AI Success Series [Part 3]: The endless R&D spiral

This email is part 3 of our AI Success Series, where we're breaking down the three fundamental mistakes that doom 85% of AI projects to failure.

You can access the previous issues here:

• Issue 1: Mistake #1: Using AI with no clear “Why”

• Issue 2: Mistake #2: Starting your AI project with unclear goals

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Do you remember that really old Tootsie Pop commercial?

For the uninitiated, it went like this:

A young kid asks: “Mr. Owl, How many licks does it take to get to the Tootsie Roll center of a Tootsie pop?”

The owl takes the pop and starts licking… “ONE… TWO-HOOO… THREE!” and then crunches the whole thing down in one bite. And the narrator sighs, “...the world may never know.”

Anyone developing an AI product should strive to be like Mr. Owl:

🦉 He knew how to get straight to the center of a problem as fast as possible 🦉

But lots of companies building with AI right now take the opposite approach: “ONE more accuracy test... TWO more iterations... THREE more data points…”

Then they just keep going.

And before you know it, half a year has passed and the product still hasn’t shipped.

Which brings us to…

Mistake #3: The Endless R&D Spiral™

We've seen teams spend thousands of engineering hours building something that technically “works,” but it doesn't meet the original goal or deliver business value.

A real example: we once heard from a group that spent 9 months building an AI that could summarize customer complaints... but after they launched, they realized no one could be bothered to read them 🤦‍♂️

All of that could have been avoided if they’d gotten that product out the door more quickly!

Endless R&D often masks deeper issues…

• Fear of shipping something that might fail

• Waiting for the mythical “perfect use case”

• Lack of clear success metrics (hello, Mistake #2!)

• Not having real users lined up to test with

But the thing is: You can't validate AI without real-world feedback.

Unlike traditional software where you can predict behavior, AI systems need to encounter actual user patterns to reveal their true performance.

How to escape the R&D hamster wheel

Experimentation is great in a lab setting… but when it’s on the company dime, it needs constraints.

Otherwise you’ll burn a ton of time and money before getting any useful feedback.

The main thing to remember is: You don’t need to solve every possible use case at once. Just build an AI project that solves something real, quickly!

Here are 3 rules of thumb to follow:

1. Time-box your projects. Give yourself a short span of time (weeks, not months) to test a hypothesis, then make a decision.

2. Ship iteratively. Start with the simplest version that solves a real problem, not the complete solution.

3. Get real user feedback ASAP. Even a “suboptimal” AI with real users beats a “perfect” AI trapped in development.

Are you stuck in endless R&D?

Whether you’re planning an upcoming AI project, or if you’ve been spinning your wheels on one that’s already underway…

Let's talk about getting you unstuck.

If you’re interested in hiring one of our world-class development teams to help build your project:

👉Book a 30-minute consultation call with us here

If you need a quick refresher on what we do at AE Studio, check out our website here.

Next up: We’ll reveal the four types of problems where AI actually delivers the most business value… plus, real case studies of successful AI implementations in action.

See you then,

— The AE Studio Team