AI Engineer World's Fair 2026
Your AI Product Will Fail Unless You Can Explain It
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Your AI Product Will Fail Unless You Can Explain It
A buyer needs to recognize the problem before they can value the architecture. Veronica Hylak shows how to turn an AI product pitch into a concrete story about the customer's work.
From a talk by Veronica Hylak
The pitch that loses the buyer
An elevator pitch opens with an agentic AI orchestration platform for enterprise knowledge retrieval. The buyer hears crickets. The explanation gets simpler—or tries to: agents talking to other agents inside a multi-agent workflow. Each clarification supplies more architecture without giving the buyer something recognizable to care about.
The pitch retreats to saving time, automating unwanted tasks, and bringing autonomous intelligence to workflows. The elevator door closes. Even the benefits are too general to explain what this product would change in someone's working day. Founders can ship impressive technology quickly and still lose the brief opportunity to make it understood.
Veronica Hylak's approach gives that short conversation three jobs: identify the customer's pain, make the product understandable, and show the change it produces. She brings experience building products and helping YC startups, safety organizations, and AI teams explain their work. Hylak reports that her AI explainers have reached eight million views.
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Start with the customer's wound
The wound is the customer's most recognizable pain: the moment in their job when they want to throw their laptop out a window. Your first slide should put them back into that situation, showing the work they are already tired of doing. Starting with what you built asks the audience to infer why it matters before you have established the problem.
Hylak recalls a recent Series B startup describing an agentic orchestration SecOps platform for enterprises. The category label carries little emotional information. A security team's actual experience is much easier to understand: dozens of disconnected tools, alerts in one system, tickets in another, vulnerabilities somewhere else, and the investigation scattered through Slack threads and screenshots.
Only after that picture is clear does putting everything in one place become a meaningful product promise. It addresses overwhelm, time lost finding context, and unnecessary difficulty in the team's daily work. The same capability now has a reason to exist in the listener's mind.
Hylak recommends an opening sequence of about 20 seconds:
- Identify the wound. Describe the frustrating situation the customer recognizes.
- Say “We fix that.” Connect the product directly to that situation.
- Show how. Make the effect on the customer's work visible.
This sequence gives the product a place in the buyer's day before asking them to understand its internals.
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Give the buyer a mental image
Once the audience recognizes the pain, the product itself must click. Hylak's comprehension test is straightforward: could someone understand what you do? A familiar story can shorten the distance between an unfamiliar product category and a problem the listener already understands.
Consider the viral clips of McDonald's AI drive-through ordering, including the bacon-on-ice-cream mistake Hylak describes. The scene makes public AI failure immediately legible. For a company working on agent observability, it supplies a more concrete opening than the category name alone.
Hylak proposes a hypothetical pitch: had McDonald's used the product, the drive-through would never have made it to TikTok. The explanation then supplies the mechanism: catch AI agents going off script and give teams a chance to correct them before the behavior becomes a public relations problem. The prevention claim is part of the imagined pitch, not evidence of an intervention at McDonald's. Its storytelling function is to make detection and correction feel consequential.
Concrete descriptions can also work without a viral incident:
- A recognizable role: Devin, the AI software engineer, gives the listener an immediate picture of the work the product is intended to do.
- A familiar protective device: a smoke alarm for AI behavior suggests detecting trouble and warning someone who can respond.
Neither description is a complete technical definition. It is an entrance to the conversation. Technical detail can follow when the buyer understands why they want to hear it—and can help close the sale.
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Show what changes in the customer's work
The final step moves from describing the product to showing its value. Improving code quality with AI or increasing productivity sounds desirable, but neither statement explains what will happen differently once the product enters the customer's world. Make the before and after visible.
Hylak illustrates the comparison with a support team's information search. These are example pitch values, not a measured product benchmark.
| Aspect | Before | With the product |
|---|---|---|
| Work | Dig through documents and tickets | Ask one question |
| Time to answer | 30 minutes | 10 seconds |
| Result | Information found through manual search | Answer with sources attached |
The change includes both the effort required and the result delivered. An answer with attached sources is more specific than a promise of productivity: the buyer can picture what appears after asking the question. Seeing the old workflow alongside the new one makes the value understandable.
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Return to the elevator
Back in the elevator, the vague time-saving pitch starts again, then gives way to a recognizable problem: the team is digging through Slack, email, and random Excel spreadsheets to find one piece of information. The revised pitch describes hours of searching becoming answers in seconds. Its explanation is concrete: connect the fragmented knowledge in one place so the team can search it and get the answer it needs. This is the proposed customer transformation, expressed as a pitch.
The product has stayed the same; the story has changed. Hylak contrasts today's market with 15 years earlier, when building something great might have been enough for the market to find it. Her commercial argument is that clear stories help products get funded, bought, and discussed, while technology people cannot understand can disappear quietly. The closing frame makes that compression visible: a box of technical terms points toward ChatGPT and the description “AI you can talk to.”
The elevator explanation now has a complete progression: the customer's wound makes the problem matter, a concrete description makes the product click, and the transformation shows why someone would want it. That gives a technically strong product a chance to be understood within the short conversation that decides whether there will be a longer one.
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Resources
From the talk
Cognition's original introduction to Devin illustrates the concrete product description used in the talk.
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