Tech Workers Split in Two: Noam Segal on Burnout, AI, and the End of the Honeymoon
Lenny's Podcast
Noam Segal has led research at Airbnb, Meta, Twitter, Zapier, Intercom, and Figma, and was Lenny Rachitsky's research partner at Airbnb about a decade ago. The two now run an annual Tech Worker Sentiment Survey, a quantitative study of how people in tech feel about their jobs, AI, layoffs, burnout, and their careers. This episode covers the second year's results. Segal's framing throughout is that the survey measures how people feel, not what is objectively happening to their roles. His headline reading of the data is that AI has become the dominant force shaping those feelings, and that it is splitting the workforce almost exactly in half.
Scope of the survey and last year's baseline
The first survey, run a year earlier, was titled "burnt out but optimistic." It found high burnout alongside fairly healthy optimism about the future. The burnout finding was concerning enough that the two published follow-up research and a framework for dealing with it, which Segal refers to as the ARMOR framework.
This year's survey drew about 6,000 respondents from product, engineering, design, research, marketing, data, sales, and other functions. Segal says he knows of no other survey of this kind at this scale. He contrasts it with the twice-yearly engagement surveys most tech employees fill out at work, which in his view rarely go deeper than rating a manager or leadership.
He also sets the results against the "AI confidence theater" described in a recent post by Elena Verna: the pattern where conversations in tech declare everything dead (engineering, design, SaaS). Segal says the survey offers a more honest picture of how people actually feel about AI than those public performances do.
The core finding: AI identity splits the workforce
The central question asked how AI has shifted respondents' professional identity, if at all. Only 3% said it hasn't shifted at all, which Segal reads as evidence that AI has changed how almost everyone sees themselves.
About 50% said they feel amplified: able to do more and do it better. Segal calls this a wholly positive response. The other half splits into three groups:
- Redefined (27%): people who know their role is fundamentally changing but have no clear positive or negative feeling about it. They simply don't understand what the change means.
- Destabilized (14%): people who feel the ground shaking beneath them, report high anxiety and little clarity, and hold pessimistic views of what's coming.
- Diminished (5%): people who feel AI has taken something away from them. Segal notes that since AI models are "the worst they'll ever be," this group will probably only feel more diminished over time.
To convey how large this effect is, Segal distinguishes statistical significance from effect size. With a big enough sample, he explains, almost anything becomes statistically significant, whether or not it matters in practice. An effect size measure such as Cohen's d shows how much a factor actually matters. Last year the two largest effects were manager effectiveness and a "founder happiness effect." Current founders were markedly happier, which Segal attributes to their agency and autonomy. This year, he reports, the effect of AI identity on the other job variables is about three times as large as either of those. He describes it as an outlier-level impact, bigger than role, company, company size, or seniority.
The identity stance lines up with every other core measure. Moving from "amplified" to "diminished," career optimism drops significantly, reported burnout rises, and layoff worry rises. Willingness to recommend one's role to someone entering the industry falls as well. Segal stresses how linear and orderly these relationships are, and says that is what convinced him of AI's influence. Lenny admits he expected a divide but was surprised it came out so close to 50/50.
Four emotional archetypes
The survey also asked respondents to select the emotions they feel about work. They could pick as many as they wanted. On average people chose five, and a few chose thirteen. Clustering these answers produced four archetypes.
The Energized (41%) say product work has become fun again. They describe feeling like they are in a "tech amusement park," free to experiment, suddenly builders with powers they never had before.
The Conflicted (35%), which Segal calls the ambivalent middle, are having the most fun of their careers as PMs, designers, or engineers while also feeling the most uncertain they have ever felt. They wonder whether they are building the things that will end their careers as they know them.
The Disoriented feel their role keeps shifting. One respondent compared people in tech to farmers on the cusp of the industrial revolution who can't see where things are going.
The Resentful (12%) feel pressured and checked out. They say things like: they've been forced to use AI or lose their job, they still see people lose their jobs even when they use it, and they hate having to lean on the technology instead of doing their own work.
Lenny's takeaway is that people on either side of the split may find it hard to picture how the other side feels, so empathy matters. Segal agrees. He argues that with the technology changing so fast, too much attention goes to mastering each new model, release, or technique ("loop engineering, whatever the next thing will be next week"). Too little goes to relationships, supporting colleagues, and collaborating with people who experience AI differently. He asks energized people in particular to spend some of that energy on the people around them instead of going all-in on the next AI development.
Burnout surges while optimism falls
Segal says he had hoped optimism would hold steady and burnout wouldn't rise, reasoning that more capable models might mean people didn't have to work as hard. The data went the other way. The share reporting significant burnout (above moderate) rose from 44.7% in 2025 to 54.7% in 2026, which means more than half the sample is now significantly burnt out. Career optimism fell from 54.8% to 48.7% over the same period. Lenny calls the ten-point jump in burnout in a single year worrisome.
Segal links this to an earlier episode with Geoff Charles of Ramp, who said his worst burnout came when velocity was lowest. That fits theories that tie burnout to stagnation, effort that goes nowhere. Segal thinks the current situation is the opposite. People are shipping faster than ever, going from a couple of PRs a day to thirty. That can be fun, but they aren't working any less. They are taking on more prototypes, PRDs, PRs, campaigns, agents, and ads, and the data suggests this is producing more burnout.
A glimmer of hope: enjoyment holds
Lenny points to one countervailing finding: job enjoyment stayed about as high as last year. Segal says respondents gave two main reasons.
First, people can express parts of their professional identity that used to be locked away. A PM with an inner designer, or a marketer who always wanted to be an engineer, can now act on that. People are "escaping our classic swim lanes," and part of each role is turning into something else. Second, people can build things that recently seemed impossible, at work or on the side, because they previously fell outside their role or felt technically infeasible.
Layoff worry and clashing emotions
72% of respondents are worried to some extent about being laid off, and 41.2% are at least moderately worried. Segal describes people feeling that by using AI they may be "cutting the branch that they're sitting on," as they watch their companies go all-in on agents.
Asked how to reconcile widespread enjoyment with rising burnout and falling optimism, Segal speaks personally. He says he has never had as much fun in his career as he has using these tools, and he spends too many hours a day playing and building with them. He calls the technology somewhat addictive and says it is hard to disengage and "touch grass." It is also tiring: constantly learning, constantly applying the tools in new contexts, constantly taking on more than a traditional role required. In his view, "there aren't any traditional roles anymore," and everyone is now a builder in practice. The technology is exciting because it is powerful, and that same power is what makes people feel it might come for their jobs. (He jokes about growing up on the Terminator films and Skynet.)
Nobody would recommend their role
Segal is known in the research community as an opponent of Net Promoter Score. He runs npsistheworst.com and even bought a domain making the opposite claim, which he redirects to his anti-NPS site. Even so, he and Lenny wanted to know whether experienced people would recommend their role and the tech industry to a friend or relative entering it today.
He explains the scale: individuals answer from 0 to 10, and the aggregate NPS ranges from −100 to +100, with zero meaning the group as a whole is neutral. The result he calls "absolutely shocking" is that no group scored as a promoter of its role. That includes founders, even though they are by far the happiest group. Sales and go-to-market, PMs, operations, and engineering all came in negative. Designers and researchers were the least likely to recommend their roles. Segal summarizes the mood as: the water in this pool is kind of okay, but you shouldn't come in.
Lenny notes the contrast with the popular narrative that there has never been a better time to be a founder, with solo and two-person companies now possible. Segal adds that willingness to recommend declines with seniority: executives, VPs, and perhaps directors are more positive than ICs. One explanation he has heard is that leaders benefit most from AI because it processes a stream of information for them. ICs, meanwhile, are each scrambling to build micro-SaaS tools inside their companies, often duplicating each other's work, with products that are easy to build but hard to maintain. He describes the IC feeling as "full gas on neutral": pedal to the metal, going nowhere, lots of building without the desired impact.
As a parent, Segal says he no longer knows what to tell his kids to study. Tech workers likewise can't tell newcomers that things will be great in five years. Lenny says this is not a result they would have seen a year or two ago.
The ladder metaphor
Segal borrows a metaphor from Lenny's earlier conversation with Scott Wu of Cognition, maker of Devin. Wu described the product climbing a ladder from high school CS student to college intern to junior engineer, and by now perhaps senior or staff level. Segal says tech workers are watching AI climb those rungs and feel it is pulling them out from under their feet. Those higher up feel more stable and better about their careers. Those lower down feel the rungs disappearing, which in his reading explains why people would not recommend getting on the ladder at all.
On which roles scored relatively better, Segal says PMs being somewhat less negative makes sense to him because PM is a generalist role, and he considers this "the era of the generalist." Sales and go-to-market surprised him most. If there really were a "SaaS apocalypse," which he personally doesn't believe, he wouldn't expect sales people to feel as positive as they do. Perhaps, he speculates, they believe sales can't be done by AI.
Speaking as a researcher, Segal says the design and research results hurt. The research community has long lived with anxiety about having a seat at the table, finding meaning, and the "democratization of research" leading to replacement. He argues that as the technology advances, teams should become more thoughtful about what they build, not less. He rejects the idea that because building is cheap, teams should build a thousand prototypes and see what works, and predicts that approach would only deepen burnout. In his framing, AI has mostly lowered the bar but hasn't raised the ceiling, and research and design are what raise it.
Both hosts stress that this is a picture of feelings, not a verdict that any function is disappearing. Lenny also highlights that when asked about their current role, most people said they are doing okay and enjoying it. Segal explains the gap as the difference between people's present experience, shaped by where they already are on the ladder, and their extrapolation of where things will be in one, three, or five years. That extrapolation is clearly more negative. "I hope we're all wrong," he says.
