News Flash:
Superhero Saves Square Peg from Round Hole!
“Prompt Engineering” shouldn’t be a thing. GPTs are the world’s largest encyclopedias. The data is vast, meaning it can tell you about Quantum Mechanics, but it’s also generic, meaning it can’t differentiate the strengths of your solutions from those of your competitors. Because of this, “Prompt Engineering” became a thing. The crux of engineering is getting a tool to do something it was never built to do. Looking at a GPT interface is reminiscent of a DOS prompt on a PC back in the 80s. The word was that everyone would have one of these things on their desk in a few years. Right. The issue is the “learning cliff.” When using a tool is more daunting than the perceived value of the solution… people don’t use them!
GPTs are a consumer interface into a Large Language Model.
It doesn’t know your differentiation and brand voice. You need it to know more.
“Prompt Engineering” became a thing because you’re trying to make it do something it wasn’t designed to do.
GPTs are today’s DOS prompt.
- According to McKinsey research, Generative AI adoption rates in marketing and sales are at 14%. The pace of AI adoption does not align with its potential advantages. Yet, 75% expect Generative AI to cause significant or disruptive change within three years.
- Gartner indicates that 34% identify a lack of AI skills and knowledge. A similar 1/3 of companies identify resistance from employees who fear role reduction or elimination as barriers to AI adoption. Additionally, 31% highlighted the need for training and development to upskill and share knowledge as critical issues, identifying major challenges related to understanding, education, confidence, and trust in AI technologies.
- The Rain Group’s industry research underscored that 50% of respondents reported difficulty keeping up with AI advancements, and 38% felt overwhelmed by the options and use cases. Furthermore, 59% showed concern about inaccurate or misleading information from AI, and 45% were wary of data privacy and security issues, underlining the issues of trust and confidence in these tools.
These statistics reflect real-world challenges in AI adoption. Anxiety, fear, and overwhelm are caused by rapidly advancing technologies that people find difficult to track and understand.
What if we changed the calculus?
Sales and marketing teams should be able to enter a plain English question and receive a human-written quality output from an AI tool. Period.
Prompt Engineering would become unnecessary.
The tools would comport to the user. Not the other way around.
Introducing the Symplexity.AI Studio
Symplexity.AI is like using a PC with Windows rather than DOS.
The tool does what it should without a radical change in user learning and behavior.
Symplexity.AI removes the GPTs from the equation, inserts your learning, brand voice, differentiation, and persona needs into the equation, and communicates directly with OpenAI.
This technology was purpose-built to address the gap between AI’s evolving capabilities and the actual adoption rates within sales and marketing teams. Today, your team can interact with AI using simple English questions and get human-written quality responses that reflect your brand.
The perceived complexity, risk, and general lack of foundational AI knowledge among these teams unnecessarily cause anxiety and prevent progress in realizing the benefits of this groundbreaking new technology.
The core problems that Symplexity.AI aims to solve involve:
- Simplifying the perceived complexity and risks believed to be associated with AI.
- Democratizing the successful application of AI. Our approach to creating Custom Language Models bridges the divide between the potential of AI technology and the current latent adoption inertia. These tools should be easy to use. These tools should adapt to the user, not force users to comport to them.
- The decision between generic tools that create verbose and unusable responses and the need for education to help employees use them shouldn’t exist.