Don’t let AI slop grenades blow up your business | Stephen’s Hill
Field notes for marketing and revenue operations leaders

Don’t let AI slop grenades blow up your business

See how smart humans use simple governance rules to avoid Shopify’s AI slop grenade problem

TL;DR

  • Shopify CEO Tobias Lütke says employees are tossing slop grenades at each other: unexamined AI emails and code that colleagues then have to clean up.
  • He’s naming a real, common problem. In a survey Fortune cites, 38% of desk workers received “workslop” and said it cost them about 3.4 hours a month to fix.
  • Researchers tie workslop to unclear AI mandates and overwhelmed teams, not to lazy people.
  • Law, radiology, journalism, open source, and audit each landed on the same governance basics: a named human, a check before handoff, and disclosure.
  • Smart governance can be light: six norms any team can adopt, plus one step you can take this week.
  • Most of this evidence is policy and practice rather than outcome studies. Radiology is the exception.

You know the email. It’s long, tidy, confident — and somehow says nothing. You read it twice, then realize the real work of figuring out what it means just landed on your desk.

Shopify’s CEO has a name for it, and this week it made headlines. I think the story deserves a closer look, because the problem is real, the fix is well understood, and it isn’t what most people reach for first.

What Shopify’s CEO actually said

In a Tuesday interview on The Knowledge Project podcast, Tobias Lütke said Shopify employees are producing unexamined emails and code with AI and not taking responsibility for the output. He called these slop grenades: work that gets tossed to a colleague, who now has to review it and work out what’s wrong. His example was an email that AI should have boiled down to its key points but instead ballooned into a long missive. Fortune has the full story.

Worth remembering: last year Lütke told employees that using AI is expected of everyone, and that they should show they can’t get something done with AI before asking for more resources.

I want to be fair to him. This isn’t a leader walking away from AI. It’s a leader describing what happens when a powerful tool meets busy people who don’t share a definition of “done.” Saying it out loud is the first step, and plenty of companies haven’t taken it.

Why slop happens (and why it’s rarely laziness)

Researchers call it workslop: polished-looking AI output that lacks the substance to move a task forward, so the recipient has to do the thinking the sender skipped. The Harvard Business Review team behind the term found that it says less about careless individuals and more about the conditions leaders create: vague directives to use powerful tools, handed to teams who are overburdened and don’t feel safe saying “I’m not sure.”

Fortune’s coverage of a BetterUp Labs and Stanford survey of 962 U.S. desk workers puts a price on it. 38% received workslop and estimated it cost them 3.4 hours a month to revise. More than half said they had sent some themselves, and that was more common where organizations encouraged AI use. Read that last part twice. When “use more AI” is the only instruction, volume is the only thing anyone can show.

The professions that got here first

Other fields have already had their slop-grenade moment, and they answered it with governance, not guesswork. Here’s what they did.

Law

The American Bar Association’s Formal Opinion 512 makes lawyers responsible for AI-assisted work and calls on firms to set clear policies, train people, and supervise use. Courts have sanctioned AI-fabricated citations, with penalties ranging from small fines to fee awards above $1.5M.

Radiology

The MASAI trial, a randomized study of more than 100,000 women in Sweden, found AI-supported mammography detected 29% more cancers and cut radiologists’ reading workload by 44%. A human radiologist still did the read.

Journalism

The AP limits AI to defined tasks like research, summarization, transcription, translation, and headline suggestions. A journalist reviews and edits every AI output before publication, and disclosure is required when AI plays a material role.

Open source

The curl project ended its bug bounty after a flood of AI-generated reports. The Linux kernel took a different route: AI-assisted patches are allowed, but AI agents can’t add the sign-off. The human submitter reviews the code and owns the result.

Consulting and audit

Deloitte Australia partially refunded a government report that contained fabricated citations. In audit, regulators are explicit that accountability doesn’t move to the tool: the human auditor remains accountable.

The fix in every field was the same: a named human, a check before handoff, and a note that AI was involved. That’s the whole governance playbook, and it fits on an index card.

How much weight to put on this

Most of this evidence is policy and practice, not outcome studies. Radiology is the exception, with randomized-trial data. Treat these as sensible working rules borrowed from high-stakes fields, and measure whether they reduce rework on your own team.

Smart governance: six norms any team can adopt

Here’s the version I’d hand to a marketing, sales, or RevOps team tomorrow.

01 · Own what you send

Your name is on it, whoever or whatever drafted it. If you can’t explain or defend it, don’t send it.

02 · Verify before handoff

Review means checking, not skimming: open the sources, recompute the numbers, run the code.

03 · Disclose substantial AI drafting

One line — which tool, what you checked — tells the recipient how much scrutiny to bring. Personal notes and brainstorming don’t need one.

04 · Protect reviewers’ time

If AI made it longer than you would have written it, cut it. Keep changes small enough to review in one sitting, and lead with the ask.

05 · Protect data

Approved tools only for company and client information. Confidential or unpublished third-party material stays out of tools that aren’t cleared for it.

06 · Measure quality, not volume

Track rework, errors found after handoff, and reviewer time — not the number of documents, pull requests, or messages produced.

Where to start this week

Pick one recurring handoff — the campaign brief, the weekly pipeline report, the outbound sequence — and add one line to its template: AI used: [tool or none]. Checked: [what you verified].

That single line makes ownership visible, tells the reviewer how hard to look, and starts the conversation that matters: what would make you comfortable putting your name on this? The answers become your norms.

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