Artificial intelligence is making it easier for employees to produce emails, documents and code at unprecedented speed. But Shopify CEO Tobias Lütke says that productivity gains can come with a less obvious cost: workers are increasingly passing AI-generated material to colleagues without taking responsibility for whether it is useful, accurate, or worth reading.
Lütke described the phenomenon as “slop grenades,” referring to low-value AI-generated work that employees produce quickly and then effectively throw at someone else to process.
“We call those ‘slop grenades’ that people toss at each other,” Lütke said during an interview on “The Knowledge Project” podcast released Tuesday. “And that’s definitely a bad thing.”
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The problem is not necessarily that AI-generated content is inaccurate. Rather, Lütke argues that generative AI has dramatically reduced the cost of producing information without creating a corresponding incentive for employees to determine whether that information deserves to be produced in the first place.
That can turn AI from a productivity tool into a mechanism for transferring work from one employee to another.
An employee, for example, might use an AI model to generate an unnecessarily long email and send it to a colleague. The recipient then uses another large language model to summarize the message simply to determine what the original sender was trying to communicate.
“Why did we invent decompression and recompression?” Lütke said. “This is terrible.”
The example captures a growing tension around AI adoption in the workplace. Companies are measuring how quickly employees can generate code, text, analysis, and other outputs, but the quantity of material produced is not necessarily equivalent to productivity.
If AI allows one worker to generate five times as much material but forces other employees to spend more time filtering, checking, and interpreting it, some of the apparent productivity gain can simply be displaced elsewhere in the organization.
Lütke’s criticism comes from an executive who has been unusually aggressive about incorporating AI into the workplace.
Shopify has rolled out AI tools for agents, while the company also uses an internal agent called River. Lütke said River handles a large share of Shopify’s production code pull requests, potentially as much as half.
That makes his distinction between useful AI and low-value AI particularly important. He is not arguing that companies should produce less work simply because it was generated with AI. Instead, he sees the greatest value in systems that improve the quality of human judgment rather than simply increasing the volume of material moving through an organization.
AI can make it easier to draft a proposal, analyze information, or write software. But someone still has to decide whether the result solves the intended problem, whether its claims are correct, and whether it should be sent to another person.
Lütke said AI is most valuable when it makes people’s thinking “clearer and more concise.” Its value falls when it simply adds more material to a colleague’s workload. That is becoming an issue as companies move from experimenting with chatbots toward deploying AI agents capable of producing work with limited human intervention.
The first wave of workplace AI was largely about helping individual employees complete tasks faster. The next phase is likely to involve AI systems producing and routing work across entire organizations. That could magnify both the benefits and the costs.
A useful AI agent can remove repetitive work, identify relevant information, and help an employee make a better decision. An indiscriminate one can create a stream of drafts, notifications, code changes and reports that someone else must review.
The resulting problem is less about whether AI can generate content and more about who remains accountable for the output.
“Humans take responsibility,” Lütke said. “Machines can help us take more responsibility because they can inform us better.”
That principle challenges one of the simplest assumptions behind corporate AI adoption: that more output automatically means more productivity.
For companies, the harder task may be designing workflows in which AI-generated work has a clear owner and a clear purpose. Without that discipline, the technology can reduce the cost of producing information while increasing the cost of consuming it.
In that sense, the “slop grenade” problem is not really a limitation of AI’s ability to generate content. It is a management problem created by giving employees an extremely cheap way to generate more work than their colleagues need. The companies that extract the most value from AI may therefore be those that measure not only how much their employees can produce with the technology, but also how much unnecessary work it prevents from reaching everyone else.