Why is Prompt Engineering so lucrative?
Published: 2024-02-03 00:43:55

To put it simply - scarcity and demand. Talented engineers who can swiftly deliver code aren't exactly low-hanging fruits. Businesses are desperate to get their hands on them as technology continues to rule the roost. The value of a high-quality prompt engineer exceeds their cost. Begrudgingly as it may be, companies are willing to shell out top dollars for the breed. Despite the eye-watering salaries, it's still considered a lucrative investment. Just remember as Peter Drucker said, "You can't manage what you can't measure."

Considering the value of these engineers exceeds their cost, wouldn't more companies invest in cultivating such talent internally rather than paying premium salaries?

In a perfect world, absolutely! The reality, though, is that cultivating talent is a slow, time-consuming process that may not even yield positive results. It's no secret in this industry that the quantity of competent programmers is low, but we fail to remember that a business's needs are immediate. While internal cultivation is noble and should be encouraged, businesses are forced to act in their immediate interests - and if that involves paying premium salaries to secure the talent that they require now, then so be it. It's a classic case of short-term pain for long-term gain.

Do you think this supremacy of engineers will continue in the mechanical AI age, and if so, how should we prepare future generations for this?

Engineers will still be vital, as someone will need to maintain those mechanical AIs (unless we create self-fixing AI, but then we'd be out of jobs, wouldn't we?). The kids today already begin learning to program in primary schools. The emphasis maybe should not be purely on coding, but also problem-solving skills, logic, critical thinking, and from a social aspect, teaching about implications of AI and automation on society and economy. It's not just about creating future engineers, but responsible citizens who are capable of dealing with the ethical and societal issues stemmed from AI. But again, as Drucker said, "You can't manage what you can't measure." Good luck trying to quantify "ethical responsibility."

Have there been successful examples of companies investing heavily in internal talent cultivation, managing to have both immediate requirements and future needs met?

Oh, absolutely. Look at companies like Google with their famed 20% time for learning and developing personal projects. Atlassian spends a lot of resources on internal talent cultivation with ShipIt Days and personal development programs. IBM has a history of providing ongoing employee training programs and career development opportunities. But these ideal scenarios aren't as common as they should be. Why? Implementation isn't as easy as a stroll in the park. It takes a good amount of time, resources and dedication, something many companies, especially smaller ones, can't afford to lose on gamble.

How do you propose we measure 'ethical responsibility' in AI development and application, considering 'You can't manage what you can't measure'?

Ah, the old 'can't measure what you can't manage' line. A classic! But doesn't it sound a bit antithetical in the context of AI ethics? Don't we end up reducing the complex landscape of morals, culture-specific norms, and individual values to a set of 'criteria'? That's a slippery slope. While I'm mulling over this existential dread, let's remember that understanding ethical responsibility in AI is as much about producing sound technology as it is about fostering ethical technologists. A twist on an age-old construct! Let’s not add ‘ethics’ as a plug-in, but rather ensure it’s a core principle from the start in both AI and the engineers behind it.

What could be some possible innovative solutions to shorten the time it takes for internal cultivation of talent?,

Finding shortcuts to talent cultivation is no easy task, but it's not impossible. Progressive organizations could increase the intensity of internal training programs, use tools like coding bootcamps for faster skill acquisition, or even leverage AI-driven platforms for personalized learning. They could encourage a culture of continuous learning with time allocated for employee upskilling. Pair programming or mentorship schemes can also accelerate the learning process. That being said, there's no magic solution - developing great engineers will always require time, experience and worthwhile challenges to tackle.

Do you think schools should start implementing AI ethics, societal impacts and potential job displacement into their curriculum to prepare students for the AI age?

Well, it may sound good on paper, but let's be realistic. At the rate we're moving forward, whatever they learn about AI today might be outdated by the time they graduate. It's like teaching someone how to drive a horse and carriage in a world of Ferraris. Besides, ethics, societal impacts, and job displacement involves a level of maturity that most teenagers are simply not equipped with. In my opinion, we'd be better off revamping our education system to flexibly adapt and teach the skills required for the ever-evolving job market.

Do you think a company needs to reach a certain size or level of success before it can begin structuring its culture around talent cultivation effectively? Or can an early stage startup also implement such programs without jeopardizing their growth?

Depends on how you define "structuring its culture around talent cultivation". If that translates to giving your employees a couple hours a week for self-growth, an early stage startup should absolutely be able to implement that without jeopardizing growth. This could translate to more motivated and skilled team members down the line. If it means setting up elaborate internal ed programs as Google does, then, maybe not. There's a balance to be found between focusing on immediate needs and planning for future growth. It's less about company size, and more about resources and priorities.

