Workslop Is a Purpose Problem, Not a Writing Problem

AI made the first draft almost free. That's why so much of it says nothing: the bottleneck moved from building to deciding what's worth building.

I think we have all seen the flood of AI-generated content and code pushed out lately simply because it can be produced 10x faster. You start reading a document and halfway through you realize it uses a lot of words to say absolutely nothing. I was reading a thought piece the other day that mentioned over half of office workers admit to sending "workslop" to their managers and peers. People are generating these massive documents and complex codebases without really thinking about what they are trying to say or build, mostly because the tools make it so easy to just hit a button and get a finished draft.

AI has collapsed the team needed to go from 0 to 1 across almost every discipline. It used to be that creating the first draft of a piece of software or a marketing campaign took weeks of effort, which naturally forced a certain level of planning before anyone even started working. You had to sit down and justify the resources you were about to spend, meaning the purpose was defined long before the actual building phase began. Now that the barrier to entry for creating that initial draft is almost zero, people skip the planning phase entirely.

Let's take a look at LinkedIn. You have probably noticed that posting frequency has gone up and the length of LinkedIn posts is also increasing. People are using new tools to push out written content at a rapid pace, simply because the technology makes it easy to do so. The problem is that this content is produced without anyone really understanding what sits underneath it or why it is being written in the first place. Content that is just built because now you can do it 10x faster is the same as vibe coding without knowing what it really does underneath. We end up with an output that looks complete on the surface but lacks the basic direction needed to actually share a real insight.

Because the raw generation of text and code is now instant and cheap, the build itself has become a commodity. The real bottleneck is no longer generating the output, but finding the right direction to point those generation capabilities. To put it simply, the purpose has become even more important. Teams find themselves drowning in drafts and codebases that are technically functional but completely useless because they have not taken the time to figure out what they are trying to achieve. The time saved on the initial build is entirely lost in the endless cycles of revision and confusion that follow.

Some may argue that if managers are spending hours rewriting their team's AI drafts, that is a management failure and they should just reject the workslop to make the original writer fix it. The issue is not only related to writing, I think it has more to do with AI as a whole. AI has commoditized the entire 0 to 1 build phase. If a manager simply tells an employee to rewrite a bad draft without clarifying the core intent of the project, the employee is just going to generate a different version of the same purposeless workslop. The failure is not in the editing process, it is in the lack of alignment before the first prompt was ever written.

Has your team changed how you define project intent before starting an AI build? How do you ensure output is driven by purpose rather than raw generation speed? Let me know your thoughts.