Why 2024 will be the year for prompt engineers

The future of large language models (LLMs) is most likely to be around democratising generative AI (GenAI) tools and optimising them for more use cases. We’ve seen what the technology is capable of; we’ll now focus on refining what we know and pushing the boundaries of deep learning even further. Datasets are bound to get bigger and make GenAI tools better and more reliable, and prompt engineers will be pivotal to aggregating organisational productivity across various industries. 

Prompt engineering involves helping GenAI tools produce the desired result while interacting with users. Prompt engineers create sets of text inputs to interact favourably with other inputs to get better responses. With the new year approaching and the technological rate of evolution rising, here’s why the demand for this class of professionals will skyrocket: 

1. Exponential growth of LLMs: OpenAI’s increasingly powerful models and the upcoming Gemini are expected to lead LLM capability into the future. Tasks like generating content, summarising ideas, responding to queries, and translating languages are just the tip of AI tools’ near-perfect mimicking abilities. As LLMs evolve, how users engage with these tools will necessitate more specific, efficient outputs. Prompt engineering will aid in getting the most out of this relationship. 

2. Democratisation of artificial intelligence: AI use cases are growing, from helping organisations build innovation pillars through generative design to letting individuals plan their holidays. AI tools are penetrating different levels of society while doing more and staying relatively simple—DALL·E 3 and ChatGPT’s integration being of notable consequence. More people and enterprises are accessing these solutions, and barriers to entry for engaging with LLMs are falling. Cloud-based platforms and user-friendly interfaces are driving this growth, and there’s more on the horizon. 

3. Broadening applications: LLMs are not concerned primarily with research and development. Models are being taken out of this specific sandbox and being used for several purposes. Their reach now extends to every conceivable domain. As the focus on productivity and reducing workplace redundancies leaps forward, use cases in marketing, education, product management, and more are improving. LLMs are stepping up to automate processes and help streamline user journeys everywhere. Unsurprisingly, prompt engineers will be at a premium. 

As companies begin to integrate LLMs into their workflows, their performances will need to be optimised. Prompt engineers will cater to this demand in the coming year, unlocking the full potential of LLMs for specific tasks and applications. 

A prompt engineer will need to have specific skills to be able to execute their role as the ‘AI whisperer’. Besides being creatively inclined to anticipate how users might interact with the AI, linguistic dexterity will be valuable. A good command of language is needed to understand how models might react to varying inputs, leading to different outcomes.  

Secondly, being able to think around problems and crafting usable prompts after critically analysing roadblocks should be a major selling point. Knowledge in deep learning, natural language processing, and machine learning techniques round off the technical skills segment. Here, concepts like neural networks, tokenisation, sentiment analysis, and data cleaning are essentials, while a strong programming foundation is just as vital. Using this mix of skills, prompt engineers will act as a liaison between man and machine, balancing human thinking against a technological canvas. For that reason, professionals in the field can expect handsome remunerations and benefits to go along with front-row seats to the AI revolution in real time. 

With the state of work changing rapidly through investment in GenAI capabilities, AI prompt engineers will be required to facilitate a seamless connection between users and technology. As innovations in LLMs make them more advanced and widespread in the general population, it will be up to prompt engineers to soften technical complexities for large sections of users and help them arrive at accurate and meaningful responses.  

The demand for these roles will be high—professionals should have the right skills/techniques and showcase the intelligence needed to be a part of the high hiring interest going into 2024. 

Abhinanda Sarkar

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Abhinanda Sarkar, Faculty Director at Great Learning.