A practical framework for enterprise AI vendor selection that prioritizes functional product. 

There is a simple truth in basketball: when someone claims they can dunk, you do not want their biography. You want to see them take off, rise above the rim, and throw it down. Until the ball goes through the hoop, everything else is just pregame chatter. 

Traditional business pitches are no different. Slide after slide explaining talent, process, and commitment to excellence. Everyone insists they are fast, strategic, and powered by artificial intelligence. It all blends together. 

And just as in basketball, none of it matters until you see the dunk. 

Why Enterprise AI Partner Evaluation Has Changed 

I have spent the last year watching something shift in how enterprise buyers evaluate technology partners. The change is not subtle. AI collapsed the timeline for what is possible. Engineers use artificial intelligence to automate repetitive tasks, reveal gaps, and support rapid iteration. User experience teams model real behavior and refine interactions in a fraction of the usual time. Designers explore and adapt visual directions quickly while matching a client’s brand and needs. At the strategy level, artificial intelligence helps teams explore concepts, identify edge cases, and clarify problems before anyone designs anything or writes code. 

Teams can now build first versions far earlier than they once could. It is now possible to walk into a meeting with something real, rather than something hypothetical. 

Traditional Evaluation Arrives Too Late  

Yet enterprise evaluation still moves as if early builds take months. Teams can create quickly, but organizations are asked to decide slowly. Forrester’s 2024 Buyers’ Journey Survey reveals the scale of this shift: 92% of B2B buyers now start with at least one vendor in mind, and 41% have already selected their preferred vendor before formal evaluation even begins. Traditional vendor selection leans on slides that outline intent, case studies that point backward, and demos that highlight features. These keep judgment at arm’s length and often arrive too late to matter. 

An early milestone changes that dynamic. A deck explains. A first version proves. 

What Functional Products Reveal About AI Vendors 

A healthcare technology company came to us through a partner referral. They needed to modernize their pharmacy network’s web presence, which included hundreds of independent pharmacy websites, each with unique branding and content, all needing migration into a modern, SEO-optimized content management system. They had already sat through multiple vendor presentations that week. Each promised speed, AI capabilities, and transformation. 

At Robots & Pencils, we stopped presenting what we could do and started showing what we already built. 

Building the Functional Product in 10 Days 

Our team had a week and a half. Our engineers used AI agents to automate content scraping and migration. Our UX team modeled user flows and tested assumptions in days instead of weeks. Our designers explored visual directions that preserved each pharmacy’s brand identity while modernizing the experience. Our strategy team identified edge cases and clarified requirements before a single line of production code was written. 

We walked into the meeting with a functional product. 

The Client Demo: Testing Real Data in Real Time 

The client entered one of their pharmacy’s existing URLs into our interface. They selected brand colors. They watched our AI agents scrape content, preserve branding structure, and generate a modern, mobile-responsive website in real time. Within minutes, they were clicking through an actual functioning site built on a production-grade CMS with an administrative backend. This was not a mockup or a demo, but a working system processing their real data. 

The entire conversation shifted. They immediately started testing edge cases. What about mobile responsiveness? We showed them the mobile view that we had already built based on pre-meeting feedback. What about the administrative interface? We walked them through the CMS backend where content could be updated. They stopped asking, “Can you do this?” and started asking “What else can we build together?” and “How quickly can we expand this?” 

After the meeting, their feedback was direct: “I appreciate the way you guys approached us. Going through the demo, it wasn’t just this nebulous idea anymore. It was impressive from a build standpoint and from an administration standpoint.” 

Why Early Functional Products Prevent Partnership Failures 

When clients see a working product, even in its earliest form, they lean forward. They explore. They ask questions. They do not want to return to a deck once they have interacted with actual software. And this is precisely why the approach works. 

Most enterprise partnerships that fail do not fail because of weak engineering or design. They fail because teams hold different pictures of the same future, and those differences stay hidden until it is too late to course correct easily. A shared early version fixes that. Everyone reacts to the same thing. Misalignments surface when stakes are low. You learn how a partner listens, how they adjust, and how you work through ambiguity together. No deck presentation can show these things. 

How Early Functional Delivery Transforms Vendor Selection 

The Baseline Iteration Before Contract Signing 

At Robots & Pencils, we think of this functional product as more than a prototype. It is the baseline iteration delivered before contract signing. It shapes how the partnership forms. The client comes into the work from the start. Their data, ideas, and context shape what gets built. 

Why This Approach Stays Selective 

Because this early delivery takes real effort and investment on our behalf, we keep the process selective. We reserve early functional product development for organizations that show clear intent and strong alignment. The early artifact becomes the first shared step forward, rather than the first sales step. 

The Lasting Impact on Partnership Formation 

When you start by delivering something meaningful, you set the tone for everything that follows. The moment that first version hits the court, the moment you see the lift, the rim, and the finish, the entire relationship changes. 

In the end, the same lesson from basketball holds true. People do not remember the talk. They remember the dunk. And we would rather spend our time building something real than explaining why we could. 

If you want to explore what it looks like to begin with real work instead of a pitch, we would love to continue the conversation. Let’s talk. 

Key Takeaways 

• The evaluation gap is real: AI enables teams to build prototypes in 5-10 days, yet traditional enterprise evaluation still operates on 3-6 month timelines. This mismatch leaves buyers relying on promises instead of proof. 

• Most buyers decide before formal evaluation: 92% of B2B buyers start their journey with at least one vendor in mind, and 41% have already selected their preferred vendor before formal evaluation begins. Early proof matters more than polished presentations. 

• Partnership failures stem from misalignment, not capability: Enterprise AI implementations rarely fail due to weak engineering or design. They fail because teams hold different pictures of the same future, differences that stay hidden until it’s too late to course correct easily. 

• Functional products reveal what presentations cannot: A shared early version shows how a partner interprets requirements, handles real constraints, navigates tradeoffs, and collaborates under pressure. No deck can demonstrate these partnership dynamics. 

• Early functional delivery changes the conversation: When prospects interact with a working product built with their actual data, the conversation shifts from “Can you do this?” to “What else can we build together?” Trust forms through shared work, not sales process.

FAQs

How long does early functional delivery take to create? 

Early functional product delivery typically takes 5-10 days, depending on complexity and data availability. At Robots & Pencils, we focus on demonstrating how we interpret requirements, handle real constraints, and collaborate under actual conditions rather than achieving feature completeness. 

What makes this approach different from a proof of concept? 

Unlike traditional proofs of concept, our baseline iteration is built with the client’s actual data and reflects real-world constraints from day one. It demonstrates partnership dynamics and problem-solving approach, not just technical capability. 

Which types of organizations are best suited for this approach? 

Organizations that show clear intent, strong alignment on objectives, and readiness to engage collaboratively benefit most from early functional delivery. This approach works best when both parties are committed to testing the partnership through real work rather than presentations. 

Can this approach work for regulated industries like healthcare or financial services? 

Yes. We’ve successfully delivered early functional products for healthcare technology companies and financial services organizations. The approach adapts to industry-specific requirements while maintaining rapid delivery timelines.