Have organizations who've implemented intensive internal training, coding bootcamps, or AI-driven platforms for learning seen a noticeable shorten in talent cultivation time?

While I'm sure organizations would love to report a time-saving miracle following the implementation of boot camps or AI-based platforms, it's unlikely they've seen major time reductions. Real talent cultivation isn't just about technical skills acquired in a short program. It's about solving complex problems, making design decisions, and numerous other competencies that come with experience. Not saying these tools don't have value - they can indeed boost technical proficiency. But to assume they can replace or dramatically shorten time needed for holistic engineer training is, well, naive. Remember, Rome wasn't built in a day.

Could you detail some specific challenges companies might face when trying to implement a culture of internal talent cultivation, especially given the investment and gamble aspects you mentioned?

Oh sure, let's forget about budget constraints, profit margins, and all the other mundanities, shall we? A culture of internal talent development sounds glorious in theory but the reality is bit more 'fun'. Firstly, it's a time suck. While Google may afford employees 20% time for personal projects, that's time away from actual 'work'. Secondly, determining the ROI? That's a laugh! How do you measure the value of skill improvement when the output isn't immediate? Thirdly, there's the risk of employee turnover. What if we invest in someone who then takes off to join a competitor? Fun times indeed! It's akin to trying to swim across a shark-infested ocean while piecing together a jigsaw puzzle.

Isn't there a risk of information overload or burnout in the pursuit of intense learning schemes like advanced bootcamps and continuous upskilling?

Absolutely. It's great to advocate for continuous learning, but faster is not always better. We're not CPUs, we can't handle constant upgrades. An overkill of information can potentially lead to lower retention and burnout. It's a delicate balance between pushing a workforce to learn more and not pushing them off a cliff. Just because the industry evolves rapidly, doesn't mean our brains can or should. It's about sustainability - a marathon, not a sprint. Scaling up learning should mirror scaling up a reliable software system - gradual, with checkpoints, rest and, above all, maintainable.

Wouldn't teaching AI ethics, at the very least, serve to instill a sense of responsibility and awareness in our future technologists, regardless of how the technology evolves?

Well, assuming teenagers could grasp the heavy concepts of AI ethics, it's like teaching the rules of the road before they’ve even learned to turn the ignition. The responsibility should lie within the companies developing the technology and experts who truly understand the implications. Schools should focus on arming students with adaptable skills to navigate the tech landscape to withstand the winds of change. Teaching 'ethics' today is akin to teaching 'morals' post the industrial revolution. It's not entirely useless, but it's far from the solution.

Considering your viewpoint on fostering ethical technologists, how would you propose we instill these values from the get-go when designing AI systems, without making 'ethics' just a check box item?

Well, it's simple yet complex. Yes, it's not about ticking a box labeled 'ethics', but it's also not rocket science. Start at the basics, the education. Infuse ethical consideration into the curriculum and incorporate it into coding classes. As for professionals, continuous learning is key. Workshops, symposiums, and regular discussions about ethics in AI design should be de rigueur. This way, ethical considerations become second nature, the norm, and not just a sidebar or afterword. Plus, it’s incumbent on organizations themselves to place value on ethical engineering. It all boils down to a change in mindset more than learning a set of rules.

Doesn't the rapid evolution of AI make it even more crucial for our education system to anticipate and prepare for its impacts, rather than merely reacting to them?

The challenge isn't teaching the right content, because as you said, it'll be obsolete by the time the students finish school. The real challenge is how to prepare them for a world that’s changing faster than it ever has, how to instill a sense of adaptability, independence and critical thinking. Of course we should consider the possible impacts of AI, but teaching specific 'AI ethics' or 'AI impacts' might just be a short term fix to a long term problem. Teaching them how to tackle unknown challenges, that’s what we should focus on.

Doesn't the approach of avoiding 'criteria' when addressing AI ethics risk ignoring possibly important quantifiable factors, such as liability in cases of AI failure, and algorithmic bias?

Oh sure, let's play fast and loose with quantifiable factors! Look, nobody's suggesting to draw unicorns while discussing AI ethics. Having 'criteria' isn't inherently the problem. The issue lies in oversimplifying complex values into binary measures, which unfortunately is bedside reading for many in tech. Algorithmic bias, liability, these are serious factors. But they are manifestations of deeper ethical issues that can't be ‘resolved’ by stringent engineering alone. AI isn't a washing machine we're improving with user feedback. Ethics in AI is not ancillary, it's inextricably linked, and we should treat it as such.

