The AI backlash is partially misplaced. On the one hand, the increase in electricity bills should be paid for by companies amidst the growing affordability crisis in America. The data center build out deserves political backlash by the general populace because people are not only fearful of being displaced, but they are footing the bill for it via the electricity rate hikes. Though there is promise for productivity boost, not everyone has been positively impacted to the same degree as programmers or white collar workers in general.

On the other hand, OpenAI, Anthropic, and Silicon Valley are complicit in making everyone believe AI will replace all workers. I’ve previously discussed how this is unlikely because of people’s talent and prowess in solving problems and specialty, knowing what to solve, and focusing on businesses’ needs to cater to smaller niches and thus will infinitely niche down so long as it’s profitable. However, I say they are complicit because they scared everyone into starting a movement stating AI is absolutely useless and horrible, and it is a political necessity to stop them.

I disagree that it’s useless. There are tons of use cases that leftist professions simply refuse to use. For example, in the reddit r/journalism community, people refuse to write articles with AI, and that’s fine because AI hasn’t achieved the same quality and context to be able to deliver stories. But to not let AI help in researching or double-checking your work is a waste given how cheap it would be. Of course, Claude Code and Claude Cowork (which replaced Harvey funnily enough; though that might not be public news yet) has positively impacted the Ivy League professions i.e. tech, consulting, and finance, making juniors start performing senior level responsibilities sooner.

Additionally, the negativity towards AI is literally counterproductive. It may be possibly socialist to stop innovating because of slight damage to the fabric of society, i.e. electricity bill increases and a partial loss of jobs, but to completely stop development is insane to me. I personally have the belief that everyone needs to continuously innovate in several fronts, regardless of industry though in particular engineering, because of the need to build competitive valuable products. Making people more productive through AI will certainly make some people lose jobs, regardless of the degree of specialization and experience, but those people can be put to use in other places where software engineers used to be too high of a cost.

I want to add on to the point of “there is no such thing as low-energy rich country” because the current AI build out and race with China can be said the same. If your nation isn’t figuring out how to be productive, whether through increasing the supply of electricity or figuring out AI tooling (whether through model providers or AI SaaS tooling), then your country will be left behind in our tight, global economy.

Firstly, electricity increases productivity because energy itself can be put into machinery that assists us in doing stuff. Whether that be large machines or things that help us indirectly like A/C, electricity is just energy that’s mass-produced to replace the biological limits of humans’ energy.

Secondly, on Reddit and I assume a lot of leftists (who are mad about AI overlords and their potential to replace all jobs, unfounded issues with water consumption) and conservatives (who are mad about electricity prices, noise from a data center just like wind turbines), there is large backlash against AI datacenter construction. Yet, just like building out a higher supply of electricity led to increased productivity, AI (at least within the software, engineering, and creative industry) has been a huge productivity boost.

I can understand the angst of those who believe AI companies will completely replace all jobs. But for those who don’t believe AI will replace most jobs which I think is the majority of the population (including me) and not Silicon Valley itself, AI should be cherished for helping to bring in more productivity boost with the slight, in my opinion, short-term issue of skyrocketing electricity bills.

The one thing one strain of people are worried about is AI companies ruling the world. There are two sides to this. The first is Silicon Valley believing in the “singularity” or the “permanent underclass” which means now is the time to earn a lot before AI makes things so cheap you’ll never be able to make a ton of money ever again as people will be automated away. I disagree with this. I’ve detailed many articles about what makes a business valuable and moat comes from the cultivation of customer loyalty, quality of service, and business partnerships. For software engineers, that is embedded in the code. Code is cheap, but the context for needing valuable code is built in parallel with a growing business. On the other hand, there’s the proper reaction from leftist advocates who believe AI companies will rule the world.

Though it’s never fully understood, the fear succinctly put is what if a frontier lab builds up a fortune of liquid assets to invest and start building in every industry and outcompeting, possibly through cutthroat tactics, that destroy competition. I’ve mentioned before that PE firms can do some tactics like conglomerating industry players and then squeezing out competitors then raising prices like a monopoly. And OpenAI or Google could technically do that. Yet, as we’ve seen, the motivation of founders and the ability of smaller businesses to niche and cater to audiences have shown why business perseveres in beating large companies. If there is lots of money to be made, someone will come along to try and replicate it until the profit margins thin out.

