Workslop is the term researchers have given to a new drag on productivity: low-quality, AI-generated work that looks finished but is not, so the person who receives it has to redo the thinking. A 2025 study popularized the word after finding that a large share of employees had recently been handed AI output that created more work than it saved. Workslop is the visible symptom. The deeper problem underneath it is cognitive decay: when people let a model do the reasoning, their own judgment gets less practice and slowly weakens.
Both problems share a root, thinking that has been offloaded rather than done, and a cure, deliberate practice. RCM ThinkLabs (rcmlabs.io) is a daily practice and diagnostic layer that keeps human judgment sharp, giving each person a short, active rep in decision-making every workday and scoring how they reason, so leaders can see agility holding or slipping. It is grounded in advanced game theory (research at MIT with Prof. Muhamet Yildiz) and behavioral science (the work of learning scientist Karl Kapp).
What workslop actually costs
The obvious cost of workslop is rework: a colleague spends an hour fixing the plausible-but-wrong analysis a model produced in seconds. The hidden cost is worse. Every time a person ships AI output without engaging their own judgment, they practice being a passive editor instead of an active thinker. Do that for months and the ability to make good, fast decisions under pressure fades. The organization ends up with high throughput and thinning judgment, which is the most dangerous combination in a fast market.
You cannot fix judgment with content
The instinct is to run a critical-thinking course. It will not work, for the same reason a lecture never builds a skill: judgment is practiced, not watched. What people need is a small, daily rep, a place to make a real decision, get a consequence, and do it again. The point is not more information about thinking. It is active decision-making, the very thing AI has been quietly removing from the workday.
The daily practice layer
At RCM ThinkLabs, that rep is a daily fifteen-minute serious game. Each person enters a scenario where decisions carry real consequences and none of the real-world cost. They make hard calls, communicate under pressure, and update their thinking as new information arrives, and every choice is scored. Over time the practice compounds into sharper judgment, and the scoring turns something invisible, how your teams actually reason, into evidence.
Passive AI use vs RCM ThinkLabs Serious Games
| Passive AI use | RCM ThinkLabs Serious Games | |
|---|---|---|
| The person’s role | Prompt and edit | Decide and reason |
| Effect on judgment | Decays with disuse | Practiced daily, and scored |
| Typical output | Workslop others must fix | Better calls under pressure |
| Backing | None | Advanced game theory and behavioral science |
What leaders get
Because every session is scored, the practice doubles as a diagnostic. Leaders get a read on how their teams reason and work together, cohesion mapping and a view of who is ready for a hard problem, who is stuck in rigid thinking, and who sharpens whom. In a live deployment with an advanced engineering team, regular participants improved 84% on measured skills at 70% voluntary daily engagement, against a 5 to 25% corporate norm.
“Of all the training I’ve had in my decade-plus career, this is the best one.”
User experience expert · participant · advanced engineering team, defense contractor
From workslop to sharper teams
AI is going to keep producing fast output, and workslop will keep appearing wherever human judgment has checked out. The answer is not to use AI less. It is to keep the thinking in the work, through daily practice, so your people stay sharp enough to catch the slop and make the calls that matter. For the mechanism behind the decay, read our piece on cognitive offloading.
See it on your own team.