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Prompt Engineering Sucks – Here’s What You Can Do About It

In the fast-developing world of artificial intelligence, prompt engineering often feels like solving a Rubik’s cube blindfolded. Aporia decided to quantify this widespread frustration through a comprehensive survey of AI engineers. The results? A wake-up call for the industry. 

Aporia looked at over 2,000 posts from AI engineers on OpenAI’s forum and noticed a common theme: 84% of engineers agree that prompt engineering is frustrating to work with. 

That is not all. Around 89% find prompt engineering moderately hard or very hard to work with. Yet, 91% of respondents have not explored alternatives to prompt engineering, despite over 1,400 individuals reported struggling to reach their goals using this method. These findings suggest that the methods for controlling AI’s behavior need a radical rethink as it becomes more prevalent in our everyday lives.

According to Aporia’s Director of AI, Niv Hertz, this survey shows a need for alternative solutions to prompt engineering to ensure that all AI agents being used are truly safe and reliable and behaving exactly as they were programmed to.

Prompt Engineering Sucks – Here’s How to Make It Suck Less

In response to the challenges with prompt engineering, Aporia has developed a solution in the form of AI guardrails that can be inserted into any GenAI app to help control behavior from both the users and the AI. These guardrails function as an intermediary between the AI and the user, examining each message to guarantee it complies with predefined rules. 

Aporia’s Guardrail system offers real-time blocking, overriding, or rephrasing of messages that violate the guardrail policies. Through the use of guardrails, Aporia has seen a huge improvement in the reliability of AI systems, which benefits both developers and end-users.

Case Studies

“Our research uncovered numerous instances where AI systems failed to adhere to their programmed instructions,” explains Hertz. “Despite developers’ best efforts in prompt engineering, we saw AI agents deviating from intended behaviors in various scenarios – from multilingual applications to content creation and data processing. These cases demonstrate that relying solely on prompts is insufficient for maintaining consistent AI performance and adherence to guidelines.”

In the case of the child-oriented Q&A AI, the engineer faced significant challenges in avoiding sensitive topics unsuitable for children. Despite initial success, subsequent attempts failed to maintain the desired content restrictions, leading to frustration and uncertainty. This example highlights the limitations of relying solely on prompt engineering to control AI behavior.

Aporia’s Guardrails would act as a filter, automatically detecting and blocking responses related to restricted topics such as death or mature themes. Instead of generating potentially inappropriate content, the Guardrails will be configured to ensure a safe, standardized response like “This topic is best discussed with your parents.” 

For the second example involving data processing with large datasets, the developer encountered hallucinations and inaccuracies when dealing with complex prompts and extensive data. Having relied solely on prompt engineering, it was indeed frustrating to constantly edit the prompt, in the hopes that this would control the AI’s behavior.

When ensuring that a model generates inaccurate information, Aporia’s Guardrails work behind the scenes in real-time to block the erroneous output or override it with verified correct responses. This way, the AI-generated insights remain accurate and trustworthy, even when handling large volumes of data with intricate prompts. 

“When you look at this example, it shows you that guardrails are a non-negotiable quality control mechanism, maintaining the integrity of the AI’s output in complication data analysis scenarios,” explains Hertz. 

What Clients Can Expect From Aporia’s Guardrails 

Prompt engineering has traditionally been the main method for guiding AI behavior, but it often struggles with consistency and is difficult to work with. Aporia proposes a fundamental change in how engineers view AI reliability and control.

Through Aporia’s Guardrails, engineers can reduce the effort required for extensive prompt engineering and ensure their AI behaves in a consistent way. This means developers can focus on improving AI capabilities instead of spending hours constantly tweaking prompts.

What makes Aporia stand out? Aporia’s Guardrails are created with a multiSLM detection engine, meaning they provide some of the fastest and most accurate AI guardrails, protecting AI systems in real-time and with near-perfect accuracy. Engineers can choose from many pre-built guardrails or create custom ones. The system also provides detailed insights into the messages sent, allowing for better oversight and observability.

Now that AI continues to advance and become more integrated into aspects of business and daily life, solutions like these will undeniably be needed to aid these systems to remain safe and beneficial to society.

“Our solution empowers engineers, improves workflows, and speeds up AI adoption in areas that have been cautious due to reliability concerns,” says Hertz from Aporia. “We are opening new possibilities for using AI in important fields where consistency and safety are vital.”

Those interested in exploring the potential of this solution and improving their current AI development process can learn more about Aporia here

Photo courtesy of Aporia

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