Faster, not better
Asked how much better AI makes them at their jobs, 97.2% said at least somewhat better. 82% said at least moderately better, and close to 50% said very much or extremely better. Segal says this was bullish at first glance, and last year's survey had also found people positive about AI improving both productivity and quality.
The open-ended explanations told a different story. Segal had assumed "better" meant higher-quality work. Instead, people described two concerns. The first was more and faster, but not better: far more PRs, PRDs, research projects, and prototypes, with no rise in quality. The second, which he calls more concerning, was a cost to thinking and judgment. Respondents said, in effect, "my brain is rotting, my work feels worse." Segal connects this to what he has heard called cognitive rot: accepting a model's first output without applying judgment, and letting one's agency in the work slowly collapse.
Lenny sees some positives here. People feel more capable, and they are self-aware about quality and skill atrophy rather than claiming everything is better. Segal, drawing on his training as a coach, says awareness isn't enough; people need to act. One explanation he offers for the shift is that "the honeymoon period with AI is over." People thought it was perfect, then realized that despite constant improvement, models aren't yet good enough to make their work straightforwardly better without their involvement. He cites Simon Willison's comments on the show about resisting skill atrophy and says the data suggests "we're losing that fight a little bit." Keeping up as the bar rises, he argues, requires deliberate practice, thinking, and judgment.
Lenny compares it to eating Doritos: if there's an easy button, people press it. He wonders how junior people will learn to code or write a PRD from scratch. Segal adds that people miss feeling smart. Encountering models like Fable 5 can erode a sense of self-efficacy. Every time you solve a problem yourself, your baseline self-confidence rises. Every time you offload it, that baseline drops, and so do your thinking and judgment. Lenny reads a line from the written report: the productivity gains are real, but the quality of the work and the sharpness of the person producing it are taking a hit. He jokes that humans need evals too.
The number-one fear: doing more for the same pay
Given how much public discussion centers on replacement, Segal expected fear of losing one's job to AI to rank high. When respondents were asked what worries them, it came second to last. The top fear was the expectation to do more for the same pay, which Segal describes as being squeezed again and again to accomplish more in less time. Second was that the pace is becoming unsustainable. That means both the expected velocity of output and the pace of technological change, which forces people to spend time learning new models and frameworks at the expense of focused work. He calls this a downward spiral that leaves people feeling they can't accomplish anything meaningful. Lenny reads another line from the report: the speed AI unlocked got plowed straight back into expectations, every gain becomes the new baseline, and the people expected to hit it are running out of room to breathe.
Ambivalence and "smiling exhaustion"
The emotion data offered some good news: the two most common emotions were positive, curiosity and excitement. Further down the list came a mix: overwhelmed, conflicted, relieved (at what people have been able to offload to AI), tired, burnt out, uneasy, anxious, and hopeful.
Segal borrows the term "smiling exhaustion" from Nikhyl Singhal's appearance on the podcast. Old-style burnout, he says, was grim and rooted in disengagement. The new version involves people feeling almost reborn, shipping and building again, but with no off switch, a brutal tempo, and rules that rewrite themselves daily.
His broader point is that people aren't simply hype merchants or doomers. Behind the theatrics Elena Verna described, everyone carries some of both, in different proportions. He tells listeners it's fine to feel excited and overwhelmed, relieved and tired, or resentful while still feeling positive overall. Those feelings can coexist, and there's nothing wrong with holding them together.
Designers, researchers, and data analysts
For the second year running, designers and researchers were the most negative group. They had the highest shares feeling destabilized or diminished, led on tired, overwhelmed, and anxious, were near the top in worry about losing their jobs to AI, and were the least likely to recommend their roles. Lenny points out that on the specific fear of losing one's job to AI, data analysts were even more worried. Segal attributes that to the strong AI capabilities emerging for data analysis. He had expected engineering to score higher on some measures given advances in coding, which he takes as further evidence that feelings don't map one-to-one onto actual AI capability.
Acknowledging he isn't objective, Segal tells designers and researchers he believes there has never been a more important time for their work. He cites conversations on the show with Linear's CEO Karri Saarinen on quality, Katie Dill on taste and beauty, and Jenny Wen, who leads design for Claude at Anthropic. Lenny adds that a recent guest, the head of the Codex app, discussed how AI is still poor at design and how AI-made design is recognizable. Lenny had hoped this would make design a differentiator amid generic "AI slop," and is optimistic that will happen. Segal recalls that some of AI's design limitations came across in that conversation as tractable, while others seemed much harder, and says creating novel, creative experiences is still beyond the technology. He hopes the design and research community's outlook turns around next year.
Who's happiest: founders and small companies
As last year, founders and people at small companies are the happiest. Segal cautions about selection bias: the sample reflects founders whose startups are still running, not those who shut down. Founders lead on nearly every measure. They are 71% optimistic, enjoy their jobs most, have the lowest burnout and layoff worry, and the most AI excitement. Segal calls this a medium-sized effect. Agency has limits, though: 47% of founders are still at least moderately burnt out, and even founders aren't likely to recommend founding a company. Lenny adds that this may reflect the current moment and could change if the market shifts, so it doesn't mean founding a company will make someone happy.
Company size shows a strikingly linear pattern. As companies grow from 1–10 people to 5,000–10,000-person enterprises, optimism falls, burnout rises, layoff worry rises, and willingness to recommend one's role falls. The two largest size bands are within the margin of error of each other. Lenny notes there's no sweet spot; it just keeps getting worse. Segal stresses that even the lowest burnout levels, at the smallest companies, are high enough to worry him. He says the "vibe" in tech feels very different from their Airbnb days. In relative terms, though, moving to a smaller company or starting something may be worth considering. Lenny muses about running the survey outside tech; Segal jokes that his HVAC technician in Florida is feeling great about his career.
Managers: the biggest lever
Manager effectiveness remained one of the largest effects in the data. The more effective people rate their manager, the lower their burnout and the higher their enjoyment. Those with extremely effective managers report around 65% higher job enjoyment and dramatically lower burnout. But supply is short. Only about 25% rate their manager as highly effective and 36% rate theirs as ineffective, barely changed from last year. The worst-rated managers cluster in data analytics and design.
Segal raises two concerns. First, in the era of the "great flattening" and "founder mode," managers have more direct reports than ever. He acknowledges the arguments for flat organizations but questions where this leads, given how much managers matter. Second, the manager is the person who most controls the squeeze: they protect you, or they largely determine how overworked you are. He suspects some of the negative trends are a function of what companies are doing to managers. On the clustering in design and analytics, he doesn't claim a clear explanation, but suggests managers in those struggling functions are suffering too, and some of that negativity inevitably passes to their teams. He urges leaders to invest in manager training, which he says is still too rare, and urges job seekers to think carefully about who their manager will be. Lenny adds that retaining good managers is harder now that AI labs are poaching talent with large offers.
"Chaotic": how people describe the industry
Asked in open-ended form to describe the state of the industry, respondents produced a word cloud of change, chaos, speed, excitement, flux, hype, instability, bubble, and opportunity. Segal shares two quotes. One: "We're in the second inning of a massive shift. No one knows how it will end, but all you can do is keep taking at bats." The other, from a senior PM, said tech is manic: half are out of touch and clinging to the overhype bandwagon, and the other half are exhausted by the first half. Sentiment analysis of the responses came out at 37% positive, 37% negative, and about 26% neutral. Segal reads this as another even split: everyone is seeing the same thing, but half find it thrilling and half find it terrifying.
Lenny cites Elon Musk's remark that we must be living in a simulation to be alive at the moment of data centers in space and human-level AI. Segal responds that, as a psychologist by training, his focus is people, not the universe. Access to the best models won't decide whether an organization succeeds, he says; the people living through this shift, excited and exhausted and hopeful and scared all at once, will.
What employees and leaders can do
Segal offers two sets of recommendations.
For employees:
- Go deep, not wide. People who feel amplified and energized report going deep on specific tasks and jobs to be done. Segal cautions against the narrative that everyone must now become a generalist who does everything while neglecting their core role. He believes that path leads to severe burnout.
- Watch the squeeze. Take the burnout test linked in the article, reflect on where you are, and realign scope with your manager if it has grown without any change in pay.
- Invest in your manager relationship. Build good communication and learn to manage up.
- Consider smaller companies or founding. The data suggests real advantages.
- Seek mentorship if you're early in your career. As the lower rungs disappear, look for teams, managers, and people willing to invest in your development.
For leaders:
- Invest in managers. Segal calls this possibly the best money a company will ever spend. He considers it a red flag that only a quarter rate their manager as highly effective, and says it matters especially for retention amid AI-lab job offers.
- Manage the squeeze. Set sustainable expectations for productivity rather than letting AI keep raising the bar.
- Don't let the bottom rung rot. Help entry-level people advance. Segal notes they are often among the most AI-native employees.
- Pay attention to design, research, and other struggling roles.
- Remember that AI is lifting some people and destabilizing others.
Lenny adds his own endorsement of the burnout test. He says he has gone through burnout without recognizing it, and that simply knowing you are severely burnt out lets you decide what to do, whether that's talking to a coach or manager or taking time off.
AI guilt
Segal closes with one more pattern: AI guilt. Early-career workers feel that using AI is a bit like cheating, and this guilt declines with seniority. It is highest in product marketing and data and analytics. He relates it to the impostor phenomenon, competent people feeling their success isn't really theirs, except that now the credit goes to a technology rather than to other people. His advice is not to feel guilty: learn to use AI, since it is unlikely to go away.
Lenny says they plan a follow-up based on listener comments, while acknowledging they won't have answers to everything. Segal describes himself as a techno-optimist despite the largely negative findings. He hopes the results turn out to be too pessimistic, and wants future surveys to capture it accurately if things do move in a good direction.
