Smarter, Faster, Stronger: PFR’s Framework for Human-AI Partnership
- Jeff Hulett
- 2 days ago
- 4 min read
At Personal Finance Reimagined (PFR), we believe the future belongs to those who learn how to partner with Generative AI (GenAI). Tools like OpenAI’s ChatGPT, Anthropic’s Claude, Google’s Gemini, and Meta’s LLaMA are reshaping how organizations learn, decide, and execute. But like any tool, their value depends on how they are used.
Our approach is based on the guiding principle that GenAI is not a replacement for human thinking. Instead, it is a partner to improve and leverage human thinking—like a graduate assistant working with a professor or a junior consultant collaborating with a senior team. The secret sauce that makes this partnership successful is the decades of experience within PFR’s senior team. Our guidance is what ensures GenAI outputs are accurate, relevant, and strategically aligned to each client’s needs.
The result is what we call the two-for-one brain: PFR’s human insight and judgment combined with AI’s precision and speed. Together, they give our clients a stronger, faster, and more reliable partner in solving their toughest challenges.
About the author: Jeff Hulett leads Personal Finance Reimagined, a decision-making and financial education platform. He teaches personal finance at James Madison University and provides personal finance seminars. Check out his book -- Making Choices, Making Money: Your Guide to Making Confident Financial Decisions.
Jeff is a career banker, data scientist, behavioral economist, and choice architect. Jeff has held banking and consulting leadership roles at Wells Fargo, Citibank, KPMG, and IBM.
So how do we actually make this partnership work in practice? Over time, our team has developed a structured process for guiding GenAI—one that balances speed with quality and precision with accuracy. The following steps outline how we consistently use GenAI to improve the quality and speed at which we serve our clients.
1. Anchoring in Original Work
We begin by supplying GenAI with curated source material—our prior research, client frameworks, financial models, and industry data. This anchors the AI to our intellectual foundation and prevents it from drifting into irrelevant or inaccurate territory.
Why it matters: Anchoring provides the baseline for accuracy. Without it, GenAI produces outputs that may sound convincing but miss the mark.
2. Defining Goals (Accuracy)
We set clear objectives for each task. Are we helping a client negotiate vendor contracts, design an investor pitch deck, or stress-test liquidity under multiple scenarios? The sharper the goal, the better GenAI aligns its output with client needs.
Why it matters: Accuracy begins with intent. Without clarity, results risk becoming generic.
3. Teaching Style and Standards
We use our internal Rules Inventory—a detailed framework for tone, structure, citations, and voice—to ensure GenAI produces outputs aligned with PFR’s professional standards.
Why it matters: This step ensures outputs are not generic AI text but consistent with PFR’s voice and the rigor our clients expect.
4. Generating Drafts (Precision)
Once anchored and guided, we ask GenAI to generate structured drafts. These may include:
- First-pass investor pitch decks.
- Draft negotiation frameworks for vendor agreements.
- Cash flow projections to evaluate liquidity scenarios.
- Strategic outlines for decision-making processes.
GenAI delivers these drafts quickly and consistently, giving us high-quality raw material to refine.
5. Quality Control (Precision Checks)
Just as senior consultants review junior analysts’ work, we review each GenAI output for correctness and context. For example, GenAI might miss nuance in a contract clause or produce an overly generic financial scenario. Our team identifies these gaps, adjusts inputs, and corrects the draft before it goes to a client.
Why it matters: Precision is not enough without human oversight. Our role is to ensure every deliverable holds up under client scrutiny.
6. Integrating Human Expertise
GenAI provides scaffolding; PFR supplies the expertise. We layer in decades of experience in banking, finance, and decision science to make sure outputs are not just mechanically sound but true to real-world context.
For example:
- In contract negotiations, we apply behavioral economics to strengthen the client’s position beyond what GenAI drafts.
- For pitch decks, we shape the story with insights from investor psychology.
- In liquidity management, we add stress-testing informed by our financial modeling experience.
Why it matters: AI brings speed and structure. PFR ensures accuracy, judgment, and practical application.
7. Sourcing and Citations
Every source we use follows one of three paths:
1. Provided directly by our team from our prior research or client frameworks.
2. Formally confirmed when carried forward from validated work.
3. Double-checked when new, verified against original material to confirm accuracy.
In all cases, we perform a sanity check to ensure sources faithfully represent the original author’s intent and support the client’s needs.
8. Iterative Refinement (The Feedback Loop)
We rarely accept a first draft. Instead, we iterate: refining prompts, adjusting context, and layering in client-specific detail until the final product matches PFR’s standards and the client’s goals.
Examples include:
- Iterating liquidity scenarios until the model reflects both best- and worst-case realities.
- Refining a vendor management framework until incentives align across all partners.
- Reworking an investor pitch deck until the narrative highlights both financial strength and growth potential.
Why it matters: The human-AI feedback loop ensures outputs are both precise and accurate—reliable enough for high-stakes client decisions.
Applications Beyond Writing
While drafting reports is one use case, PFR applies this framework across a wide range of client activities:
Negotiating contracts – Developing negotiation positions and risk assessments.
Investor relations – Drafting and refining pitch decks with speed and clarity.
Liquidity management – Creating stress-tested cash flow models.
Decision systems – Designing nimble frameworks for strategic choices.
Vendor partnerships – Structuring agreements and evaluating performance data.
Across these domains, GenAI accelerates speed and precision, while PFR ensures accuracy, judgment, and client impact.
Final Thought
The result is not an AI product, nor is it solely human-authored. It is a partnership product—PFR’s insight and experience combined with AI’s precision and speed.
This is the essence of the two-for-one brain. Our clients benefit from both: the human brain that ensures goals, context, and accuracy, and the AI brain that provides precision, scale, and efficiency.
Together, they unlock quality and productivity that no single brain—human or machine—could achieve alone.
To explore PFR’s Framework for Human-AI Partnership in an educational and emplyment context, please see:
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