There is a whole business segment out there of people making money writing blogs. Either they earn money directly from ads, affiliate links, subscriptions or donations, or they grow the blog to a certain viewership and then sell it to someone who needs a platform to promote their product. There are marketplaces for this like Flippa and Motion Invest, to name two, and Youtube channels like Income School to teach you how to do it. And albeit the multiples for selling such a blog are relatively low at around 2-3, if you can grow the blog fast enough and maybe do more than one at a time, it’s still a profitable business.

At the same time, there are tens of thousands of users on Stack Overflow, answering the millions of new questions per year for free. These people are not getting paid but receive a different kind of reward: recognition. Apparently, a strong enough motivator.

A robot reading multiple blogs

But with the advent of AI and their liberal use of copyrighted material, or just plain piracy, both kinds of incentives might be threatened: If on one hand AI scrapes your content so people don´t need to visit your page to create clicks or recognize your name, and on the other hand the AI might create the kind of content you provide directly without needing your input, then why put in the time and effort to create content, especially when you depend on the ability to sell it for money? Consequently, there are various signs that content creation on Stackoverflow is dropping: 1, 2, 3, and also Blog sales are contracting.

Consequences For You And Your Company

Ok, there are less travel blogs and less answers to beginner questions on Stack Overflow: So what?

Knowledge Stagnation

Well, wether you are a worker, self-employed, or leading a company, you have to stay up to date in your field to stay relevant. This is especially true for STEM based jobs and companies, where the state of the art continuously advances. And let’s face it: our continued learning effort is based heavily on publicly available information and knowledge gained by individuals. Sure, the current state might be distilled into AI models and therefore way easier to access. But what if, for the next shiny typescript frontend, there is no one to explain in detail why the useState set method is not reflecting a change immediately? Are we really relying on the AI being that good by then to answer the question for us? Maybe doing the research into a rare bug on a weird browser config itself?

The danger is that after a short period of fast knowledge gain, there may be a stagnation due to the unwillingness of individuals to “work towards an AI”, which is what writing blogs or Stack Overflow answers will be.

Loss Of Value Generation

Some way, every worker and company is providing value using a set of skills that they acquired over a longer period of time. The more skillful, the more you can set yourself apart from the competition. At some point the question might arise: is there actually more knowledge and problem solving ability in an AI than in a worker or company, especially if you are just starting out in a job and the knowledge base you are relying on is stagnating? If so, why would a customer not just take the AI that is happy to work 24/7 on any project you might not, at least with good conscience? This might not be a sudden “you are all fired” event but rather a “we are not hiring” type of decline.

Widening The Moat

Warren Buffet only invests in business that have what he calls: “A wide moat”. A competitive advantage that allows the business to keep pricing power. In the postulated world of stagnating public knowledge and the threat of replacement through AI, how could such a moat look like?

Closed Source Research

In the STEM field, individuals and companies may need to rethink how they approach knowledge sharing. Historically, open collaboration and public sharing of research have driven innovation, but with AI rapidly consuming and replicating publicly available information, the incentive to share openly may diminish. For individuals, this could mean focusing on developing unique, specialized skills or proprietary knowledge that cannot be easily replicated by AI. For companies, this requires a continued and intensified effort into in-house research, not necessarily groundbreaking one, but they need knowledge distinct enough to make it valuable, complex enough to not be provided by AI and secret enough to make someone pay for it.

AI Assisted Knowledge Base

The knowledge gained from the previous step has to be easily accessible to every employee that needs it. Try to incorporate an AI powered knowledge tool and make it a habit to document any gained knowledge in a way that the AI can pick up on. A wiki with retrieval augmented generation and AI based search or a document management system like paperless ngx with AI plugin might do the trick. This way you could not only find the data that you need, but the answer for your question that lies within the data.

Keeping It a Secret

This might seem obvious from the above used term “closed source research”, but comes with several facets: when the knowledge you or your company holds becomes valuable, how do you keep it within your company? What about employees leaving the company? Should every employee have access to every information? Is your IT security good enough to prevent a competitor from scraping our AI assistant? What if your employer or customer wants access to the AI making up your valuable skillset?

All this might take considerable effort and has to be paid by the customer. Is this economically viable?

Signature Products

And finally, why should you hand out any kind of knowledge at all, when you can just provide it as a service and bill the customer monthly? Having a signature product is an asset even for service based companies or the self-employed. If placed correctly in the market, the name of the product alone is a competitive advantage that a reverse engineered solution or AI generated replacement cannot provide. Or to put it differently: “No one gets fired for buying IBM”. But you do get fired if your self-made AI copy of an IBM product fails.

“Do not go gentle into that good night”

While AI is posing a threat to the current human value generation, there are things we can at least try to combat the loss of our significance in the face of the AI overlords. If we get lucky we might even form a clear distinction between our services and a run-of-the-mill AI prompt that translates to excellent and sustainable profits.