Bad news for the tech community.
Burnout at work is a major problem and AI could add to this already overwhelmed employee problem.
The honeymoon period with AI is over. When people are asked, what are you afraid of? Losing my job to AI is actually second to last. What we saw rise up to the top is the expectation to do more for the same pay. We did this survey on how people are feeling in tech right now. Burnout is increasing significantly. Optimism is declining.
It's never been crazier. When are we going to get to the optimistic part of this episode? Half of the people in tech are feeling incredible. And the other half told us, "My brain is rotting. My work feels worse." Elon had this really interesting way of describing it. We're definitely living in a simulation if we're alive right now when we're about to start building data centers in space and AI is going to be as smart as human. What does this tell us we should be doing if we can do anything? We're in the second inning of a massive shift. No one knows how it will end, but all you can do is
Today, my guest is Noam Segal. Noam and I go a long ways back. We worked together at Airbnb for many years where he was my research partner. Since then, he went on to be a research leader at Intercom, Twitter, Wealthfront, Meta, Zapier, and Figma. Noam is so amazing, and over the past couple years, I've been lucky to partner with him on a bunch of research projects. The most ambitious of which has been a tech worker sentiment survey, which we plan to run every year. This is the second time we've run it, and the results are so interesting. I believe this is the largest survey of its kind looking at how people in tech feel about their jobs and AI and layoffs and burnout and the future of their careers.
There's so much in this and basically this episode is a conversation about the results. At the end of the conversation, we go through a bunch of advice on what you might do if you are currently on the struggle bus and trying to figure out what to do. I am so excited for this episode. I'm so excited for this report. A big thank you to Noam for doing the work to create the survey, run the survey, analyze the survey, and write the post that we will link to. It is so good.
Before we get into it, do not forget to check out lennysproductpass.com for a free year of the hottest and most well-crafted AI products in the world, available exclusively to Lenny's Newsletter subscribers. With that, I bring you Noam Segal.
Noam, thank you so much for being here and welcome to the podcast. Thank you so much, Lenny. It's such an incredible experience to be here. Thanks for having me.
It's my pleasure. We've actually worked together for a long time. And few people know this. You were the researcher on our team when I was at Airbnb, this was like 10 years ago.
Decades ago, a decade ago, Lenny, so much has changed.
So much has changed.
So much has changed. Which is a great segue to what we're going to be talking about today, which is we did this survey on how people are feeling in tech right now. It's never been crazier. And so we did this report on just how are people feeling. And this is the second time we've done this. We ran this a year ago. And the idea here is we're going to have this yearly tech sentiment survey that's going to track how tech people are feeling. Before we get into the takeaways, give us a little context just on this survey, like how you ran it, what were we looking at? Anything people need to know?
Yeah, so to your point, this is the second time we're running this survey, which I really feel is unique in the tech industry. I appreciate you for giving me the opportunity and giving us an opportunity as a community to learn more about how we're all feeling in tech. I'm not aware of any survey like this at this scale looking at these things.
Last year when we ran the similar tech sentiment, the first inaugural tech sentiment survey, the title was burnt out but optimistic. We were seeing fairly high levels of burnout but also fairly good levels of optimism about where things are going. And we actually followed up on the burnout point and we created the armor framework, if you remember. And I'm really glad we did that. This year we surveyed about 6,000 people from product, engineering, design, research, marketing, pretty much any role in tech. And the results were very interesting. So I'm very excited to jump into them.
Yeah. I just remember when you shared the first draft of the analysis and I was just reading it, I was like, "Holy, this is so interesting." And it just feels like it's putting words to the way I feel, the way that I hear a lot of people feel. So, I'm really excited that we're doing this.
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Today we're going to go through the top 10 takeaways. What's the big picture takeaway from the report overall? If someone could take one big takeaway away.
Well, first I'll say that you and I both noticed an incredible post from Elena Verna a couple of days before this pod was recorded, and she's talking about the AI confidence theater and how in conversations these days in tech everything is dead. First of all, coding is dead, design is dead, SaaS is dead, etc. Obviously, that's not true. So, what you're about to see in these results is the best picture we could provide and probably the best picture anyone's provided so far of how people are really feeling about AI.
And to me, this also ties to the fact that if you're watching this and you work in tech, you probably answer some sort of biannual Culture Amp style survey about how you're feeling. But the questions don't really dive any deeper than the effectiveness of your manager or leadership at the company you work at.
Whereas the big picture in this survey, and I think the thing that stood out to us the most, is how bifurcated the workforce is right now. And what you're going to see is that AI has an outlier level, outsized impact on how people feel about their work, more so than any other characteristic of their job, whether it's their role, the company they work for, the company size, their level, etc. Half of the people in tech are feeling incredible, energized, amplified, excited about the technology and the future of their role. And the other half feel like the future is unclear. They feel destabilized. They feel diminished. Other negative emotions around that. It's a very interesting picture that really cuts the tech workforce in half, and that's what we'll see in a second.
It feels so like yes, this feels correct as we look at people in tech. It's just so clear that this is happening, and what's interesting is it's 50/50 in the results. I didn't expect it to be so even. That was a really interesting takeaway.
It's 50/50. When you dive a little bit deeper into the data, there is some nuance there. So, we're looking at this slide with the question that you and I both decided to add to the survey, which is, how has AI shifted your professional identity, if at all? And I'll actually call out first of all that only 3% of people reported that AI hasn't shifted their identity. So, clearly AI has changed how we each view ourselves. That's first of all. But then to your point, the most prominent thing here is that 50% of people in tech are feeling amplified. They feel like they can do more. They feel like they can do better. It's a wholly positive emotion. And it's great. It's great for them. But the other half of tech divide into three distinct groups. The first group is people who feel like their role is being redefined. That group doesn't actually have that much clarity or specific positive or negative emotions around what's happening. They just don't really understand it. It's a very mixed bag type of emotion where it's very clear to me that my role is fundamentally changing, but I don't really know what it means. And that's 27% of our sample.
Then as we go down the line, we have two groups who have clear negative emotions around what's going on. The first group, 14% of people, feel destabilized. The ground is shaking beneath them. They have very little clarity on what's going on. They have high anxiety levels. They report having very negative and pessimistic views of what's to come. And then 5% of people feel diminished. They feel like the great powers of AI have taken something away from them, and something that obviously is never going to come back, because what's the saying? AI models are the worst today that they'll ever be. They're only getting better. So people who feel diminished now will only feel more diminished in the future, probably.
Super. So, following that thread—
Sorry for the bad news. Sorry for the bad news.
There's some good news here. So, following the thread, these buckets correlate super strongly with basically every other measure of how people are doing. So, this kind of regression on just every other core question you asked, and it's so interesting to see how connected these are.
Yeah. And just to put a couple of statistical terms on this to clarify how big the effect is: in tech we are somewhat obsessed with the notion of statistical significance. But the thing about statistical significance is that if you have a large enough sample you can sort of reach that type of significance regardless of how much the effect matters practically. A better way to look at things is using an effect size measure like Cohen's d in this case. And what effect size tells you is practically how much does this thing matter.
So for example, last year a couple of the largest effects we saw were, number one, your manager. Who your manager is and how effective they are matters a ton to how much you're enjoying your job and how optimistic you are and how burnt out you are or not. And we'll see some of that later on. And the second large effect we found was the founder happiness effect. Founders, at least people who are currently founders and in their journey of running a startup, are incredibly happy, probably because they have a lot of agency and autonomy relative to the typical employee.
This finding, this insight around the impact of AI on your identity and on every single other variable around your job, is about three times as large as those other effects. So this technology, this era that we're in, is having an outlier level, outsized impact on how people are feeling about work, more so than anything else we've seen.
So let's actually look at that data of just how this sort of classification connects to optimism, burnout, things like that. And we're going to come back to just what exactly is that divide, just a question to ask that tells you which side you're on. But let's look at this first.
Yeah. So we'll dive into some of these things in a little more depth later on. But just to put it all together, what you're looking at here is the AI identity stance and then a breakdown by your AI identity around career optimism, burnout, layoff worry, and an interesting one for me, and we'll talk about this further: would you recommend your role to someone coming into the industry now? And what you can see is that as you move from the people who feel amplified to the people who feel diminished, career optimism goes down significantly. Burnout, or reports of burnout, go up significantly. Layoff worry also rises significantly.
And perhaps the most significant finding of them all is that people would not recommend junior people, early career people, entering into the tech workforce at this moment given what's happening with AI. And you're seeing these very linear, clear, and organized effects, which just demonstrates to you the impact that AI is having on all of these different variables.
And what I love is you took all of these data points and you've created these four archetypes of people today. And I feel like everyone listening is going to be like, okay, that's me. So let's go through that.
Yeah. So, we're seeing these four tech workers. And the way we got to this is later on in the survey, we asked people about how they're feeling and to report specific emotions. And people could choose as many emotions as they wanted, right? And by the way, fun fact, on average, people selected five different emotions. And I think a couple of people selected 13 emotions that they're feeling, which is a lot.
So the first archetype we found is the energized tech worker, and that's 41% of our sample. These are the people who were saying that product has become fun again. I'm exploring things. I feel like I'm in the tech amusement park where everything is open to me and I can experiment with new approaches. I'm a builder now. I have powers that I've never had before, etc. These people are very energized about the technology and about their careers.
The second group we called the conflicted, the ambivalent middle. These are 35% of the sample. These are people who are having on the one hand the most fun they've ever had as builders, as PMs, as designers, as engineers, whatever their role is. And on the other hand, they're feeling the most uncertainty that they've ever felt in their careers. They just don't understand where this is going and whether they're building the things that will ultimately lead to the end of their careers as they know it.