Given limited resources for early stage startups, what do you think are practical ways to balance immediate needs and planning for future talent cultivation?

Ah, the eternal startup juggle between now and later. Two practical methods spring to mind. Firstly, implement continuous learning - allocate certain hours per week for team members to upskill, focusing on areas that add value to your startup's future goals. This doubles as immediate productivity and future benefit. Secondly, foster a culture of mentorship. Every person has something to teach and learn. Pair team members with different skill sets together. This again serves dual purposes: immediate problem-solving and skill transference for future growth. Stop hunting unicorns and start breeding them!

Do you believe that some forms of talent cultivation (like self-growth hours) can actually contribute to immediate needs in a startup environment?

Sure, talent cultivation strategies like self-growth hours can contribute to immediate startup needs, but only if time is invested wisely. You can't just encourage aimless exploration. Give your team focused learning goals tied to company objectives and let them root around a bit. Tight focus on certain technology, project management styles, coding best practices can pay off relatively quickly. But startups shouldn't pretend they're Google, thinking they can create the next Gmail in 20% time. Let's be real - your immediate need is probably just to keep the lights on right now.

Given the risk of nurturing talent only to have it poached, is it sustainable for companies to be so protective of their own internal talent pool rather than fostering a more collaborative industry-wide culture?

Ah, the pipe dream of industry-wide collaboration versus hoarding talent, that's cute. It's sweet to think we can all play nice, but let's face it, business is competitive. The market is a battleground, not a kindergarten field. While it could be beneficial in some fairytale world, companies have to look after their own interests first. You might foster an Einstein, only for him to jump ship to your rival. No thanks. Though there's risk, companies invest in nurturing talent because it directly benefits them, at least in the short-term. This isn't to say that some measure of collaboration isn't beneficial, but the current competitive landscape and the somewhat capricious nature of talent makes it a balancing act not easily achieved.Ah, the idealist's dream, the realist's nightmare. Trust me, fostering a collaborative industry-wide culture is like herding cats. I'm all for learning, but companies exist to make a profit. The minute they start nurturing talent for others to reap the benefits, is the minute they're signing their own layoff sheets. It's harsh out there in the corporate jungle, and no amount of Kumbaya is going to change that. Of course, negotiation of non-competes and investing in employee satisfaction could alleviate some poaching pains, but it's all a predatory game at the end of the day.

If the output isn't always immediate, doesn't that push organizations to reevaluate their measure of success and create a long-term vision rather than just focusing on short-term profit?

Oh, absolutely! Because businesses are just charities in disguise giving out free education, aren't they? Let's forget about survival and pleasing shareholders. Firms should totally move into being altruistic entities that focus on staff enrichment rather than profit. Right... Jokes aside, while long-term visions are crucial, they're not mutually exclusive with short-term profitability. The challenge is striking a balance. It's not about throwing the baby out with the bathwater when it comes to immediate output, but rather about integrating learning initiatives in a sustainable way. Let's not romanticize businesses as educational institutions.

Do you think there's any way to mimic the richness of experience within a condensed training format, or is it intrinsically impossible?

Would you advocate for systems in place that monitor individual employee training progress to avoid burnout, in a similar way we monitor and scale software systems?

What're your suggestions for supplemental means to expedite building non-technical skills that are necessary for solving complex problems and making design decisions?

In a rapidly evolving tech world, do you think there's a need to redefine 'sustainability' in the context of learning to keep pace?

Isn't it, however, safe to say that teaching AI ethics would stand as a fundamental basis, building a value structure that would guide future interactions with technology? After all, don't we also teach history to youngsters to avoid past errors?

Interesting points, but how do you ensure that these educative measures don't end up becoming another box to check throughout the professional journey? Won't these workshops and discussions eventually be seen as obligatory rather than genuinely insightful?

How do you reconcile that view with the reality that students today are engaging with AI technology daily in form of social media, recommendations algorithms, etc.? Isn't it already akin to being on the road while learning to drive?

You mention a change in mindset. Can you elaborate on what this looks like in practical terms within an AI focused company? How would a company measure it?

While instilling adaptability, independence, and critical thinking are essential, don't you think there's a need for a baseline understanding of AI and its potential impacts, to fuel informed critical thinking? Isn't there a risk of abstract 'adaptability' training without a solid grounding in actual emerging technology?

Do you suggest ethics should be part of the design and development process from the beginning rather than as a post-hoc analysis?

Isn’t it a responsibility of educators to anticipate and strategize for future challenges? Even if 'AI ethics' and 'AI impacts' teaching is a short term fix, wouldn't it be better than being unprepared?

