The AI Adoption Straight Line: Finding Focus in the Age of Unlimited Potential

Fortune smiled upon me in the most spectacular way

I recently received what every Product Manager dreams of: the ultimate gift of empathy, wrapped in AI brilliance. Through a LinkedIn automation twist of fate, I found myself in conversation with the CEO of BuildBetter.ai. Following an impressive demo, I was invited to explore their innovative platform, specifically designed for product managers. And thus I embarked on an exciting and revealing journey.

Like any passionate product professional (a special breed of optimistic masochists), I dove in headfirst. In my ongoing quest for AI tools to streamline my own product management, BuildBetter caught my attention with its focus on video chats, my personal favorite form of communication. Imagine a sophisticated fusion of Otter’s transcription prowess and ChatGPT’s intelligence, but evolved into something even more remarkable.

My initial week with the platform revealed the familiar growing pains of adopting new technology. The transition from sales to customer success was rocky and I encountered hurdles while introducing the platform to my team. Even those colleagues who ventured to try it faced considerable resistance in making it part of their workflow. While the platform excelled at video data collection, I found myself overwhelmed by the array of features and possibilities – ironically experiencing the same hesitation and confusion I regularly witness in my own users. This moment of vulnerability became a powerful mirror, reflecting insights about my own limitations I hadn’t expected to confront.

What emerged weren’t flaws to criticize, but valuable learning opportunities for both sides. Every piece of feedback I shared revealed improvements not just on their platform but on my own approach to product development. The BuildBetter’s team response was exemplary – they embraced each suggestion with genuine enthusiasm and gratitude, demonstrating exactly the kind of receptiveness users dream of encountering. Most impressively, as our discussion unfolded, other team members were already springing into action behind the scenes, working diligently to enhance the user experience.

Let’s be honest – every AI product today is basically trying to solve the “how do we make this not weird?” puzzle. While AI promises to revolutionize everything from rocket science to making toast, most professionals are stuck in that awkward phase where the AI is less “helpful assistant” and more “eager intern who keeps rearranging your desk.”

Looking at BoodleBox, my own digital offspring, I’ve had to admit that I’ve been guilty of allowing the “but what if we made it do everything?” syndrome when “do one thing well” was staring us in the face. I realized that even for someone deeply immersed in product development, we must all must “crawl before we run.”

This experience has led me to develop what I’m calling the “AI Adoption Straight Line” theory – which is really just a fancy way of saying “keep it simple, stupid” with extra empathy and baby steps thrown in. Easy to preach, harder to practice, and even harder to admit when you’re not following your own sermon.

The Current Landscape

2024 marked a watershed moment in AI integration, with chat interfaces leading the charge. As we navigate through 2025 and beyond, we’re approaching a crucial turning point from “Look, it can finish my sentences!” to “Actually, we need this to pay the bills.” This transformation demands a complete reimagining of our approach to both AI-enhanced software development and user experience design.

The software industry is currently doing a rather impressive split between two worlds: the comfortable old realm of clicking buttons (ah, simpler times), and the brave new world of asking AI to do things in plain English. This dichotomy has led to an interesting phenomenon where both established companies and new ventures are retrofitting AI chat capabilities onto existing solutions, often redundantly solving previously addressed problems. Basically just strapping rocket engines to bicycles, convinced that’s what transportation needed all along.

Here’s the real head-scratcher for product leaders: how does one effectively communicate specific value when their tool’s capabilities are essentially boundless? The irony is the more possibilities we offer, the more users retreat to the comfort of basic features, rarely justify the substantial computational investment required.

The Straight Line Solution

To address this challenge, I propose a straight line approach – the radical notion that maybe, just maybe, we shouldn’t try to boil the ocean with AI. Revolutionary, I know.

Instead of overwhelming users with infinite possibilities, what if we focused on the stuff users actually need to do? You know, those mundane, everyday tasks that everyone does, all the time, without fail. The boring stuff. The stuff that actually keeps businesses running.

Here’s the groundbreaking formula:

• Find what 100% of users do 100% of the time
• Make that ridiculously good
• Don’t add a chatbot just because you can

This approach accomplishes three things:

1. Saves users from decision paralysis (because nobody needs 47 ways to send an email)
2. Ensures you’re not burning compute power to generate haikus about project management
3. Creates a solid foundation for future features that people might actually use

In other words: Let’s make AI boring again. But like, useful boring. The kind of boring that gets things done and doesn’t require a PhD in prompt engineering to use.

Building User Confidence Through Repetition

The secret sauce of AI adoption is boring, predictable success. Not exactly the stuff of sci-fi dreams, is it?

Think of it like teaching a teenager to drive. You don’t start with parallel parking on a steep San Francisco hill during rush hour. You start in an empty parking lot, doing the same mind-numbing circles until muscle memory kicks in. Then, and only then, does that teenager start asking, “Hey, what happens if I try…”

Turns out, users don’t fall in love with AI because of some flashy feature list or the theoretical possibility of achieving digital nirvana. They fall in love with it the same way you fell in love with your favorite pen – because it writes smoothly and never fails you when you need to jot something down.

The magic happens when users stop thinking “Will this work?” and start thinking “I wonder what else this can do?” It’s like watching a toddler go from wobbly first steps to running marathons. Except in this case, the toddler is your user, and the marathon is them finally figuring out how to use your AI for something you never even imagined.

Who knew that the path to revolutionary AI adoption would be paved with… consistency?

The Visionary’s Dilemma

Let’s be honest – telling a product visionary to limit their AI’s capabilities is like asking a kid in a candy store to only eat vegetables. I know it hurts.

Yes, you’ve got a technological Ferrari under the hood. Yes, it could probably write a dissertation on quantum physics while composing a symphony and debugging code. And yes, it’s absolutely killing you to watch people use it as a glorified calculator.

Think of it as strategic sandbagging – I’m not permanently condemning your AI to a life of mundane tasks, just making sure users don’t run screaming for the hills when they see everything it can do. It’s like dating – you don’t lead with “I’ve already planned our wedding and named our future children.” You start with coffee, or whatever AI-enabled virtual dating app the kids are using these days.

Looking Forward

Let’s cut to the chase: The AI Adoption Straight Line theory is basically the “teach a person to fish” philosophy, but for AI. Except instead of throwing them into the deep end with a nuclear-powered fishing submarine, maybe we start with a nice, simple rod and reel.

It’s not about showing off how many tricks your AI can do (sorry, data team). It’s about being the reliable friend who brings an extra phone charger, not the one who shows up with a portable generator and a complete backup power system when people just needed a quick battery boost.

To all you visionaries out there, clutching your models and muttering “but it can do so much more” – I hear you. I see you. I feel your pain. After all, even Iron Man started with a clunky Mark I suit before he got to the fancy nanotech version. And if Tony Stark can exercise patience, so can you.

The path to AI world domination – er, I mean, widespread adoption – isn’t a sprint. It’s more like teaching your grandmother to use a smartphone: start with calls, work up to texting, and before you know it, she’ll be creating autonomous AI assistants.

Baby steps, folks. Revolutionary, world-changing, AI-powered baby steps.