The third archetype are the disoriented people. The people who feel like their role keeps shifting. There's a quote that we saw from one of the respondents: we're like farmers on the cusp of the industrial revolution and we just don't see a clear path to what's happening. Very interesting comparison to that era. And these are people who are feeling very disoriented around what's going on in their career and where things are leading.
And then finally, 12% of the sample we categorized as resentful. They're feeling pressured. They're feeling checked out. They are not enjoying their work right now. They're saying things like, "I've been forced to use AI or lose my job. And even when I use AI, I'm still seeing people lose their jobs. I just hate it." You know, I hate having to leverage this technology rather than do my own thing and maybe ignore the technology, which obviously none of us can ignore at this point.
There's a lot of people clearly that are very unhappy, resentful, disoriented. I imagine that group can't imagine a lot of people are feeling extremely energized, and I think the vice versa. So I think this is just really interesting to see that so many people are very different from you. There are many people that are having a really good time, a lot of people that are having a really bad time, and it's just a good way to remember that and basically have empathy for the other half, especially the folks not doing as well, because not everyone is as
energized, and we'll talk about what that energized group looks like, but I think that's just an important point: a lot of people are having a really hard time.
I really agree with you, Lenny, and I think that given the pace of change of the technology, I really do feel that too much of our focus is being spent on mastering the technology and trying to understand what the heck we should be doing with these new releases, new models, new capabilities, loop engineering, whatever the next thing will be next week. And we're not spending enough time and focus on our relationships at work, on seeing our colleagues, on supporting our peers in also being able to work with this technology, thrive with it, succeed with it, and get along and collaborate well with people who don't belong in the same bucket as us when it comes to how the technology is being perceived. So I personally would love to see all of us, especially energized people, take some of that energy and spend it on the people around you rather than the all-in focus on whatever the next thing is with AI.
Let's go to the next takeaway. Let's talk about burnout and optimism.
Yeah. So last year we looked at burnout and we looked at optimism, and burnout was at a worrying level, enough that we published further research on it and we introduced the ARM framework around how to deal with burnout and fight burnout. And this time around, I'm not sure what I was expecting necessarily. I think I was hoping that optimism would hold steady and that burnout wouldn't go up, because supposedly with new abilities and even better models, perhaps you might think that we wouldn't have to work as hard or put as much energy into everything in a way that gets us burnt out. And yet, that's not what we're seeing. When it comes to significant burnout, burnout that's higher than moderate, we've gone up from 44.7% in 2025 to 54.7% in 2026. So burnout is surging. More than half of our sample are feeling significantly burnt out at this point. And at the same time, optimism around the future of our roles and our careers is falling from 54.8% in 2025 to 48.7% in 2026. Bad news for the tech community.
I don't know what to say about this other than that sucks. I don't like this. I get it fully. I can completely understand why people are feeling this. Pretty worrisome, the rise, like a massive jump, over 10% increase in burnout in just a year.
Yeah. And it's interesting, you've had several guests on in the past who've talked about things related to this. I loved your conversation with Geoff from Ramp, and he shared that his worst burnout happened when velocity was lowest. So when you put effort into things that don't actually move, it doesn't feel good, and that leads to burnout. And I think that maps for me with certain theories around burnout where stagnation leads to burnout. I think what's going on now is the opposite. These data showcase to you that as we ship faster than ever, as we move from shipping a couple of PRs a day to 30 PRs a day, or just doing so much more, in some ways that might be fun, but we are burning out more than we did before. And we're not working any less hard, clearly, right? We're just taking on more stuff, more stuff, more prototypes, more PRDs, more PRs, more campaigns, more agents, more ads, and it's leading to more burnout.
Yeah. And that's actually one of the takeaways which we'll get to. I don't know if you have this in this deck, but the glimmer of hope that you pointed out is that enjoyment of work is actually still very high. There's burnout, but also people are still, at the same levels as last year, actually really enjoying their work.
I think what we heard about enjoyment more than anything else, which does give me hope, is a couple of things. First of all, people are able to bring out certain aspects of their identity and of their passions that they weren't able to before. If you're currently a PM by role, but you have a designer within you, or you're a marketer, but really inside you have that engineer that's been really wanting to come out, now you can, right? Various tools that are available to us these days enable you to bring out those sides of your personality and those professional aspirations. And that's something that people are really enjoying. We're sort of escaping our classic swim lanes, and a certain percentage of our roles are transforming into something else. And then the second thing that people are saying that they're finding enjoyable is that they are able to manifest things that they've wanted to build that seemed impossible not very long ago, and that's whether it's in their main job or things that they're doing on the side, etc. So it is still, for many people in tech, an exciting time and an enjoyable time, because we can do things that we never thought we'd be able to do, because they're outside of our role, because they're outside of what felt technically feasible, or for other reasons.
And this is another data point. At the end of this, you have a bunch of recommendations of what to do with all this information, and that connects to something that you recommend later. But before we get there, one of the other really interesting takeaways was around layoffs and how fear of layoffs impacts burnout. Talk about that.
We did ask people how worried they are about being laid off. And as you can see, 72% of our sample are worried to a certain extent about being laid off, and 41.2% are at least moderately worried about being laid off. So it is clear that people are feeling that they might be cutting the branch that they're sitting on when it comes to using AI. People are reporting that their companies are going all in on agents, all in on these technologies, and it does feel like they may be pushed out at some point. So the worry level is high. And I think if you're watching this, you're starting to notice that there's a ton of ambivalence right now in the community and a ton of clashes between emotions: feeling energized and enjoying my job, and at the same time not being very optimistic about it, and feeling tired from it, and feeling worried that all of that enjoyment is going to end one day when the company I work for decides that I'm no longer needed.
I feel a lot of people listening are probably feeling all this and feeling heard. So what's interesting is, so far, the two takeaways. One is this bifurcation that's happening and these archetypes that break that group a little bit further. At the same time, just broadly, burnout is increasing significantly. Optimism is declining. Talk about just those two, how you think about those two side by side: this idea of many people are much happier and having the best time of their life, many people are having a really bad time, but then broadly this optimism and burnout shift.
I think there's something addictive about this technology. And I'll speak for myself for a second and say that I've also never had as much fun in my career as when using these technologies. And I've been using it for too many hours a day, playing about and building. I think many of us, even those who aren't as energized about the technology, still feel like we're in this fascinating technological playground. And it's very, very hard to disengage from that technology and touch grass, read a book, whatever you love to do in your spare time as well, Lenny. And so, yes, we're enjoying using this technology because it's opened up avenues that we've never had. But on the other hand, it's tiring. It's tiring to be constantly learning this technology and constantly trying to apply it in different contexts and constantly trying to take on more than what your traditional role dictated, because again, there aren't any traditional roles anymore. We're just all builders these days, whether that's an official thing within a company or not. And so I think that naturally this leads to these clashing emotions: these exciting feelings around what's possible and how fun it is to use AI, and on the other hand, the realization that the reason this technology is so exciting is because it's so powerful. And because it's so powerful, it might be coming for us and to take our jobs, right? Did you grow up on the Terminator movies? I keep thinking about the Terminator movies.
I don't know about growing up, but yes, I watched them early in my
Oh my gosh, I love those movies, and I just can't help but wonder when the robots are coming for us. So, incredible technology might be coming for us at some point. Skynet is being built right now.
Skynet is coming.
So, there's going to be a really great takeaway around this. Before we get to that one, actually, it's like every single one is so interesting, and just like, man, this one's interesting, but they're all interesting. Let's get to the next takeaway around people's sense of their own career and whether they recommend it.
This is a wild one for me because at least within the research community, I am known as the Net Promoter Score hater. I even built a website dedicated to fighting NPS: NPSistheworst.com.
It's an actual website. Fun fact, by the way, I dislike NPS so much that I even bought the domain NPSthebest.com, and I forward people from that to NPSistheworst.com. That's how committed I am to fighting NPS. But you and I were both genuinely curious about whether people who are already a few years in, and they're maybe senior or above senior in their roles, what would they say to the person entering the industry now? Or what would they say to a person considering entering the industry now? Would they recommend their role and the tech industry more broadly to a friend or a relative of theirs? And the answer was shocking. Absolutely shocking. So, let me show you the data around this. And let me preface this with a quick explanation on NPS, because it's not so easy to understand. NPS is this question around whether you would recommend a product, or in this case your role, to a friend or family member, right? And the scale goes from 0 to 10, 10 being you would absolutely recommend your role and zero being you would absolutely not recommend your role. But then NPS as a whole, when it's calculated, goes from minus 100, which is absolutely terrible, to plus 100. And the zero point represents neutrality. It represents that the sample as a whole is neutral. It's not a promoter, to use NPS speak, meaning I would promote my role to other people, I would recommend it to other people. And they're not detractors either, which means I'm not negative about my role. So that's the zero point. What you're seeing here is that no one is a promoter of their role in tech right now. Not even founders, who are by far the happiest, happy-go-lucky people in tech right now. Founders would not recommend their roles. Neither would people in sales or go-to-market, PMs, operations, engineering, and the worst of all, designers and researchers, my community, are the least likely to recommend their role to other people coming into tech. It's sort of like saying, I'm kind of swimming in this pool, the water's kind of okay, but you shouldn't come into these tech waters. They ain't for you.
My god, what an interesting takeaway and part of this research. So, just looking at this chart, just as people are seeing this, everyone's like, "Nope, don't do what I do." It's interesting. We're going to talk about how founders are the happiest people in tech, but still it's a very stressful, hard job. I'm surprised it's the least, like you would think many founders would be like, this is the craziest, gnarliest job, you should not do this, it sucks. But it's interesting. They're the least unhappy. They're the least likely to recommend.
