About What Andy Said…

“The announcement that we made a few days ago was not really financially driven, and it’s not even really AI-driven, not right now at least. It’s culture.”

That’s what Amazon CEO Andy Jassy said after the layoffs last week. Ignoring its tone-deafness (for now), I want to question the “culture” bit.

Long ago, I worked in the same building as Jeff Wilke. We often chatted in the elevator, usually on the way up from the parking garage. He was the CEO of Amazon Retail, and the #2 Jeff at Amazon.

I attended Jeff Wilke’s seminal talk on “a culture of and.”

Most companies are cultures of or. Add new customers OR improve customer service. Create loyal customers OR charge for luggage. Companies that “are the industry’s best X” usually thrive by sacrificing one thing to be the best at another. Airlines are the obvious example. Cell phone companies. Grok. Starbucks. Krispy Kreme Donuts.

But Wilke believed that the most successful companies were the ones with a culture of and. That’s why Amazon wanted the best prices AND the fastest delivery AND the best customer service.

Wilke explained that Amazon’s leadership principles were intentionally constructed to create a culture of and. They’re SUPPOSED have tension.

Every single one contradicts at least one other. Some even contradict themselves. That’s the point.

Amazon pushed to do it all. Delivering results with low standards was as bad as not delivering results because we kept the standards high. Bias for action without diving deep was an anti-pattern, and a sign of a disengaged leader. Having backbone was actually bad if you wouldn’t also commit.

Last week, Andy said, “It’s culture.”

His culture isn’t the culture that I learned from Jeff Wilke.

If I were to chat with Andy in the elevator, I’d ask: where in the leadership principles does it say that leaders lead “the world’s largest startup?” Where is “flatness” mentioned?

I’d point out that leaders earn trust. I’d say that leaders hire and develop the best. I’d refer to being earth’s best employer, and how leaders shoulder the responsibility of being better, and doing better, for their employees.

I’d tell him that when I think about what Amazon culture used to be – the one that Wilke advocated for – it was about ALL of the leadership principles, and the culture of and.

And I’d tell him that the “culture” that he’s fostering is a culture of or, instead of a culture of and.

PS: I personally knew several 10- and 15-plus-year veterans that he laid off last week. I’d also mention that implying that they were somehow bad for Amazon’s culture is not only tone-deaf, but downright mean.About What Andy Said…

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More on the Amazon Layoffs

So my last post went viral (thanks reddit!), and I appreciate the comments & feedback. Anyone looking for a good boss should check my post history on LinkedIn.

I received some interesting questions! Some I already answered on my website, arneknudson.com, but here’s one of the big ones:

If the reason for the layoffs isn’t post-COVID downsizing, and isn’t optimizations from AI, then what is it?

To answer that, a disclaimer first: This isn’t investment advice. Take no financial action based on this. It’s my opinion, with little actual evidence, and layered with dollops of speculation. E.g., I might WILDLY speculate that the cost of each corporate employee is $500k/year in salary+benefits+stock; ergo, cutting 30k of ‘em saves about $15BB/year.

So… why layoffs?

It comes down to Free Cash Flow (FCF). Amazon wants cash in hand.

First, GPUs are expensive. AWS is feverishly reallocating space to GPU racks. Tying up cash in infrastructure is a hefty negative to FCF, until you sell it.

Second, Trump’s economy is hurting both Amazon Retail and AWS.

Amazon Retail (both 1P and 3P) is disproportionately affected by tariffs. Case in point: when Trump eliminated the de minimis exemption, it destroyed the small 3P sellers. Amazon monitors 3P sales and, if sales are good, they’ll buy their own supply and undercut their price. But killing de minimis killed the small sellers. Amazon stopped competing, and entire product segments went “out of stock.”

Similarly, every time there’s a random tariff announcement, huge ships literally stop in the middle of the ocean and wait for Trump to go TACO. That’s a problem for the lean machine of Amazon Fulfillment.

As for AWS? It’s disproportionately affected by a downturn in the tech economy. When tech companies cut costs or go out of business, AWS’s YoY growth shrinks. Sure, AWS will be making money hand over fist on GPUs. But if AWS loses revenue from struggling non-AI businesses, they can now offset about $15BB of that. Why? So they can keep up their FCF.

Amazon released earnings last night. Mega profits, bigly sales, stock price go brrrt, yay! But check out this slide, which is slide 12 from Amazon’s Q3 2025 earnings call slide deck:

FCF is cratering, and if the trend continues, it’s going to be about $3.2B in Q4, and NEGATIVE $5.5BB in Q1’26. (To be clear, Amazon reported ~$61BB in cash & equivalent holdings; so a negative FCF means that number will start to go down, NOT that they’re going to go into debt.)

I believe the economy is hurting Amazon Retail and AWS. And while exploding GPU costs are a problem, I think the layoffs are mostly about offsetting the tariff-related costs in Retail, maintaining AWS’s high FCF, and maximizing cash in hand for the next 12-18 months.

