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“We’re at-will. Just let them go.”
Leaders in the U.S. say these words, or something like them, with regularity. Because employment here is generally “at-will,” many assume they can terminate someone for any reason. But that misunderstands what at-will employment means—and what else is at play.
An employment decision doesn’t end when someone walks out the door. Even in at-will employment, every termination is judged in three courts: the court of law, the court of social media, and the court of public opinion. Each one can impact your business more than you realize.
The court of law
Despite what many people believe, at-will is not a magical shield against any legal liability. It doesn’t override other applicable laws, including those prohibiting discrimination, retaliation, or violations of whistleblower protections.
Most employees who leave an organization, even if they were fired, don’t sue their employer. But when they do, and if it gets to a trial, the question often isn’t whether the employer had the right to terminate them. It’s why they did.
Just ask the Society for Human Resource Management, the world’s largest HR association. In December 2025, a federal jury found SHRM liable for race discrimination and retaliation against a former employee. SHRM maintained that it followed appropriate procedures, even after the employee raised concerns of racial discrimination during her employment. But testimony and evidence at trial showed that the same individual who was responsible for investigating the employee’s complaints was also advising leaders on communications with her behind the scenes, and the employee’s termination paperwork had been drafted the same day she reported retaliation.
The jury awarded her $11.5 million. And the costs didn’t stop there.
In addition to the jury’s award and its own legal expenses, just this month, SHRM was ordered to pay more than $534,000 in attorneys’ fees for the plaintiff. Much like at-will employment, many leaders assume insurance covers everything. But SHRM’s insurer has sued to avoid paying $10 million of the verdict.
SHRM is appealing the decision. But regardless of the final outcome, it’s a reminder that employment decisions can carry significant costs in money, time, and reputation.
If it can happen to the organization that describes itself as “the global authority on work, workers, and the workplace,” it can happen to any employer.
The court of social media
Unlike a courtroom, social media doesn’t have rules of evidence or filing deadlines. There are headlines, screenshots, recordings, and sections that can shape public opinion in hours.
For many employees, a lawsuit feels intimidating and costly. Posting online does not. It feels—and is—accessible. A recorded layoff call, a screenshot of a termination email, or a “Day in the Life of Getting Fired from My Corporate Job” TikTok can reach more people in an hour than your organization reaches on LinkedIn all year.
By the time leaders start asking whether a recording is legal, it’s too late. People have made their conclusions, and continue to do so when you respond. While your lawyer may advise, “We don’t comment on personnel matters,” the public isn’t judging your legal defense. They’re evaluating whether your response reflects the values your organization claims to stand for.
After SHRM’s verdict, its CEO called it “just a blip in the history of SHRM.” That one word, “blip,” made headlines on its own.
Because in the court of social media, perception often shapes reality.
The court of public opinion
This court may have the smallest reach, but the longest memory.
One thing I learned as an employment lawyer and HR leader is that every employee is a walking billboard for your organization. People talk—to former colleagues, to friends, and to candidates, directly and on Glassdoor. And those people pay attention to what’s said, especially when a situation feels unfair.
The story spreads through their personal and professional communities. And there’s no formal appeal process in this court. Just your reputation is decided, one conversation at a time.
Use the 3-court test
None of this means that you can’t let someone go. You can, and sometimes that’s the best path, for your business and even that person. But it means that an employment decision—especially a termination—should be one that you’re comfortable defending in all three courts. Before you move forward, pause and ask:
- Would it hold up in court? Look at the record: Did this person recently complain or take protected leave? Look at consistency: Are there others who’ve performed the same, or worse, and what happened to them? If a performance review says “Exceeds Expectations” but the termination notice says “Poor Performance,” that inconsistency won’t just concern the employee. It can raise real questions for a jury as well.
- Would it survive a headline? Explain the decision in one sentence, as if someone who’s a complete stranger to your organization would read it. The decisions that are hardest to explain can be the ones most likely to go viral.
- What will the team think? Not what an official statement says—what others will actually believe. Especially if the person leaving was a respected or vocal team member.
When you have doubts in any of these three areas, slow down and take a closer look.
When HR or Legal raises concerns, they’re usually not trying to create delays. They’re helping ensure the organization follows a process that is fair, defensible, and consistent.
The difference can be significant: between a fair process and Exhibit A.
A few extra days spent asking hard questions may prevent years of litigation, reputational damage, or rebuilding trust. Because at-will tells you what you’re allowed to do. It doesn’t tell you what you should do.
So, the next time someone in the room says, “We’re at-will,” ask the follow-up: “But would we win in all three courts?”
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In 2004, Jeff Bezos banned PowerPoint from Amazon’s senior leadership meetings in favor of narrative memos, read in silence at the start of each meeting. The idea was that a well-structured and tightly argued memo communicated its ideas in a way that a deck built around bullet points could not. As Amazon moves into the AI era, it is developing internal tools that can help produce polished documents much more efficiently. Its internal AI assistant, Cedric, promises to deliver “six-page narratives in seconds,” according to Kristi Coulter, a former Amazon executive.
But no matter how good Cedric’s outputs are, using an AI tool to trim the traditional writing process down to mere seconds undercuts what made well-written memos valuable in the first place. The memo itself was never the point. What mattered was what writing the memo forced the human to do. As Bezos put it, there is “no way to write a six-page, narratively structured memo and not have clear thinking.” The process, not the output, was the real source of value.
How AI breaks the memo
Bezos wasn’t promoting writing for its own sake. Writing mattered to him because it was a forcing function for rigorous thinking about important decisions. As one Amazon veteran told Coulter, writing the memo forced them to confront their own ideas and clarify what they wanted to say. And this often meant that writers would change their mind several times while writing the narrative.