There's a strong narrative right now that there's never been a better time to be a founder. You're a lot less reliant on other people to build.
There's a ton of conversations around the solopreneur or the duopreneur, right? There's a ton of conversations around how this is the era to be a founder, and yet people who are currently in that role aren't very excited about recommending it to other people. There's also another layer to this, which is as you go down in seniority, you're less likely to recommend your role. So execs, VPs, maybe even directors are sort of more likely to recommend their role than people who are ICs. That's an interesting one. And I've seen all sorts of explanations for that. One explanation, for example, is that at the top of the pyramid, VPs are benefiting more from AI because they're getting all of this stream of information and knowledge being processed by AI, making their jobs a lot easier. Whereas ICs are each scrambling to build all of these micro SaaS products within the companies they work for. No one knows what anyone else is doing. There's a lot of duplicative work. It's a lot easier to build products these days, but a lot harder to maintain them. And so I think a lot of ICs are feeling like, there's a saying, full gas on neutral, right? Like you're pushing the pedal to the metal in your car, but you're in neutral gear. You're not going
anywhere. I think that that's the feeling that a lot of ICs are having these days with these technologies. Like, I keep building these things, but I'm not having the impact I want. Everyone else is building too, there's a lot of confusion, and it's just not worth it anymore.
There's this interesting trend also, there's this whole meme of "don't become part of the permanent underclass." And I feel like there's a few of these threads throughout this, and here it's like, okay, I'm a PM, but it's too late. Don't do this. The door is closing for this role. Things are changing, and it's not just PM, it's every role. Everyone's just like, maybe you should do something else.
Yeah, I would agree with that, and I think it's unfortunate. I feel like in the past people were pushed to CS, to learn to code. I know that these days, for myself as a parent, I don't know what to tell my kids to do anymore. I'm not sure what roles will be there for them in just a few years. These are very confusing times, and I think tech employees are feeling that as well. They don't understand what's in line for them in the future. We certainly don't know what to recommend to others, like, yeah, in 5 years
it's going to be great.
Plastics.
No one knows. Just zoom out for a moment. It's so insane how much change we're living through right now. This is not a result we would have seen a year or two ago. This is so unstable and uncertain, and this is very new for people in tech, I think.
Yeah, I like to use certain metaphors or examples from other areas in my life to explain these things. So, I believe you spoke in the past to Scott Wu, the co-founder and CEO of Cognition.
Mhm. Devin.
And yeah, the makers of Devin. And I recall that when he described the product, he talked about this ladder that the product progressed on. It went from a high school CS student to a college intern to a junior engineer, and at this point probably a senior or a staff-level engineer. I would say that we are all watching this technology climb the rungs of this ladder and advance, and we feel like the technology is pulling those rungs from under us. And so the further we've gone up the ladder, the better we feel about our careers and the more stability we have. But the lower we are on that ladder, those rungs are getting pulled from under our feet. And so it makes lots of sense that we wouldn't recommend being on that ladder to anyone else, because the rungs are disappearing.
Man, there's so much to talk about with this, but let me point out a couple things as I look at this, and then we can move on to the next takeaway. One is just, you know, at the
Interesting that sales and PM are the least bad at "don't get into this role." That's interesting, I wouldn't have expected that. Salespeople not as scared about the future of the role. PM, interesting, that's a big audience here, not as scared. As you said, research and design the most "don't do this." As a researcher, you touched on this a little bit, but I'm just curious, how does it feel seeing this?
It's tough. I think the research community has lived with a lot of concerns and trauma and anxiety over the years around having a seat at the table, around finding meaning in our work, around topics like the democratization of research and other people taking on our roles and eventually replacing us. It definitely hurts a lot to see this.
I think there's a very important role that research needs to play in the future of building products. I think that as this technology progresses, we should become even more thoughtful about what we build rather than less thoughtful. I've heard the narratives around, you know, it's so cheap to build, just build a thousand prototypes and see what works. I think you heard this in a recent conversation as well. I would suggest that we're just going to get even more burnt out that way. I would not recommend that approach personally. I think research and design has a very important part to play in raising the ceiling of what's possible, whereas AI has mostly lowered the bar, but it hasn't raised the ceiling.
And I can also tell you that PMs being somewhat more likely to recommend their roles, even though they're not likely to recommend their roles, does actually make sense to me. It's more of a generalist role, I would claim, than some of these other roles. And this is the era of the generalist, if you would ask me, the AI era. I'm the most surprised by sales and go-to-market, because if we are indeed in some sort of SaaS apocalypse, which I don't personally believe we are, but it's been said, then I don't think sales and go-to-market people should be feeling too great about recommending their roles. But maybe they believe that sales at this point cannot be done by AI.
Yeah, there's just so much I want to talk about here. It's important to note, this is a very important note that I'm going to say here: this doesn't mean design is going away or research is going away. This is just saying people in that role right now, the narrative in their head is "don't do this." Does not mean this is over, because it could just be all this hype that we keep hearing, like, you know, guilty of adding to it from various guests. But this is just how people feel; doesn't mean this is what's happening.
100%. This entire unique project in tech is all about how people feel. It's not about the realities of working in tech. It's about people's emotions, about how people feel. I really do think no one other than us has really captured these emotions in the way that we have. But yeah, that's a great reminder. This is not an image of reality. This is an image of how people are feeling in tech right now.
Another quick data point that we want to make sure to communicate here. You touched on this, but I don't know if you actually made this as clear to people as it should be. So this is looking at "would you recommend people get into my role." We also asked just how are you feeling about your role, like are you happy being in this role? And the result there was, "I'm actually doing okay. I'm happy I'm a PM, I'm happy as a designer, researcher." So as you said, it's this kind of like "the water's fine, but don't get in." Talk a little bit about that just to make sure that point is clear.
When we asked people things like are they enjoying their job, as we talked about earlier, most people said that overall, yes, they're having fun in their role. I think what's going on here is that, again, people are lacking optimism compared to what they were, right? Optimism has gone down. So there's a big difference between how people are feeling now about their role, given what they've achieved in their careers and where they are on the ladder, compared to what they're extrapolating might happen in a year, in 3 years, in 5 years. And what people are extrapolating might happen is clearly more negative than their current experiences.
So yeah, I mean, all in all we're doing okay as an industry. We're enjoying, we're trying new things. We're experiencing a complete paradigm shift in how we work, and that's fun for a while, but it seems like people feel like this is not going in the best of directions. And of course I hope we're all wrong. I hope we're all wrong.
Me too. As a natural optimist, I'm like, it's gonna be all right. So, we'll see.
I'm a natural optimist, too. And I'm realizing so far we haven't been in too much of optimism mode. So, I hope we manage to get to some of that as well.
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Let's talk about takeaway four. Looked at productivity, looked at quality, looked at just kind of the upside of AI.
This was a very interesting one to me. In last year's survey that we did on the impact of AI specifically on productivity and quality, people were rather bullish about the technology and how much better it makes them, not just more efficient but better. And this time around we saw some interesting findings. Let me start with this, and this is sort of the initial view, but it leads to something very different than I thought would happen.
When we simply asked the question, how much better are you at your job thanks to AI? Unequivocally the answer was yes. You can see here that 97.2% of people are saying that AI is making them better at their job, and close to 50% of people are saying that AI is making them very much or extremely better at their job. So it's very clear that, high level, however you interpret better, which we'll get to in a second, people feel like AI has had an impact.
But when you dive deeper into what that means and you go below the surface level, as you can see here, "we're doing better" actually means something rather different than what you might think. So when I heard people say they're doing better, I thought they meant that literally. I thought the quality of their work was better, that AI was contributing to better quality of work. In fact, it's the exact opposite.
What we heard from people were two concerning things. The first is that I can do more faster, but not better. So again, AI has sort of lowered the floor of what's possible and enabled people to put out a lot more work than they ever have before, whatever that work is, whether it's PRs, PRDs, research projects, prototypes, but the output isn't of higher quality.
And perhaps the even more concerning effect which we heard about, the deeper cost of all of this, is the cost of using AI on thinking and judgment. People essentially told us my brain is rotting, my work feels worse. And this is related to a phenomenon I've heard about recently, is it cognitive rot, I think, is what I've heard. Basically this phenomenon where you see the initial output of an AI model and you just accept it. You don't apply your judgment to it. You don't apply thinking to it, and you slowly let your mind, your involvement in your work, your agency sort of collapse into this rotting state, so to speak.
Yeah, this is such an interesting takeaway. There's a positive note to this. As you said, I'm looking at the numbers here. 82% of people say AI is making them at least moderately better at their job, and nearly 50% say very much or extremely better, which may correlate with that original bifurcation, like the people that feel like AI is making them better at their job are probably the people that feel most energized.
So whether it's true or not, I think there's a couple happy points. That's one: people feel AI is making them better. They feel that, so that's real, even if it may not be. And at the same time, I think they're self-aware the quality is an issue, and also maybe I'm atrophying in my ability to, say, code or write strategy docs. So at least people are self-aware that this is happening. Not just "I'm killing it, all my stuff is higher quality and it's much better than ever."
They are self-aware, but, you know, among other things I'm a certified coach, and I would suggest that beyond being self-aware, we need to act on this. There are several explanations I could give to this phenomenon. One of them might be that the honeymoon period with AI is over. We thought it was perfect and the best thing that ever happened to us since sliced bread or whatever typical Americans say. But we've realized it's not quite there yet. And yes, the models are the worst they're ever going to be. They're only getting better, but there's still so much they need to get better before we can really say, "Yeah, my work is just so much better, and I don't need to be as involved with it."