And maximizing cash in hand NOW is a big ol’ red flag for what Amazon thinks about the economy.

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You Gotta Do What Makes You Happy

Apologies – this post originally went up on LinkedIn back in late August, and … then I left it in draft here, while publishing it there. Catching up!


Anyone that’s worked for me knows I have phrases that I say I lot. Maybe mantras, or if I’m being overly generous to myself, witticisms. But if you ask them, they’ll probably tell you my most repeated mantra is: “you gotta do what makes you happy.”

This has two distinct meanings. The first, which is from a personal standpoint, is that you should find something that you really enjoy doing. One way to know “is this what I want to do” is to ask yourself, “do I enjoy it even when I fail when doing it?” There’s usually a lot of ways to fail at something, but only a few ways to succeed. The people that really enjoy a job are the ones that aren’t afraid to experiment, and aren’t afraid to fail, because they get to learn more, so they can do even better (and have more fun!) next time. Another way to know is to consider whether you feel happy going to, or coming home from, work. Some people get a lot of happiness from accomplishment, and that’s great, because you should feel happy when you come home from work. But you should really find a job where you feel happy going into work. You should be excited about the possibilities, not just the consequences.

I used to feel happy going into Amazon, and being a leader, but a lot of senior leadership’s recent decisions made me unhappy about coming into work. I enjoyed helping people, I enjoyed getting releases out, and I enjoyed helping my team get to the lowest ops load in the org. But I didn’t feel proud, or happy, talking about the job with other people. It’s one of the reasons I left, and it’s also why I’m now writing more – I know I’m reasonably good at it, but even though I’m not the best, I’m enjoying doing it. I’m enjoying writing my blog and my books, and ultimately, it’s fine with me whether or not a lot of people read them.

The second meaning of “you gotta do what makes you happy,” which is from a leadership perspective, is that unhappy people are less productive. When people are unhappy, they’re going to seek out things to make themselves happy, which means they’ll be spending some of their time watching TikTok videos, going for long lunches, reading social media, or checking up on their fantasy football team. Those people will always be less productive than their own best selves. If they’re superstars (see my earlier post about how talent is a power curve), they may be more productive – even when distracted – than anyone else on the team. But our goal, as leaders, is to get the most out of every person on the team, over the long term.

So as a leader, one of the consequences of believing that I want my people to be happy is that I never begrudge someone leaving my team. If they do, it means (hopefully) that they’re trying to follow their passion, and therefore, I SHOULD HELP THEM DO IT. I tell people to not let the fear of change dissuade them from trying another team, or another role. I’ll have an article later about how not to be afraid, but for now, focus on whether your tentativeness about changing roles is fear of the unknown, or disinterest in the new challenge. The former is normal, and you should ignore it; the latter is bad, and you should listen to it.

I’ve helped many people on my teams move on, and I’ve kept good relationships with them afterwards. Some have even come back to work for me later!

Now, you might be thinking, “what if I don’t like how hard it’s gotten for me recently?” When people come to me with this issue, I first try to understand what’s causing the stress, and see what I can do to help. Depending on the circumstances, one possible piece of feedback that I give them is that you should NOT be afraid to stick it out when things get tough. If you search for articles related to “grit” and how perseverance can lead to better long-term mental health, you’ll find things like [https://www.sciencedirect.com/science/article/abs/pii/S0191886918304409], which found that “perseverance promotes greater resilience to depressive symptoms by enhancing positive self-conscious emotions (e.g., authentic pride) and positive self-valuation (e.g., sense of power).” Or, in [https://link.springer.com/article/10.1007/s10902-020-00343-4], where they found the “positive relationship between grit and subjective well-being is largely driven by the perseverance dimension of grit.”

In other words, if you like doing something, but it gets hard, you should try to push through it, and learn from it along the way. In the long run, you’ll probably end up happier, and proud of the fact that you persevered.

But on the other hand, if things are hard for reasons NOT related to the work, and grit’s not going to solve the problem, good leaders are able to listen, and ask good questions, and then act appropriately. Too many managers lean too heavily into the techbro-style leadership of “you just need to work harder” or “suck it up,” which can be incredibly damaging feedback.

So when I have my one-on-ones with the people that work for me, I often start with: “are you happy?” Good leaders need to create an environment where people are comfortable enough to respond with honesty. And when they ask the question, good leaders listen carefully and compassionately to the answer.

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Another viral LinkedIn post

I’ve had another one of my posts on LinkedIn go viral: https://www.linkedin.com/feed/update/urn:li:activity:7388737736590909440/

Turns out, part of the reason why is because I’ve become internet famous: https://www.reddit.com/r/jobs/comments/1oicvgs/18year_amazon_veteran_ive_never_seen_layoffs_this/

I’m amused by the number of people that don’t believe that I’m as old as I am. Or that think that AI didn’t exist 25 years ago. It’s even more funny to me, because I often make the joke of saying “I graduated back in ’94, with a degree in AI, because that’s what they called it back then.” (Yes, it’s a nerd dad joke, but I’m a dad, and a nerd, so I get a pass.) It’s playing off the idea that the term “Machine Learning” didn’t exist until recently, but “AI” has been around for a long time. Neither of which is true, really; both terms were coined back in the 1950’s.

