The AI Labs Are Taking Something More Valuable Than Your Data

Seven articles in eight days is pushing it, even for this community. This is my last article for the week, and I’ll take a break over the weekend to let everyone catch up. Thank you for holding on during a wild ride. I deeply appreciate your support and patience.

It was necessary for my Cici series. You may have noticed that many of the articles pinged as partially AI-created with Substack’s new feature. Cici is working behind the scenes, but what it creates is imperfect. The Cici version of yesterday’s article was less than half the size of the finished product. Other articles suffered from pervasive LLM-speak.

While Cici reduces the time required, there is still a significant amount of time required to create each article. Why am I writing so much here? As I mentioned in my last article, I have a business problem. My reach on LinkedIn has dropped, and course sales have come down with it.

I need a new workflow to offset the lost revenue. The best-performing content channel is now Substack, but that new workflow (creating articles vs short-form LinkedIn posts) is more time-consuming. If it weren’t for Cici, the new workflow would be infeasible. This is the way we must position every agent in the enterprise because it aligns technology with value creation and revenue generation.

We need obvious and significant value, especially if we are early in the maturity journey and most parts of the business are still skeptical or unwilling to transform. This is how we build a track record of success, narrative, and the coalitions that can move a business.

This is a good example of the AI Last Mile Problem.

The comment is 80% good, but the 20% bad creates significant loss in a production environment. First, it is obviously AI-generated, which immediately damages the poster’s perception with readers. Second, it is the kind of ‘right’ that LLMs are known for. In another context, this would be an extremely relevant point to raise.

In this context, it makes the poster appear technically inept. The taxonomy describes document formats. Automating document change tracking and formatting updates is a solved problem, especially in finance and construction domains. That last 20% can damage the reputation these comments are meant to enhance.

Content-to-cash is a long-chain workflow that starts with content, and AI generating content is synonymous with slop. The first problem I need to solve is getting my agent to create content that sounds like me, or I’ll sound like the commenter above and incur the same losses. My audience here is far less forgiving than the average LinkedIn user.

I detailed an approach in a prior article that works fairly well in terms of writing style. It gets 80% right, but the problem is that the content it writes still sounds like an LLM wrote it. It is much better, but not quite right. How do we get the other 20%? The AI Last Mile Problem shows that getting the last 20% is harder than getting the first 80%, which is why AI and agents demo so well, then fail to reach production.

Again, we see that business architecture informs, optimizes, or constrains our agentic architecture.

The LLM needs more granular instructions. I can keep feeding articles into the model and build increasingly granular style guides, but if 700 articles isn’t enough… How many more articles do I need to write? Luckily, there’s another way to approach this challenge.