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How to Solve the Non-Functional Requirements Problem

“The first iteration of a solution is going to be real rough” ITX Delivery Director Christina Halladay told me over coffee one morning. “It takes iteration, and solid communication, to get it just right.” In technology, we often find a disconnect between what we know it takes to craft an excellent digital product — knowing … Continued

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The AI Users Want Isn’t Autonomous

Recently, experimental AI models from frontier labs have been escaping containment (often through creative and unexpected means) and wreaking havoc. Misalignment between the intentions of humans, and the means that AI models use to accomplish their goals, means that the importance of human-in-the-loop decision making will only become more important as these newer, more capable models hit the … Continued

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A Review of Acquisitions in the WealthTech Industry

Recently, in the WealthTech industry, the big players have preferred buying to building. The biggest deals capture attention: Bain Capital taking Envestnet private for $4.5 billion, or Vanguard agreeing to buy Altruist for roughly $4 billion — more than double what the company was worth sixteen months earlier. However, looking at the largest acquisitions risks … Continued

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Lessons From a Billion-Dollar Acquisition Spree

For fifteen years, financial professional organizations such as broker-dealers demonstrated a preference towards building their own tech stacks. They hand-picked the best CRM, planning tool, and reporting software, then employed ad-hoc solutions to make the pieces work together. One company named Orion made a different bet. Instead of being one great tool, it would become … Continued

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The Hidden Aspects That Make or Break Application Modernization

Most organizations approach application modernization the same way: identify what looks old, pick a modern replacement, and build a timeline.  The scope feels manageable because the problem feels obvious.  Two years later, they may have an application that looks modern enough, but struggles to function. This pattern is not bad luck. It is what happens when organizations diagnose the problem by … Continued

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Tips and Tricks for AI Prompt Writing According to ITX Research

There is no magic bullet to making AI chatbots (aka Large Language Models[1]) perfectly accurate. Even if you follow our guide on Best AI Prompt Writing Practices[2], you may still struggle to get the AI to follow your instructions exactly. But, through our research on best practices, we also found some phrases that can alter how an LLM will respond. 

But first, let’s set a baseline. To observe how much we can affect an LLM’s output, we need to have a control. So, here’s a regular question for Microsoft Copilot, no bells or whistles. Let’s see what we get back (be warned, this is a taffy-heavy post!). 

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Best AI Prompt Writing Practices According to ITX Research

ITX is no stranger to experimenting with new and interesting technologies. Of course, hot-button and top-of-mind is AI-generated content: does it have a place within copywriting?

And while we at the ITX Content Team believe it does, we’ve continued to investigate the technology. Our research, which includes several internal experiments, has led us to believe that it could be a useful tool for a content writer, with some major caveats

So, how can you get the most out of a large language model (LLM)? If rumors are to be believed, everyone’s already using AI for everything. If that’s true, then how does anyone stand out if we’re all using the same programs?

Really, there is no secret. There are many different schools of thought, and some tricks you can use to improve an AI’s output, but it’s up in the air at the moment. Our general philosophy: to get good out, you’ve got to put good in.

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Can You Use ChatGPT AI for Writing? Our UX Writers Think So

It’ll seem so obvious in 10 years, won’t it?

By 2034, Generative AI may well be on its way to Artificial General Intelligence, capable of outperforming humans at most economically valuable tasks. Possibly this AI boom will pop like another dot-com-style bubble, inflated by hype. Or maybe we’ll be living underground, relying on dogs to sniff out machine infiltrators.

Unfortunately, we’re stuck in the present: a time where AI conjecture, hype, and fear swirls around the public sphere. To cut through this noise, we in the ITX User Experience Content team determined there was only one remedy: the scientific method. We put ChatGPT-4 through its paces to understand if it’s something that can add value to our clients’ products. Here’s what we found.

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