I advocated and even foresaw OpenAI’s doom (as of August, OpenAI’s revenue slowed significantly compared to Anthropic) when they tried to build into consumer and not B2B. Sam Altman is a classic 20-year-old YC founder who tried to do a lot of consumer instead of chasing the big B2B money. Then Anthropic ate its lunch. I mean it’s fairly intuitive: B2B was always going to have more money to pay for things compared to consumers. No code solutions never take off because creation requires users to hurdle the activation energy to actually do so, which most people don’t have. Finally, even B2B services don’t build in-house solutions all the time; they still purchase vendors and require their expertise in product design and talent into considering solutions. SaaS startups are like consultancies. I’ve mentioned before that ERPs are one of the best, weirdest conglomerate-esque businesses in that the software is built on decades of experience and talent fielding multiple enterprise customers. That talent and wisdom then goes into the product such that the next customer of the ERP can take advantage of wisdom from previous customers of the ERP. And ERPs are expensive to maintain, let alone build. OpenAI barely got started; they could’ve become the next Microsoft building tons of random B2B applications to increase revenue. It may have been marginal, but the talent density of OpenAI and attractive legacy meant they had the ability to do so. Google tried this playbook of building a suite of B2B products, but their organization and culture doomed them. Additionally, executives at Google kept seeing that tiny businesses with decent billion dollar valuations but nothing compared to the trillion dollar valuation wasn’t worth going after. So sure Google could’ve competed in CRMs, but it wasn’t worth it to them. Microsoft on the other hand went down that route, but the research department for whatever reason stifled. So there’s a potential trade off in venturing into building random businesses that incrementally add profit. I think it’s worth doing what Microsoft did. It’s very similar to Warren Buffett’s strategy. If you can continuously build profitable businesses in a quick amount of time (assuming lots of cross-selling), then the investment payback negates the tradeoff of not being able to put money into research or large scale projects (in the case of Buffett, that would be purchasing an insurance company so that he could have a huge cash dump every beginning of a year).

Anyways, let’s say OpenAI and Anthropic spontaneously start doing the Microsoft/PE strategy, and they start dominating almost every industry, outcompeting and outpricing everyone (if they beat Uber, I’d be stunned. It’d flip my theory of business upside down because that’d have to be the craziest cross-sell to consumers or a lot of money was lost. I digress…). What then? That’s when anti-trust laws should start taking place. A large organization should not dominate every industry. Thankfully, the way business works ensures this probably won’t happen. Back to Microsoft, did you know they had Power BI and a CRM alternative compared to Tableu/Metabase and Salesforce? They actually own a large chunk of both markets, but they aren’t the dominant players. Point being, it would be pretty hard for OpenAI to outcompete every industry that has huge profits because someone is bound to do better. However, from if they do end up doing so, antitrust laws can be put into place to ensure there aren’t horrible tactics at play.

I’m particularly worried about the power and leverage of money. Huge cash piles can warp proper microeconomics, and the long term outcome of players with such an advantage can be devastating for the end consumer and innovation of an industry. However, if OpenAI simply recruited the best talent and started making the best products, I don’t think I would see an issue with that. That’s just business (so long as they also don’t start bribing Congress and have negative externalities against the populace akin to the Chaebols of South Korea). This is akin to what GE essentially became. But with more cash in the US, more risk taking, and thus more successful niche businesses, we now see GE’s downfall re their stock continuously tumbling. Maybe one could advocate splitting up the company. This is what happened with Standard Oil, AT&T, and American Tobacco Company.

So I’m not yet worried based on the inability for frontier labs, whether deliberately strategic or incompetence, will destroy businesses and tons of jobs. The only way for all those jobs would be lost is if all businesses, not just OpenAI/Google/Anthropic, found a way to replace tons of humans in the workplace, but I have faith that people won’t be replaced because we are constantly specializing, people do not like writing down things to help LLMs learn processes, and general communication and strategy is still needed between coworkers and departments.

People are still people. They constantly improve, and LLMs haven’t reached that point of knowing people whether that be the end consumer, gaining their trust or knowing what to market, or between coworkers.