David Monnerat

Dad. Husband. Product + AI. Generalist. Endlessly Curious.

Author: dave

  • In Defense of One-on-Ones

    In Defense of One-on-Ones

    Earlier this week, a former colleague forwarded me a video of Airbnb CEO Brian Chesky in an interview with Fortune saying he doesn’t believe in one-on-one meetings.

    The full context might reveal nuances specific to certain managerial levels. For example, he could have been referring to CEOs having one-on-ones with the rest of the C-suite who report to them. However, most of his references were to “employees,” and most of the comments on the video seem to generalize across all one-on-ones. Based on the video and related commentary, there appears to be growing skepticism about the value of one-on-ones.

    I’ve worked for bosses who didn’t see the value in one-on-ones, and I’ve worked for bosses who would use them to drive their agenda. When managers ignore or misuse one-on-ones, employees feel undervalued, disconnected, and unsupported.

    I’ve also been fortunate to work for bosses who modeled what a one-on-one should be. When managers prioritize regular one-on-ones, employees feel heard, supported, and valued. This fosters trust, alignment, and engagement, benefiting both the employee and the organization.

    Based on my experience, getting rid of one-on-ones is a terrible idea. (However, I favor getting rid of bad one-on-ones.)

    A few comments from the video highlighted misconceptions about one-on-ones or are signals of a bad one-on-one.

    “The employee owns the agenda. And what happens is they often don’t talk about the things you want to talk about.”

    One-on-ones are more than just about the agenda — they’re about building trust, understanding what motivates your team, and catching minor issues before they become big problems. Even if the employee’s agenda doesn’t directly overlap with your immediate goals, it gives you insight into what they’re thinking and feeling, which can help you guide them more effectively.

    That said, there are ways to make the meeting productive for both sides. The beauty of one-on-ones is that they’re a two-way conversation. While employees should have space to bring up what’s important to them, the manager also has an opportunity to steer the conversation toward topics they find valuable. It doesn’t have to be one or the other — it can be a balance.

    One way to address this is by co-creating the agenda. Before each meeting, you could ask the employee to suggest a couple of items they want to discuss, and you can add one or two topics that align with what you want to address. That way, both sides feel heard, and the meeting stays focused.

    In the spirit of the statement in the video, resist the temptation to control the full agenda. Remember, the one-on-one should be about the employee…not everything needs to be about you.

    “You become their therapist” and “They’re bringing you problems but often times they’re bringing you problems that you want other people in the room to hear. In other words, there’s very few times an employee should come to you one-on-one without other people.”

    One aspect of this comment I agree with is that some conversations are more appropriate in a team setting. Employees sometimes talk about their work or the project status they should bring up with the full team, such as surfacing a new issue. The nod to Jensen Huang’s quote, “I don’t do one-on-ones because I want everyone to be part of the solution and get the wisdom” is appropriate.

    But often, employees bring these topics up because they think that’s what their manager wants to hear. After all, that’s the only thing their manager asks about in one-on-ones.

    Sometimes, an employee, especially a junior one, doesn’t know how to bring a difficult topic up to the team. As a leader, those present opportunities to coach them and help shape how to bring those items to the team in a way that supports your organization’s culture.

    Finally, if an employee is bringing you items that are genuinely more appropriate for a therapist, you, as a leader, should set those boundaries and guide them to a more appropriate forum. However, don’t dismiss these topics when they relate to workplace well-being…the employee may be asking for accommodations, not solutions.

    “If they’re concerned about something, if they’re having a difficult time in their personal life, if they want to confide in something; they don’t feel safe telling a group. But that should be infrequent.”

    As I mentioned above, if the employee brings challenges in their personal life, look for opportunities to provide accommodations, not solutions. If the employee expects more and you are not willing, capable, or permitted to engage further, guide them to appropriate resources.

    But if they don’t feel safe bringing a topic to a group, coming to you is a gift. It’s a sign that your team has a perceived lack of safety or a potentially unhealthy dynamic that needs to be addressed.

    Also, while these items should be infrequent, this is not an exhaustive list of topics appropriate for a one-on-one conversation. Career development, goals, feedback, and recognition should be regular topics, too.

    Even with the expanded list of potential topics, there’s also no requirement that one-on-ones be weekly. It’s less about the frequency and more about the regularity and building a strong, trusting relationship that empowers the employee to thrive.

    A final note on bad one-on-ones…

    One of my first managers to schedule one-on-ones (probably from a corporate directive) said, “We’re going to have one-on-ones. Send me an agenda beforehand.”

