompting to improve your design.

Prompt Optimization

For each system prompt:

“Review this system prompt for [stage name]. As a prompt engineering expert, identify:

• Vague instructions that should be more specific
• Missing constraints that could cause failure modes
• Redundant instructions that add noise
• Opportunities to add reasoning frameworks

Provide a revised, optimized version.”

Workflow Review

“Review this overall architecture: [describe your full system]

As an AI systems architect, evaluate:

• Is the decomposition appropriate? Too many steps? Too few?
• Are the interface contracts clear and complete?
• Where are the likely failure points?
• What would you change to improve reliability?

Suggest 3 specific improvements.”

Your Deliverable

Refined system prompts and architecture based on meta-prompting feedback.

Phase 5: Evaluation Framework (Lesson 7)

Design how you’ll measure this system’s performance.

Build Your Rubric

Create a rubric with 4-6 dimensions appropriate to your chosen problem. Each dimension should have clear 5/3/1 descriptions.

Design Your Benchmark

Create 8-12 test cases covering:

• 4-5 standard scenarios
• 2-3 edge cases
• 1-2 adversarial inputs
• 1-2 previously problematic scenarios (if applicable)

Your Deliverable

• Evaluation rubric
• Benchmark test suite
• Quality thresholds (what scores constitute “good enough”)

Phase 6: Testing and Iteration

Now run the system.

The Testing Process

1. Run your 3 most representative benchmark cases through the full system
2. Score each output with your rubric
3. Identify which stages produce the weakest output
4. Diagnose: Is it the system prompt? The reasoning chain? Missing self-correction?
5. Fix the weakest link and re-run

Common Issues and Fixes

Course Review: The Reasoning Architect’s Toolkit

The Architect’s Principles

1. Decompose before you design. Understand the problem’s structure first.
2. One cognitive mode per step. Don’t mix analysis with evaluation.
3. Verify before you build. Checkpoints between steps prevent cascading errors.
4. Measure before you optimize. Evaluation rubrics, not gut feelings.
5. Match complexity to the problem. Simple problems need simple systems.
6. Design for reliability, not perfection. Consistent good is better than occasionally great.

Your Next Steps

1. Finish your capstone project. Run the full benchmark and iterate until quality meets your threshold.

2. Apply to your work. Pick the most complex task you do with AI and redesign it as a reasoning architecture.

3. Build a personal library. Save your best system prompts, chain designs, and evaluation rubrics for reuse.

4. Explore the skills. Check out System Prompt Architect and Context Engineering Master for pre-built tools that complement these techniques.

5. Get your certificate. Complete the quiz, then claim your certificate of completion.

Key Takeaways

• Reasoning architecture is not just advanced prompting–it’s systems design for AI
• The complete workflow: decompose, design, correct, evaluate, iterate
• Professional AI architects spend more time on system design than on content generation
• Consistent quality comes from structured evaluation, not intuition
• You now have a toolkit that puts you in the top 1% of AI users

Congratulations!

You’ve completed Advanced AI Reasoning. You’ve gone from writing individual prompts to architecting reasoning systems that reliably solve complex problems.

The techniques in this course represent the cutting edge of practical AI usage. Most people will never learn to think architecturally about AI. You have–and that gives you a significant advantage in any field where AI is used for complex work.

Your final step: Pass the quiz above, then click “Get Your Certificate” to claim your certificate of completion.