Dean brings deep experience as a product manager and solution consultant, offering practical insights into how proposal and pre-sales teams can work smarter.
They explore the difference between automation and true reasoning AI, how to keep proposal content libraries relevant, and how to align proposal, sales, and solution teams around shared goals. Dean also breaks down the real-world metrics proposal leaders should track, common misconceptions about AI, and why collaboration—not replacement—is key to future-proofing your proposal process.
We cover:
- How to write responses that evaluate well in 2025 - What AI breakthroughs actually move the needle (vs hype) - Whether your content library should be static or live-connected - How to manage expectations when sales leaders think AI is a “magic bullet” - Ways to discuss AI with leadership, and which KPIs they care most about - How to evolve your proposal playbook under time constraints - Working smarter with SMEs
Tune in if you want tactical steps, realistic projections, and a framework to drive AI adoption in your proposals.
Host (Chris @ Stargazy): Welcome to The Stargazy Brief. Today we’re talking with Dean Shu, CEO of Arphie, a company using AI to transform proposal and RFP workflows. Dean’s experience spans SME, product management, and software development—so he knows the process from every angle.
He shares how to get SMEs engaged in RFP responses, how to modernize your content library, and what AI can actually do to help proposal teams work faster and smarter.
Dean Shu: At Arphie, we focus on helping B2B SaaS companies—mostly large public firms or fast-growing private ones—streamline their RFP and proposal processes using AI. These teams are cross-functional, often involving product, security, and engineering. Our tools support that collaboration and ensure explainable, auditable results—especially critical for public companies managing risk.
Chris: How should proposal teams adapt to today’s evaluators and buying processes?
Dean Shu: Generic responses don’t win anymore. If you can replace one buyer’s name with another in your proposal, it’s too generic. Buyers are overwhelmed; they want clarity and reasoning, not fluff. The best proposals read like intelligent dialogues, not brochures. AI can now scale that kind of personalization—adapting logic and value arguments to what each evaluator actually cares about.
Chris: Let’s talk about AI. What’s truly transformative versus overrated?
Dean Shu: Overrated is using AI as a bolt-on text generator. That leads to “fast drafts, slow fixes.” True AI value lies in reasoning and explainability—showing why an answer is correct and how it connects to company data. When AI can reason transparently, it becomes a collaborative partner, not a cleanup project. Teams see faster turnaround—up to 60–80%—without sacrificing accuracy or compliance.
Chris: How should teams rethink their content libraries?
Dean Shu: Some teams thrive with live connectors that pull from updated sources; others prefer smaller, portable Q&A libraries for consistency. The real issue is that many libraries have become “knowledge debt.” Teams spend more time verifying than using them. We help them slim down, connect live data where possible, and keep trusted answers static where needed.
Dean Shu: Fast-moving SaaS teams prefer live connectors since their products change often. Teams with slower product cycles lean toward curated Q&A libraries. Security and compliance content stays static; product and support data should be live. Proposal managers who live in RFPs love the libraries; solution consultants who multitask prefer live connections.
Chris: What do sales leaders get wrong about AI?
Dean Shu: They assume AI can replace people. It can’t. Think of AI as a “smart intern”—great at following directions, not at strategic judgment. Or like a race car for the mind—you still need a skilled driver. The real value is human–AI collaboration, not headcount reduction.
Chris: How can proposal teams educate their leaders?
Dean Shu: Bring a balanced view. Don’t just highlight AI’s limits—show where it helps and where it doesn’t. This builds credibility and can help secure budget for the right tools. Leaders respect pragmatic, data-backed reasoning.
Dean Shu: The core metrics are shortlist rate, win rate, and proposal volume. Also track opportunities lost to capacity constraints. These show the ROI of better tooling and processes.
Chris: What should teams change in their playbooks?
Dean Shu: Audit time use. Most teams waste effort importing complex RFPs or maintaining outdated libraries. Use AI where it removes friction and focus on process improvements that save time each cycle.
Dean Shu: Even under heavy RFP load, find slower periods to make small improvements. Iteration beats overhaul. Build a business case—tie proposal improvements to revenue. And when adopting tech, pick vendors known for strong, ongoing support.
Dean Shu: Be clear about what input you need and when. Use collaboration tools that make assignments visible and easy to respond to. SMEs want to help—they’re just busy. Also, avoid double work: if engineers already maintain documentation in Confluence, connect to it instead of making them re-enter answers in a library.
Dean Shu: Anyone interested can contact us at hello@arphie.ai. We take a consultative approach—no sales reps, just experts helping you see if Arphie fits your needs. Whether or not you choose us, we want teams to benefit from AI responsibly and transparently.
Chris: You can find Arphie linked in our show notes and on Stargazy. Thanks, Dean, for an insightful discussion on how AI is reshaping proposal management.
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