It is true that building meetings around memos disciplined the readers as well. Because meetings began in silence, everyone worked through the same argument before anyone spoke, and the discussion started from the substance. But if the content of a memo carries less of the writer’s thought, the value of reading it diminishes in proportion to that fall. Time spent studiously reading well-written but empty texts is time wasted.
The underlying problem is that AI can break the link between thinking and the production of text. Steve Huynh, a former Amazon principal engineer, recently described a review meeting in which a product manager began discussing a six-page memo he was supposed to have written. Almost immediately, it became clear that he was reading it for the first time. He was presenting something that he had not thought about at all.
Readers are adapting to the change in the writing process. Coulter reports that one Amazon manager now asks for longer documents because he plans to have AI summarize them, and Huynh says some employees now tag suspect memos “AI;DR”: AI, didn’t read. In a Stanford and BetterUp Labs survey on workslop, 42% of workers who had received low-effort AI-generated work said they saw the sender as less trustworthy. Once a written product stops being evidence that someone thought about the content, readers simply stop giving it their attention.
The memo’s 3 jobs
The trap for leaders is to treat this as a problem about memos. Ultimately, businesses don’t need memos. They need good decisions. The memo mattered only because, for a long time, it reliably communicated the results of the thinking process that lay behind the writing.
Baseball provides a useful analogy here. In his book Moneyball, Michael Lewis tells the story of how the Oakland A’s responded to the loss of a star player, Jason Giambi, to free agency. Instead of trying to replace him with another player of the same caliber, the A’s realized they didn’t need another Giambi, per se. What they needed was the measurable impact he had on their results. So rather than search for one player to fill the gap, they tried to recreate him “in the aggregate” by finding several cheaper players who together delivered the same statistical impact.
There is a lesson here for how we think about Amazon’s memos—and, indeed, for how we think of much else in the new AI-powered workplace. We shouldn’t be looking for simple substitutions of AI work for human work. Instead, we should look at how work produces value in aggregate and then redesign workflows to reproduce the end result, not the individual steps.
A well-written memo bundles three distinct jobs into one artifact. It forces authors to think, it provides evidence that the author has done the thinking, and it gives its readers a shared understanding of the issue at hand. What the Oakland A’s can teach us is that, rather than trying to restore all of those functions in one stroke, the better path is to make two distinct moves: one that restores the first two jobs together, and one for the third.
Force the thinking, then prove it
The rebuilding process starts with honesty about where thinking is actually needed. A great deal of human writing does not provide the basis for making important decisions, so in those cases there is little reason to build a replacement process that forces the thinking and evidential functions alongside the communicative role of the writing. A report summing up project progress over the past week, for instance, can simply be an assemblage of information, and the process of collating and communicating it can happily be automated. But when it comes to visions of the future or arguments about which decisions are best, leaders have to adapt to the fact that polished prose no longer guarantees deep thinking.
The first move is to both rebuild the forcing function and provide evidence of the underlying thinking. This can be done by making the author, rather than the document, the thing that gets examined. Amazon’s meetings already included the seed of this requirement. Once the silent reading ended, the writer had to answer for every line. The change for the AI era is that the defense becomes the initial gate. A memo earns its place on the agenda only if its author can walk the room through the argument and take questions without the document in front of them. That is not something the author can hand to Cedric, because Cedric will not be in the room, and knowing the defense is coming does what the blank page used to do.
Terence Tao, the Fields medalist, has proposed the same rule for mathematicians: If the authors of an AI-assisted result cannot give a clear, expert-level talk on it, the result should not be published. A proof that no human can properly explain, he writes, “should be viewed as incomplete, even if it has been formally verified.” The same holds for a memo.
Who does the understanding?
The memo’s third job, helping create shared understanding, seems the least problematic, but it raises a counterintuitive challenge. We tend to think that AI-written texts are problematic because they waste our time by spreading poorly thought-out ideas. Restoring the underlying thinking should, then, automatically solve the communication problem as well. But things are not quite so clear cut. Even when the content is genuinely good, AI can help humans produce more valuable outputs than other humans can absorb.
We can see this in the challenges that the discipline of mathematics is facing. Mathematicians are being overrun by journal articles and preprints containing AI-generated proofs that nobody can properly digest. In September, OpenAI said its models had solved one of math’s Millennium Prize problems. A month later, it released hundreds of AI-generated results in one batch. Many of the proofs have been verified by software that checks their logic, but knowing that a result is correct is not the same as understanding why it is. The Association for Human Mathematics put it bluntly in a statement reposted by Tao: “We reject OpenAI’s assertion that this release advances our subject.”
Pavel Etingof, a mathematician at MIT, argues that AI’s results truly become part of mathematics only when a human reads them, understands them, and gets something out of them. A thousand new proofs sitting unread on a shelf add nothing to the discipline. The same logic holds for companies grappling with a surfeit of good writing outputs; no matter how intelligent a memo is, it becomes a part of a company’s decision-making only if the relevant humans absorb it. That points to a new division of labor: AI can increasingly shoulder the generative burden, but the understanding still has to be done by people.
That makes human understanding a scarce and valuable resource, and leaders may have to start rationing it. Working out how to filter and direct the flow of outputs becomes an entirely new type of task. The preprint server arXiv, for scientific papers, now limits authors to two submissions a month. A company can do something similar, such as limiting the number of memos that get a silent-reading slot in a given month.
The artifact is not the thinking
For two decades, a six-page memo was reasonable evidence that someone had thought hard. AI has broken that link, and no policy will fully restore it. What leaders can do is stop mistaking the document for what it was meant to produce. The alternative is more six-pagers than ever, and fewer people who understand what’s in them.