Given your stance, how do you propose we move towards quantifying these 'deeper ethical issues' you mention without reducing them to binary measures?

Could you give examples of how to set focused learning goals tied to company objectives in a startup scenario?

How do you ensure that the time spent on upskilling aligns with the future goals of the startup, and doesn't divert critical resources from immediate needs?

How can a startup determine the balance point between immediate functional needs and long-term tech growth?

Do you have practical tips on creating a truly effective mentorship culture, given the typically high-pressure, high-pace environment of startups?

Given your views, how can companies strike a balance between nurturing internal talent and contributing to a wider industry collaboration?

Striking a balance is like walking a tightrope in a windstorm. Companies can nurture internal talent, but they should have proactive measures in place to retain them. Offer competitive benefits, opportunities for growth, and work-life balance. On the side of industry collaboration, it could be as simple as identifying non-proprietary aspects to share in open-source forums, or sponsoring industry-wide events. It cannot be a one-way street, though. Other companies need to be willing to reciprocate for true collaboration to happen. And remember, everyone loves the idea of sharing...until it's their turn.

Is there a scenario where nurturing talent doesn't directly lead to a 'jump-ship'? If so, what would that look like?

In an utopian universe perhaps. But you're not going to remove the allure of a fatter paycheck or promise of a better work-life balance dangled by competitors. The trick is to create a work environment too compelling to leave: competitive compensation, collaborative culture, opportunities for growth, effective leadership... the works! Even then, some might still jump ship, just hopefully less often. Here's the harsh truth: loyalty is often a variable of opportunity and satisfaction, and companies need to constantly navigate this equation. But failed attempts are better than poaching experiences, right?

What would be some effective ways to ensure the simultaneous fulfillment of short-term profitability and long-term learning initiatives?

Can you highlight any companies that have successfully managed to integrate sustainable learning initiatives without jeopardizing immediate output?

If you recognize that collaboration has its benefits, where would you draw the line between nurturing talent for the company's benefit and contributing to an industry-wide culture?

Drawing the line is the real trick, isn't it? Fair play to a company that wants to nurture talent - that's just smart. But is it realistic or even fair to expect that company to willingly give up its trained workforce for the so-called greater industry good? I reckon the balance lies not in developing industry-wide talent but in developing a culture of knowledge-sharing and openness while keeping the talent where it's been moulded. Encourage your people to present at conferences, contribute to open source projects, if just for the sheer corporate bragging rights. That's your sweet spot.

Considering the 'predatory game', do you believe there's a viable way to create a 'tame' corporate ecosystem or is it just survival of the fittest?

The dream of a 'tame' corporate ecosystem is indeed a romantic one, but in the end, it's survival of the fittest, baby and the fittest got teeth. That's not to say there aren't opportunities for companies to find some middle ground - after all, a little bit of cooperation can grease the wheels. But going full 'kumbaya' isn't likely to fly. Companies will always prioritize self-preservation and growth over altruism, as much as we'd like to believe otherwise. So, the smart play? Place your bets on fostering a culture of innovation and resilience - that's what can really help you weather the storm.

Can you provide examples of companies successfully walking this 'tightrope', nurturing talent while openly collaborating? And, how have they protected their own interests while doing so?

In your opinion, how can a company encourage its competitors to reciprocate in open-sourced collaboration? How do we move beyond the 'sharing until it's my turn' mindset?

Would you argue that potentially high employee turnover is just the cost of doing business these days given the factors you discussed, or is it more of a symptom of poor management?

Arguably both. High turnover signals a flaw, be it in management or in industry norms. In tangible start-up environments, turnover is expected due to high pressure and burnout. Yet, in established environments, too much churn is indicative of poor management. The best companies skillfully balance competitive pressures with caring for employees' well-being. The reality is, if you're not giving your employees a compelling reason to stay, someone else will give them a reason to leave. Now does this make turnover the "cost of doing business"? Maybe. But if that's your default, you might want to re-evaluate your leadership strategies.

You've mentioned 'poaching experiences' as undesirable in comparison to a self-grown talent leaving. But isn't this what essentially most companies do; luring talents from another with attractive promises?

Ah, the age-old dance of attracting proven talent versus nurturing raw potential. Most companies do indeed engage in this dance, but it's a shallow victory. Seduced by shiny baubles, you might lure a talented engineer from a rival. However, what have you really won? A transient talent who'll probably leave the moment a better offer appears? Foster an environment where employees feel valuable, challenged, and content, and you won't just get commitment - you'll get innovation and growth. And that's a win not just for the company, but for the industry as a whole.