    “Send me an agenda” is ambiguous and intimidating, especially for junior employees. I had no other context, no list of suggested topics, and no idea what I was doing. I would send a status-focused agenda because that’s all I knew. I don’t think either of us got much out of those meetings.

    Eventually, I reported to a different manager who also scheduled regular one-on-ones. When I sent the agenda, my manager stopped by to apologize for assuming that I understood the purpose of the meeting. They helped me move from a status-focused agenda to one that balanced my work, career, and where I needed help. I felt seen and supported, and that showed up in my work.

    While both the employee and the manager can be responsible for bad one-on-one meetings, the balance of responsibility skews toward the manager because they hold the leadership role and set the tone for the meetings.

    As a leader, take the responsibility and focus it on what is best for your employees and organization.

    Don’t abolish one-on-ones.

    Make them better.

  • The Humanity In Artificial Intelligence

    The Humanity In Artificial Intelligence

    I wrote this essay in 2017. When I restarted the blog, I removed the posts that had already been published. But after reading this one, while the technology has advanced significantly since then, the sentiment still applies today.

    Dave, January 2025


    Algorithms, artificial intelligence, and machine learning are not new concepts. But they are finding new applications. Wherever there is data, engineers are building systems to make sense of that data. Wherever there is an opportunity for a machine to make a decision, engineers are building it. It could be for simple, low-risk decisions to free up a human to make a more complicated decision. Or it could be because there is too much data for a human to decide. Data-driven algorithms are making more decisions in many areas of our lives.

    Algorithms already decide what search results we see. They determine our driving routes or assign us the closest Lyft, and soon, they will enable self-driving cars and other autonomous vehicles. They’re matching job candidates with applicants. They recommend the next movie you should watch or the product you should buy. They’re figuring out which houses to show you and whether you can pay the mortgage. The more data we feed them, the more they learn about us, and they are getting better at judging our mood and intention to predict our behavior.

    I’ve been thinking a lot about these systems lately. My son has epilepsy, and I’m working on a project to gauge the sentiment towards epilepsy on social media. I’m scraping epilepsy-related tweets from Twitter and feeding them to a sentiment analyzer. The system calculates a score representing whether an opinion is positive, negative, or neutral.

    Companies already use sentiment analysis to understand their customers’ relationships. They analyze reviews and social media mentions to measure the effectiveness of an ad. They can inspect negative comments and find ways to improve a product. They can also see when a public relations incident turns against them.

    For the epilepsy project, my initial goal was to track sentiment over time. I wanted to see why people were using Twitter to discuss epilepsy. Were they sharing positive stories, or were they sharing hardships and challenges? I also wanted to know whether people responded more to positive or negative tweets.

    While the potential is there, the technology may not be quite ready. These systems aren’t perfect, and context and the complexities of human expression can confuse even humans. While “I [expletive] love epilepsy” may seem to an immature algorithm to express a positive sentiment, the effectiveness of any system built on top of them is limited by these algorithms themselves.

    I considered this as I compared two sentiment analyzers. They gave me different answers for tweets that expressed a negative sentiment. Of course, which was “right” could be subjective, but most reasonable people would have agreed that the tone of the text was negative.

    Like a child, a system sometimes gets a wrong answer because it hasn’t learned enough to know the right one. This was likely the case in my example. The answer given was likely due to limitations in the algorithm. Still, imagine if I built my system to predict the mood of a patient using an immature algorithm. When the foundation is wrong, the house will crumble.

    But, also like a child, sometimes they give an answer because a parent taught them that answer. Whether through explicit coding choices or biased data sets, systems can “learn wrong”. After all, people created these systems—people, with their logic and ingenuity, but also their biases and flaws. A human told it that an answer was right or wrong. A human with a viewpoint. Or a human with an agenda.

    We create these systems with branches of code and then teach them which branch to follow. We let them learn and show enough proficiency, and then we trust them to keep getting better. We create new systems and give them more responsibility. But somewhere, back in the beginning, a fallible human wrote that first line of code. It is impossible for those actions not to influence every outcome.

    These systems will continue to be pervasive, reaching into new areas of our lives. We’ll continue to depend on and trust them because they make our lives easier. And because they get it right most of the time. The danger is assuming they always get it right and not questioning an answer the feels wrong. “The machine gave me the answer, so it must be true” is a dangerous statement, now more than ever.

    We dehumanize these programs once they encounter the cold metal box in which they run. However, they are extensions of our humanity, and it’s important to remember their human origins.