You had Simon Willison on this show talking about how people are worried about skill atrophy, that they're not learning enough, and that we need to be consciously resistant to this and not let ourselves cognitively rot. And I think this data suggests that we're losing that fight a little bit. We need to put a little bit more energy into fighting this cognitive rot that we're feeling, and to make sure that as the bar continues to rise and this technology continues to evolve, we're meeting that with deliberate practice, deliberate thinking, deliberate judgment.
People are just so bad at that. Just like if I have an easy button, I will press it. I know I shouldn't, but I'm just going to eat those Doritos. So that's the challenge, I think, for people, just like because you could do it the easy way, it's so hard to resist. And that connects again to this ladder that's being raised, that people just getting into this stuff have to make themselves do it the hard way to learn how to do it for real. And I'm really curious how that plays out with junior folks in the market learning how to actually code, how to do writing, how to write a PRD from scratch with your fingers versus talking to Claude about it.
Yeah, there's so much to say here. I think people miss feeling smart sometimes, you know. I thought once upon a time about myself that I'm smart, and then you encounter these models, most recently Fable 5 that just came out for the second time, and you don't feel that smart anymore, and you sort of lose this sense of self-efficacy that you used to have. And the second thing to say about this is that every time you, not the AI, solve a problem and get over a barrier, it raises your baseline of self-efficacy, of self-confidence, of self-belief. And every time you offload that to your favorite AI model, you're lowering that baseline, and your thinking and your judgment is watching. And that's a serious problem.
So maybe to just wrap up this takeaway, the sentence used in this report I love, I'll just read it: "The productivity gains are real, but the quality of the work and the sharpness of the person producing it are taking a hit."
Absolutely. And maybe we'll get to this in the end, but we should keep a close eye on this and really try to work on our own self-efficacy.
We need evals for people, like are humans becoming...
Evals for people. Let's do that.
Your smartness. Okay, let's talk about takeaway number five, which I also thought was extremely interesting. My god, so much interesting in this. Let's talk about the fifth takeaway.
Yeah. So, I think the dominant narrative right now in our community is the fear of being replaced. And as we talked about, a lot of people in tech do fear and are worried that they're going to be replaced, that they're going to be laid off. And so it would make sense that if we had a question and one of the options to respond to that question were "I'm worried about losing my job to AI," that it would rank fairly high. But when we look at this slide, and when we look at when people are asked what are your concerns and what's bothering you right now, what are you afraid of in tech, losing my job to AI is actually second to last on that list.
And instead, what we saw rise up to the top is the expectation to do more for the same pay. It's almost as if we're all feeling like we're being squeezed and squeezed and squeezed some more to accomplish more things in less time for the same pay. And so that fear of being overworked is by far the dominant fear, alongside the second item in this list, which is that the pace is becoming unsustainable.
And by pace I mean both the pace of the work and the expectation of work velocity, just how much you have to put out a day, every single day, and the pace of change of the technology, which requires you to invest a significant amount of time in learning the new model, the new framework, the new way to use the technology, which of course takes away from your core focused working time. So, it's sort of an evil downward spiral that really prevents you from feeling like you're able to accomplish anything of meaning. You just feel very overworked, very tired.
I'm confident everybody listening understands exactly what you're describing here. Obviously connects to that burnout point we made earlier. I'll close this takeaway with another quick read from your post. You're such an amazing writer, Noam.
I love reading your summaries of what you learned. So, I'll just read this: "The speed AI unlocked got plowed straight back into expectations. Every gain becomes the new baseline, and the people expected to hit it are running out of room to breathe."
When are we going to get to the optimistic part of this episode?
Maybe we'll find something. Okay, let's talk about 6, which has a little bit of optimism.
Oh, yeah. Okay. A lot of ambivalence is another way you put it.
Yeah, I mentioned this earlier. The industry is definitely in a state of ambivalence. We try to capture all of the emotions that people are feeling at work right now. And I am happy to report, as you can see here, that the top two emotions are positive emotions, curiosity and excitement. And that's wonderful. That is optimistic. I'm glad that's the case. People are sharing that they're excited about the technology, about the capabilities, about what they're able to achieve. They're feeling curious about what the future might bring and what else they could do as these models and systems continue to evolve. So, that's wonderful.
But as you go down this list, you can see that there's this very interesting mix of positive, negative, and neutral
emotions. People are also feeling overwhelmed. People are feeling conflicted. People are feeling relieved in certain ways about, you know, what AI has taken from them in a good sense, you know, what they've been able to offload to AI. And then people are feeling tired, burnt out, just working hard and hard as we said, uneasy, anxious, and then hopeful. So, as you can see, there is a wide variety of emotions here. And it's really tough to figure out what exactly is going on.
But one thing I definitely wanted to mention, which Nikhyl Singhal mentioned in an episode with you, I know he's a friend of the pod and such an incredible leader in product and in general in the tech community. He talked about smiling exhaustion. And I just love that term because I think it captures this ambivalence. The old type of emotion, the old type of burnout was just completely grim, you know, it was all about these negative emotions that come from disengagement and exhaustion. Whereas now, when Nikhyl talks about smiling exhaustion, it's about people almost feeling reborn on the one hand. You know, I'm shipping again. I'm building. I'm creating these incredible things with AI. There's never been a more exciting time, but there's no off switch. There's no off switch. And so, the tempo is absolutely brutal. The rules keep rewriting themselves every single day. It's a very relentless pace. And so, we're smiling through that exhaustion that we're feeling. And I think that captures the ambivalence more than anything really.
I think it's also good to kind of come back to one of the core points you made earlier that half of people are actually feeling very like they are working very hard, probably exhausted at times, but they're also just like really into it, they're going all in, feeling good, energized about where things are going. So I think it's important to always remember, like kind of come back to that as we share all these negative elements. There's actually a large group of people that are actually loving this time and doing super well.
There are... I think more than anything what I would like to highlight here is that, you know, we tend to think of things way too often in black and white terms. We see people as either people who are just full of hype or people who are, is it doomers, would that be the right... you know, or haters or whatever you want to call it. What we're seeing here is that as always in life, if you ask me, things aren't as simple. Behind that facade, behind the theatrics that Elena Verna discussed, we all have both the hype person within us and the doomer to a certain extent. And the only difference between us is that we have different amounts of each. But we're not just one or the other. And there really is a ton of ambivalence, and I just want people to know that it's okay, you know, it's okay to be excited and curious, but also feel overwhelmed. It's okay to feel relieved and tired. It's okay to feel resentful even if all in all you feel positive about the technology. Those emotions can coexist within us. It's very natural. Don't let this narrative that you're either/or dominate and convince you that anything's wrong with how you feel, because really all of these emotions are very understandable given the times we're in.
Such an important point. I love that you said that. Okay. So the next takeaway, what we did here is when we were looking at this bifurcation that you found, we looked at just which functions are having the best time and worst time. And we had a hint at this earlier, and it turns out there's a couple that are just overall having the worst time right now and feeling the least happy. So let's get into that.
Yeah. So definitely, and we saw this last year, by the way, as well. We are seeing that designers and researchers are the most negative. And just to clarify what I mean by that, what you can see in this slide is that when it comes to AI identity shift, designers and researchers are the highest in feeling either destabilized or diminished. When it comes to emotions like feeling tired, overwhelmed, or anxious, researchers and designers lead the pack in a negative way. Of course, when it comes to worries about losing one's job to AI, again, researchers and designers are pretty much as high as one can be. And then finally, when it comes to these NPS-like scores of whether people would recommend their role to a friend or to a colleague, researchers and designers are the least likely to recommend entering their role at this point.
We talked about this earlier. I don't know how much more there's to add here. Basically, again, it's not that this function is in big trouble necessarily. This is how people in that function are feeling right now.
You know, I'm not objective because I'm part of the research community and the design community. If I may, I just want to tell people in this community that I truly and honestly believe that there's never been a more important time for our roles to manifest in the products that we build. You've talked about this with many people, Lenny, in previous interviews, about concepts like taste, about concepts like craft, about concepts like quality. I'm thinking of people like Karri, Linear's CEO, who talked so beautifully about the importance of quality and how you build products. I'm thinking about people like...
Katie Dill comes to mind. We had a whole conversation around taste and beauty and value.
Katie Dill, recently Jenny Wen, who leads design for Claude at Anthropic, and so many other people who talk about the importance of taste, of judgment, of design. So I honestly hope that designers and researchers make a comeback when it comes to how they feel about this industry, because the industry needs them. The industry needs us. And so I hope we see a change next year, and this is the call to all designers and researchers to get in there and do our thing, because it's incredibly valuable in this era.
Yeah, I've had a few conversations recently about just design, and in particular just why is design not a huge value add and differentiator today, knowing AI is just so bad at it. We just had the head of the Codex app on talking about why AI is not good at design, and you could clearly tell AI designed this thing. And you would think this was the moment for design to become such a value add and differentiator for companies, seeing all this AI slop that's being produced. So I'm optimistic that'll emerge as people are like, I'm so sick and tired of all these generic things. I want to actually build something great.
Yeah. And moreover, if I recall correctly, you in that conversation talked about how some of the issues around AI doing design are perhaps tractable problems, but some of them are even intractable, I would say, or definitely much, much harder to solve for. It's still the case that creating incredible, novel, creative experiences is not something that this technology is quite capable of. So, we'll see what happens, but I really do hope that the design and research community turn around and change their minds about the industry next year.
Yeah. Man, I can't wait to do next year already. What's it going to be? But if you actually look at the losing my job to AI bucket, there's actually a role that is even more worried about losing their job, and I believe that is data analytics. Our shades are kind of very similar to keep the message clear, but that's really interesting. The data analysts basically are the most worried about losing their job.
