Tuesday, March 12, 2024

NEW INC. MAGAZINE COLUMN FROM HOWARD TULLMAN

 

The Future Belongs to Prompt Engineers

Although the platforms that will run AI will largely belong to big tech. There will still be plenty of opportunities for startups to live in this new world. 


EXPERT OPINION BY HOWARD TULLMAN, GENERAL MANAGING PARTNER, G2T3V AND CHICAGO HIGH TECH INVESTORS @HOWARDTULLMAN1

MAR 12, 2024

In my next life, I think I'd like to be a prompt engineer. If you don't know what that is, I'm not really surprised; most people don't.  But you should learn because in the next decade these folks are going to be among the most valuable, strategic, and in-demand employees in any company.

Prompt engineers learn how to think like a machine. Your business will need to find and hire these folks if you plan to be competitive for the same reason that most NFL football teams have more data scientists on their rosters than they do quarterbacks. Data is the oil of the digital age, and its use and proper application will drive every kind of company in the future.

If you plan to scale your business, you can be sure that you'll need to augment your team's own actions and decision making with machine-driven technologies to be able to match the speed, recall and reaction times of the competition. In the digital world, speed kills in a good way. Prompt engineers are the humans who will translate our queries and be our primary interfaces to the existing and constantly emerging massive AI knowledge systems, artificial neural networks, machine-learning environments and large language models (LLMs). These AI engines are now being built by the country's largest tech companies and rapidly deployed around the globe. As you might expect, the prime players are the usual suspects and the only ones who can afford the required investments while, of course, our government itself (unlike China's) isn't even in the game. Once again, it's gonna be a winners-take-all world.

There's also a powerful and discouraging reminder here of the early days of the computer gaming industry, where dozens of entrepreneurs thought they'd build their own game machines, interfaces, and programs. Over a relatively short period of time, these dreams were crushed by Sony, Nintendo, and Microsoft, each of whom developed a dominant platform and basically required all the other industry players to develop games that would run on top their platforms.

While stupid and greedy venture investors will invest and lose billions betting on AI nuts-and-bolts startups, it appears entirely likely that the real battle for platform dominance is largely over.  The playing field will be owned and operated by the same half dozen or so tech giants--Apple, Amazon, Meta, Alphabet, et al. -- that already own search, the desktop, our phones, email and messaging, video, and large slices of the Internet itself.

Everyone else will be remitted to running on top of these platforms, and as licensees or "partners," with the gatekeepers of these major systems. As the industry giants continue to build out the underlying infrastructure for these processing environments, the most likely and potentially profitable opportunities for entrepreneurs and new business builders will be in developing industry and market-specific tools and applications that make use of the capabilities of the LLMs and other versions of the machines, rather than trying to create new versions of the systems and machines themselves.

This is actually good news in one respect:  little guys will still have a place in the ecosystem. The successful smaller and more agile players will be more organized around supporting business operations, exploiting their industry and market knowledge, and enhancing business logistics, rather than on building costly and super-technical programs that take years to develop and are likely to be copied and overrun by extensions of the established players' offerings. In addition, the capital costs of entry for specific solution suppliers will be considerably less, as will be, at least initially, the cost of attracting and retaining scarce talent.

Amazon of old was a good example of this business versus bits distinction. Today, they call themselves an A.I.-driven tech biz, but at the beginning, Amazon was all about logistics, location, execution and speed. Their tech was okay, but the competitive edge was their aggressive leadership, industry knowledge base, powerful analytics, and people who were hungry, competitive, and scrappy workhorses rather than kids, academics and computer jocks. They quickly came to know the basic book business better than the big guys in the space and beat them at their own game. Also, in fairness, the development work, and advances that Amazon has made with Alexa in terms of voice recognition, interpretation, and conversation continuity have helped dramatically move the A.I. needle forward. That work remained largely under the radar for many years - whether by design or media inattention.

Knowing what's important to ask and how to frame the right questions of the new machines will be the most critical competitive skill set in the new A.I.-enabled economy. That's because, as often as not, it's harder to shape and design the precise question than it is to eventually find the correct answers. The skills required to do this job well are far more practical and qualitative talents rather than the more quantitative and purely technical ones we ordinarily associate with computer scientists and engineers.

Anyone who has ever asked Google a question and had the unsettling experience of being told in response that there are "about 1,250,000 search results" knows that limiting and narrowly stating your inquiry is the key to achieving any simple and useful answer. In much the same way, the current LLMs are way too much of a good thing and need to be tamed and bounded. In fact, at the moment the best way on the web to get the right answer to a question is to post the wrong answer and wait for the good Samaritans and the trolls to weigh in.

Smart prompt engineers will iteratively fashion and input the "prompts" or plain English questions, which will ask the generative machines for increasingly precise and detailed answers, solutions, directions, evaluations, statistical relationships, and other responses. This will all be based on the machines' compilations, interpretations, and discovered connections, which it will theoretically draw from literally all of the digital data and accumulated knowledge in the world. The latest advances have enabled the machines to retain the content and context of earlier inquiries and incorporate those requests into the continuing series of prompts, which has made the iterative process somewhat easier and more consistent.

What's especially attractive about becoming a prompt engineer is that anyone can learn the job and - as far as I can tell - not only don't you need an extensive technical background or an expensive education, you simply need a lot of common sense, an extensive vocabulary, the ability to constantly iterate and tighten down queries on a wide range of subjects, and a passion for problem solving, crossword puzzles, Scrabble and Wordle. Readers, writers, liberal arts grads, and kids straight out of high school are all welcome. It's about aptitude and knowledge, not college -- what you know, not where you go. It also helps to be hyper-literal and anal as well, but that's not essential. Remember that these people are trying to learn to think like the machine they're interacting with.  

And even if you (or your kids) aren't looking for a new career, and don't have access yet to the latest and greatest tools, you should still spend a few minutes experiencing these back-and-forth conversations. I recommend trying Microsoft's Copilot which is free, readily appended to its suite of Office products, and couldn't be easier to use. It invites you to "ask it anything" and it's an interesting trip down whatever rabbit hole strikes your fancy.  And more than a little addictive. You can start to build your own company-specific questions and also do a little DIY experiment to see how these systems can make sense out of, and better organize, your business's own data, historical information, and customer input about their experiences in order to provide support for and augment the performance and behaviors of your team.

Having instant access to the world's storehouse of accumulated information, literature, and knowledge at your fingertips is a very exciting and empowering feeling.  One which will give you a clear idea of why so many people are thrilled, awed, and scared by the possibilities, opportunities, and challenges of these new tools. AI is all about careful curation and filtering the flood at this point. Prompt engineers will be steering the ship and leading the way.