Problem-First Approach to AI Yields Faster Results, According to Saraplowman

In a recent LinkedIn post, Saraplowman offers a contrarian view on how businesses should approach the integration of artificial intelligence (AI), suggesting that many are starting with the technology rather than the underlying business challenge.

Saraplowman posits that the conventional method of beginning with AI tools and then searching for applications is less effective than the reverse. The author shared their experience, stating:

“I think most people are approaching AI backwards…🤖 They’re starting with the tool and asking…“What can I build?” 🤔”

Instead, Saraplowman advocates for a problem-centric strategy, emphasizing that identifying a specific issue should precede the selection of an AI solution. This approach, according to the author, leads to more practical and rapidly deployable outcomes.

Defining the Problem Before the Technology

Saraplowman illustrates this point with a personal example rooted in sales prospecting. The author outlines the critical questions a salesperson needs answered to optimize their outreach efforts, such as identifying the most promising leads and the optimal time to contact them.

The author’s process involved articulating these core sales challenges before engaging with AI tools. Saraplowman explained this method:

“For me, that problem was prospecting…If I had to hit quota next quarter, what would I want to know before I picked up the phone? Who should I call first? 📞 Who’s actually worth my time? When are they most likely to answer?”

By clearly defining these needs, Saraplowman was able to direct an AI tool, Perplexity, to build a solution tailored to these specific requirements. This contrasts with a scenario where one might explore the capabilities of an AI tool without a predefined objective.

From Idea to Usable Solution

The core insight Saraplowman draws from this experience is the speed at which an idea can be transformed into a functional solution when the problem is the starting point. The author highlights:

“So instead of building a workflow from scratch, I explained my process and had Perplexity Computer build around it…The most interesting part wasn’t the output…It was realizing how quickly you can turn an idea into something usable when you start with the question instead of the technology!!!”

This perspective suggests that a clear understanding of the ‘why’ behind AI adoption—the specific business problem it aims to solve—is more crucial than understanding the ‘how’ of the technology itself. Saraplowman’s post, tagged with #AI and #Sales, encourages a more strategic and problem-driven adoption of artificial intelligence within business contexts.