I think we're seeing incredible capabilities coming out.
Makes sense.
Yeah. With the different models out there to run data analysis. I'm seeing this in the research realm as well. I would suggest that we're also seeing incredible advancements in coding. So I was expecting engineering to be higher in certain places here, and it's not. But again, this isn't about the objective reality of how far AI has come in terms of its capabilities doing each of these roles. This is about how people are feeling in these roles, and there isn't a one-to-one correlation between those things.
Speaking of that, let's talk about who the happiest people are. Who's doing great? Who's doing best?
So, the happiest people in tech. This is something that did not change between last year's survey and this year's: it's still founders and people who are working in smaller companies. And I do feel the need to say that when it comes to founders, to your point earlier, being, not that I know, but being a founder is an incredibly challenging, all-encompassing job, and there is a certain selection bias here in the sense that these are people who are currently in the active role of a founder in a startup that is still running, rather than founders who had to shut down their startup or pivot, whatever it might be. So, I just want to make that clear around who we're looking at. But yes, when we look at founders and when we look at, in this case, you're looking at company size as well, you can see that whether it's optimism, whether it's burnout, layoff worry, or whether people would recommend their job, you're just seeing these increases or decreases depending on the question. It's very clear that founders are top of nearly every measure. They're 71% optimistic. They're enjoying their jobs the most. They have the lowest burnout, the lowest layoff worry, the most AI excitement. It's a medium-sized effect compared to other effects we saw, but very significant. And that said, you know, if we talk about founders, even having that ownership and even having that agency has its limits. Many founders are still at least moderately burnt out, 47% of founders that would be, and as we said earlier, even founders aren't very likely to recommend being a founder to other people right now, which is very interesting.
I think it's also important to note there's definitely this, as you said, this kind of meme of there's never been a better time to build. People may see this and be like, I got to start a company, it's the best place to be. It may be this moment currently where people are feeling most excited about it, and then as the bubble, you know, I don't know if it's a bubble, but as things start to get harder, there may be a shift away from that. So it's interesting so far that we've seen two years in a row founders are the happiest, but I wonder if that changes if the market changes, that kind of thing. So this isn't saying you're going to be happy if you become a founder, but it is really interesting that two years in a row, one of the clearest takeaways is just founders seem to be happiest across every dimension.
Yeah. And then company size as well. Again, optimism goes down if you're working for a larger company. You get more burnt out if you're working for a larger company. You're more worried about layoffs if you're working for a larger company. And you're less likely to recommend your role if you're working for a larger company. So that also remained consistent. And if we look just at burnout specifically, then you can see very clearly here that burnout climbs in very significant ways between working for a small 1 to 10 person startup and working for a 5,000 or 10,000 person enterprise company.
It's so wild. It's wild how linear this is. There's no bump, and then those two at the end there, as you point out here in the chart, they're statistic...
It's within margin of error, yeah.
It's wild here, it just only goes up. There's not like a sweet spot and then it comes down again. And then if you go back to the previous chart, exactly the same thing. It's just very linear. Everything goes up and gets worse as your company size grows. That's wild.
Absolutely. I would say one thing to highlight here, if you look at burnout for example, is that even the lowest is still fairly high, right? So, I would say people are feeling somewhat less burnt out, somewhat healthier working for a startup, but I would view these levels of burnout, of worry, as worrisome. I'm worried about the level of worry right now in tech. It is not a good vibe. You know, you mentioned how we met a decade ago at Airbnb. I do feel like the vibe was very different then in tech. So, I am a bit concerned about the numbers that we're seeing here. But yes, from a relative point of view, perhaps one should consider doing a shift and starting your own thing or working for a smaller company.
Yeah, exactly. That'll be one of the takeaways. You know what would be awesome is if we do one of these for non-tech. I'm really curious, just like you think people are scared and worried in tech, I'm so curious how that would compare to, you know, say, the blue-collar folks or other functions. I don't know if we have the audience to do that, but that'd be really interesting.
I mean, I think my HVAC technician is feeling pretty great about his career right now, burning hot in Florida. Everyone needs air conditioning. That's not going to change anytime soon.
Take a hack. Yeah. To start a company.
We should do that.
Start a filming business. Oh, man.
So, what I love about doing the survey again is we're starting to find things that are consistently true. And the next takeaway is another really good example that we saw last year too, around managers. Let's get into that.
Yeah. So, I mean, perhaps people are aware of this. Managers matter a ton. Who your manager is probably matters more than most other characteristics of your role. And we found this very explicitly last year and this year again: manager effectiveness. So we basically asked people, how effective is your manager? How would you rate your manager? And what you can see here is that the more effective your manager is, the less burnt out you feel and the more you enjoy your job. And this is a massive, massive effect that we're seeing. So if you have an extremely effective manager, for example, you're reporting around 65% higher job enjoyment and dramatically lower burnout. The problem is the supply. Only about 25% of the sample rate their manager as highly effective, and 36% of the sample rated their managers as ineffective, which by the way is a very small change from last year. So we're seeing managers be rated not so well, and at the same time we're seeing that when managers are effective, which is clearly not often enough, the impact that has on people's enjoyment, burnout, and other aspects as well is incredible.
That's wild. I think we're adding new insight into the world here just finding this. I've never seen this before, just how impactful a manager is. We always hear anecdotes, we always hear, you know, people don't leave jobs, they leave their manager, but this is wild, just how much that impacts you. And clearly one of the takeaways might be, if you're having a bad time, find a better manager, as you said, easier said than done.
Yeah, but there's a couple of things here I want to also note before we move on. First of all, we are in the era of the great flattening. We're in the era of founder mode. People have more direct reports now than ever before. We're trying to keep things as flat as possible and remove hierarchy. I'm concerned about this. I think obviously there are good arguments for flatness and lack of hierarchy, but I am curious to see where this goes given the importance of who your manager is on your well-being. And then the second thing is, we talked earlier about being overworked, about this squeeze that AI has on us. Who's the person more than anyone else who kind of manages that squeeze? It's your manager, right? It's your manager who protects you. It's your manager who in many ways almost dictates how much you may be overworked or not. And so yeah, this matters more than ever before. And I'm definitely concerned that some of the negative phenomenon we're seeing are a function
of what we're doing to managers in tech and how we're building out our organizations.
Such an interesting point. Whether we do it now or next time, just looking at these metrics for managers, like how much more burned out are they, how much less happy and optimistic are they, would be really interesting. There's a couple notes here in the actual post that I want to highlight that I thought are really interesting. One is just the core takeaway here is the biggest lever you have to increase retention in your company is improve your managers, connect people with better managers basically. So interesting. That's like a thing you can do, obviously easier said than done, but that's the biggest lever of things you can change. And then the other thing you noted is the worst-rated managers cluster in data analytics and design. Poor design.
Yes. So, and I'm not sure there's a clear explanation for that. I think one possible explanation is that, again, you know, managers are just people too, and so design managers and data and analytics managers are in design and in analytics, they are suffering clearly based on what we saw. And I think it's hard to separate how you feel in tech from your job as a manager. It's hard not to put some of your negative energy onto your team and the people you work with. And so I have a lot of empathy for design managers, research managers, data and analytics managers, and other managers in tech who are having a hard time right now and they're not feeling energized. And unfortunately, some of that is being pushed on to their direct reports.
And then I very much appreciate in some of the companies I've worked for having the opportunity to go through manager training, which is something that's still all too rare, I feel, within organizations. If you're listening to this and you're a leader in an organization, if you're C-suite at a company, please invest more in your managers. And if you're looking for a job right now, consider carefully who your manager might be, because probably nothing will have more impact on your well-being than who that person ends up being.
And to build on how difficult things are for companies right now, the level of poaching and offers thrown out at the best people, just imagine how sucky it is to find a great manager, train people to become awesome managers, and then they get, you know...
Only to lose them.
Only to lose them to, you know, the labs, people with infinite money. So, it's just extra hard. Which is a good segue to our final takeaway, which is a really good summary of just what people are feeling right now.
Yeah, it is the wildest it's ever been. We asked people to describe the state of the tech industry right now. We got thousands of responses. These were essentially open-ended responses, and we just sort of clustered those descriptions into this word cloud. I still love word clouds. Some researchers are sort of anti-word cloud. I love... I'm not gonna apologize for the word cloud.
No, this is amazing.
It's like such a clear... Look at this. Just look at this. This is exactly what it feels like.
Yeah. We're seeing change. We're seeing chaos. We're seeing speed. We're seeing excitement, flux, hype, a lack of stability, a potential bubble, but also crazy opportunities. Everything's evolving. Everything's unstable. It comes with costs. It's better. It's worse. It's huge. It's confusing. All smooshed together into a more chaotic industry than it's ever been. I don't understand anything about baseball, or maybe it's cricket, but we got this quote. Do you understand baseball? Does...
Hopefully if you're watching you understand these things, but we got this quote: "We're in the second inning of a massive shift. No one knows how it will end, but all you can do is keep taking at bats." Is that a cricket thing? A baseball...
That's baseball. I don't know how many innings. I don't know if there's innings in cricket, but it's definitely baseball. It works for baseball at least.
Yeah. Basically, it's just saying keep trying. Just keep taking shots. Shots on goal. A lot of metaphors.
Yeah. So many good quotes. Another one I see here which was a good one: "Tech is manic. Half out of touch, clinging to the bandwagon, porbing into the overhype. The other half are exhausted by the first half." That came from a senior PM. Yeah, fascinating stuff.
