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Can Generative AI increase Productivity for Manual Test Cases?

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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Enhancing Python API with ChatGPT

Alejandro Tommasino is a fixer. Well, he’s a Solutions Architect at ITX Corp. But when something’s not working properly and no one else can figure out why, you call in Ale.

That’s exactly what happened when ITX was deploying a new API to access a My SQL database. The codebase was supposed to go into multiple databases, create a report of ITX employees and their roles from the data, and then deliver that report. However, the site would always mysteriously crash about six hours after the report was delivered.

The team was stumped; a lack of error management in the code prevented them from figuring out what exactly was failing. If your car just shut down while you were driving without showing something like a check engine light, anything could be the problem.

So, that’s what Ale was tasked with. The problem? Python. Although Ale had experience with C#, PHP, and JAVA, the project was written in Python, a programming language that he had never even touched before.

Very early on, Ale decided that he would use ChatGPT to help diagnose and solve the problem; however, he realized the AI would be best used not as a magic box that spat out code, but as a learning tool. “It’s cool to say AI fixes everything, but when it comes to technical things, like coding, there are still a lot of errors,” Ale said. “When I moved my mindset to not having the AI do the work for me, but be there for me and enable me, that’s where I found it to be most helpful.”

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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.

Read Article
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