When we look at this overall, it's crazy how we see again this bifurcation, that 37% of the words used when we ran sentiment analysis were positive, 37% were negative, and the remaining 26% or so were neutral. Basically, an even split. We're all seeing the same thing, but half of us find it thrilling, the other half find it terrifying. I was, you know, rather taken aback when I saw these data. It's pretty wild how equally divided we are.
Yeah, man. And I think you used this quote earlier that this is the most normal it's ever going to be.
I mean, I don't know. The prophecy was given to the fool, so I'm not going to try and be a prophet. But yes, I doubt it's going to get, you know, more normal and normalized statistically than this. So, we'll wait and see, I guess.
Yeah. Like, if we zoom out, we're living through history right now. The amount of change, and like, this is unprecedented. You know, the industrial revolution is always the metaphor people use, which is accurate. Maybe crazy or maybe not, but that's the interesting part. Like, what an interesting time to be living through. Elon had this really interesting way of describing it. Like, we're definitely living in a simulation if we're alive right now when we're about to start building data centers in space and AI is going to be as smart as human brains. Like, what are the chances you are alive at that moment? Which is probably, okay, maybe some higher intelligence is simulating the most interesting time in history. I don't know if that's a good rap, but...
Listen, I have a lot of respect for Elon. People like Elon have chosen to focus on the universe and what's out there and the laws that govern the universe, and that's their focus. I became a psychologist, by academic training at least, because my focus has always been on people.
And if I had to share a closing thought to wrap up all of this research, I would say that having the most advanced AI and the access to the best models in the world won't determine whether your organization succeeds. We have to remember that underlying all of this stuff are people. We as people are going through the most massive shift and changes that we ever have in our lives. And it's people who are feeling excited and exhausted and hopeful and scared, often all at once. And we're all taking part in crafting and building this future that we hope still has a place for us in a few years.
And so I keep that in mind all the time. It's people driving these innovations. It's incredible people building these technologies. My focus will always be on the people. And I hope that if you're out there watching this, you take care of yourself. You touch grass. You take a moment to reflect on what you want for yourself in your career. And you remember again that it's fine to feel all of the emotions, and you should just do whatever works for you to get through this wild period in the tech industry.
So, kind of building on that, you spend a lot of time thinking through the results and what people can actually do with this data, because it's one thing to just report, here's what people are feeling. Okay, cool. What should people do? So, there's a really important section at the end of the report that we should spend a little time on, which is just where do we go from here? What does this tell us we should be doing, if we can do anything, to kind of move ourselves basically into a happier place?
So starting with if you're an employee, you know, especially if you're an IC working at a company, one thing we saw people who feel amplified and energized reporting is that they actually went deep on specific tasks and specific jobs to be done rather than trying to be the generalist who does everything. I think it's the people who try to be, or lean too much into being, a generalist who end up getting severely burnt out, right? And so I just want to caution people a little bit away from the narratives that you need to be a generalist at this point and just do all of the things and completely ignore the core parts of your role. I think that's a bad idea, and based on what people are reporting, it's not going to end up with you at least feeling good, right? I also would love for people to watch out for this squeeze, being overworked for the same pay. We deserve better. We've linked in the article to a burnout test. Take the test. See where you're at on the burnout scale. And then, you know, based on that, reflect on where you are. Talk to your manager. Scope out your work again. You know, recalibrate, realign with your manager on your work, and make sure that you're not being squeezed out of, you know, being positive about your role and being successful in your role.
As you're going through this list, let me just make sure people fully understand the frame, because you made these two buckets, basically things you can do based on these results. One is just if you're an employee, I think you have five pieces of advice. If you're a company, you have five-ish pieces of advice. So, just to be super clear, the first one is just pick a couple things you want AI to be useful for and just go deep on those couple things, versus trying to spread it all around and AI has to be doing everything for you. Pick a couple things that you're most excited about and then just go really deep there. The other is this, what you said, just watch the squeeze. Watch you being squeezed and talk to your manager about, hey, my scope's increased, nothing's changed comp-wise, that kind of...
Absolutely. And then speaking of managers, again, the third point is that your manager clearly matters more than pretty much anything else when it comes to how you feel about work. Protect that relationship. Invest in that relationship. Build up good communication lines with your manager. Learn to manage up. That investment in that relationship will pay off greatly in terms of how you feel.
And then beyond that, first of all, if you want to try out working for a smaller company or starting your own company, clearly there are some advantages to that, and so it might be worth considering. And then if you're earlier in your career and you feel like the rungs of the ladder are slowly disappearing and it's becoming harder to climb that ladder, I'm a huge believer in mentorship and the value of mentorship. Strong mentorship is still an incredibly effective thing. Seek the teams, seek the managers, seek the people who are willing to invest in developing you. It's incredibly valuable, especially in this era. So that's what we have for employees.
And then if you're leading a team, if you're leading a company, then again, as we mentioned before, invest in your managers. It's probably some of the best money you'll ever spend. It's sad to me that only a quarter of our sample, and perhaps tech workers in general, rate their manager as highly effective. That to me is a major red flag. It's a major issue in tech. And so if you want to improve burnout, if you want to elevate enjoyment, if you want to improve retention with these crazy job offers flying around from AI labs, you have to invest in your managers.
And then otherwise, manage that squeeze. People are feeling how AI is raising bars in ways that aren't sustainable. So you have to figure out the right level of expectations and the right level of productivity. Don't let that bottom rung of the ladder rot. You know, make sure that you're doing what you need to for entry-level people to advance, because those early career people are also probably some of the most AI-native people you can find, right? They find it very natural to use these technologies, in some ways more so than people who have been, you know, too used to previous paradigms. And then, selfishly, I hope that leaders pay a little bit more attention to design and research and other roles who are feeling more negative than other roles. And keep in mind that this technology, AI, is lifting some people and destabilizing others. And you really have to pay attention to that. We are clearly not experiencing this technology in the same way.
Amazing takeaways. I want to double down on that burnout survey that you mentioned. We're going to link to it in the show notes, but people, like, it sounds dumb, and why am I going to do that? I've definitely gone through periods of burnout and wasn't aware that that was happening, and it's so helpful to be like, oh wow, this is not normal, what I'm feeling right now. And knowing this, that, okay, you're extremely burned out right now, then you can decide what you want to do with that information. Often it's, you know, talk to a coach, talk to your manager, take some time off if you can. But just knowing that is actually really powerful, and he made this really great quiz based on actual science and research that we'll link you.
100%.
Awesome. Now, is there anything else that we haven't talked about? Anything else you want to leave folks with? We've covered a lot, so I don't know if there's anything left. We'll obviously link them to the report where they can go deeper. We're also going to do a follow-up based on what comes out of this conversation, what we see in the comments, because this is a lot of information and a lot of scary stuff, some optimistic stuff. We're not gonna have answers to everything, but we're planning to do a follow-up of just, here's what came up, let's see if we can find any answers. But other than that, is there anything else that you want to share?
There's one interesting phenomenon that I wanted to mention. We're starting to see this AI guilt, and in particular amongst people who are early in their career, in the sense that people who are early in their career feel like leveraging the technology is a little bit like cheating, in a sense, and that guilt declines with seniority. And in particular, we're seeing people in, actually, product marketing and data and analytics, which showed up previously in a couple of places, feeling the most guilt.
This is related to the well-known and well-established impostor phenomenon, right? Like, I'm not good enough. Competent people feeling like their success isn't really theirs, it's someone else's. Except this time we're putting that on AI, on a technology, rather than other people. I would say to all of you who might be feeling that guilt, AI is an incredible technology. Leverage it. Learn how to leverage it. I doubt it's going away. It's the worst it's ever going to be today. It's only getting better. So there's no reason to feel guilty about leveraging it. On the contrary. I think inevitably we all are, all the time. So...
Well, to close, I just want to appreciate you. It's incredible, the work that you've done here and the work that we've done together over the many surveys. It's just like a side thing you do with me, running, like, I don't know, one of the biggest surveys out there around this stuff, maybe the biggest, analyzing it, writing it so beautifully. So I think this is a really unique and special report, and I appreciate you for doing this with me. I'm really happy about where this all goes and just what we're doing for folks.
Thank you so so much.
Well, with that, Noam, where can people find you online if they want to reach out, maybe follow-up questions, and how can listeners be useful to you?
Yeah, so the best places to find me are on LinkedIn. I'd love to connect with anyone who wants to connect on LinkedIn, or within Lenny's community, within
your Slack. I hang out there and always happy to talk to people within the community. So please catch me on LinkedIn or on Slack. That would be best.
How can listeners be useful to you, Noam?
If you're watching this, what I would like to convey is that I hope this research has been helpful to you and more than anything I hope that you consider participating in future research projects of ours. I'm really, really glad that we get to do these things, Lenny. And I want to give all of you watching the opportunity to learn more about what's going on in tech, how you can be better at your job, you know, how you can feel better about your job and all things in between.
We plan to continue conducting both quick polls of the community, in-depth longer form surveys, interviews, all sorts of things. And so if you get a message, an email, a Slack about a research project, please participate. Would love to hear your voices, hear your perspectives, and then share that back with the community. And hopefully it makes us all better at our jobs and also feel better about our jobs because I do hope that even though much of this was a little bit tough and perhaps negative, I too, Lenny, am an eternal optimist. I'm a techno optimist. I believe this is going in good directions and I want to make sure we capture that accurately. So yeah, please participate. We'd love to see you in our next research project.
Excellent. And with that, Noam, thank you so much for being here. Thanks a bunch.
Thank you so much for listening. If you found this valuable, you can subscribe to the show on Apple Podcasts, Spotify, or your favorite podcast app. Also, please consider giving us a rating or leaving a review as that really helps other listeners find the podcast. You can find all past episodes or learn more about the show at lennyspodcast.com. See you in the next episode.
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