Maybe we should start an “I’m so old” contest in the comments? I’m so old that I still have my childhood Osborn 1 in my store room. I’m so old that the first computer game I 100%’d was Zork II. I’m so old I remember the smell of mimeograph ink. I’m so old that I know the tings and pings of a 1200 baud modem, and I know what baud means. And I’m so old that the textbook for my college AI class was a stack of laser printer printouts of a draft of the professor’s friend’s pre-print book, because there pretty much wasn’t any other AI textbooks available, yet.

My profile on LinkedIn is up to date and accurate, by the way (as of October 28, 2025). Maybe I should add “concentration in Artificial Intelligence” to my degree blurb?

I’m going to copy-paste the contents of the LinkedIn post below (obviously without the comments). I encourage civil discussion, and I’m happy to answer any questions. Enjoy!

And, because I’m fair and honest, I will concede one potential misstatement: my direct experience with layoffs at Amazon goes back as far as the financial crisis of 2008. But I also worked in tech during the .com bubble, and I did a lot of interviewing for Amazon in 2008. So when the 2008 crisis rolled around, and we had a hiring freeze, I asked my more wizened peers about the last time something like it had happened – which was the .com crash. They said it was bad, but only for a little while. So I concede: (1) my experience with how Amazon fared during the .com crash was first-order anecdotal (meaning I spoke to colleagues, who were there during the crisis, AFTER the crisis, about their memories of it); and (2) my direct experience started with the financial crisis in 2008.

I maintain that during my tenure (and based on first-order anecdotes from before it), and until now, I don’t believe that Amazon ever had a period where there were layoffs for multiple years running.


In my 18 years at Amazon, I went through a few layoffs and hiring freezes. This is the first time I’ve seen multiple years of significant layoffs essentially back-to-back. Even in the depths after the .com bubble, it wasn’t this bad. They’ve been laying people off now for almost 3 straight years.

The explanation that this is downsizing after hiring too many a the height of the pandemic doesn’t pass the smell test, at least to me. That was 3 years ago; they’re not that dumb to keep those people around for 3 extra years. Those folks were laid off back in ’22.

I’m also not convinced that this is optimizations due to AI. My degree’s in AI, and I worked on AI stuff at Amazon; I don’t think there’s enough automation yet, and it’s not accurate enough yet, to replace 30,000 people. The cost of inaccuracies seems too high. But I could be wrong; maybe they’ve gotten their false negative & false positive rates low enough to avoid too many region-wide AWS outages. (Or not.)

One of the articles I read said this was going to be in HR, and I can tell you as a former manager, my experience working with HR had been steadily worsening over the past 5-7 years. They outsourced so much of the work, overworked the people they had, and had such high turnover that I never knew who I was supposed to work with. When I needed to put someone on a performance plan or help a new hire receive some kind of accommodation, it seemed like it was a different person each time. If they really are laying off tens of thousands more HR folks, this is only going to get worse.

And, I suspect, it means they don’t plan on hiring MORE people – in any of the business units – for a year or more.

So, by the smell-o-meter, this seems more significant than streamlining workforce, improved AI, and “nah, we don’t need as many HR folks.”

If you’re an Amazonian, and find out tomorrow that you’re soon to be a former Amazonian, let me know, I’ll be happy to chat. It’s a weird world out there these days. Good luck, my friends!

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Amazon, Salesforce, and (American History) X

First off, apologies for missing the last couple of updates. I was working on query letters for book 1 in my series, while simultaneously finishing book 2. The good news is that the first batch of query letters are out, and now I’m waiting; the better news is that I finished a complete first draft of book 2, and I’m now working on the editing. Ping me if you’d like to read it and give me feedback, or learn more about it!

Second, earlier this week, I saw one of my LinkedIn connections’ post, saying goodbye to Salesforce. His farewell post reminded me of my own, when I left Amazon earlier this year. In his, he called out Salesforce’s CEO Marc Beninoff, who said that the Orange Cheat-o should send the National Guard into San Francisco (in clear violation of the posse comitatus act, since he specifically said he’d be “all for” the military being cops). Then, a few days later, it became public knowledge that Salesforce made a pitch to ICE. Specifically, they offered AI tools to help ICE staff up quickly, as well as other services.

My connection bravely stood up for what he believed in, gave his notice, and left his job without knowing what was coming next. I applaud his courage, and wish him the best.

I’ve noticed several connections leave Salesforce in the last few weeks. He was the first one I saw who specifically called out Beninoff’s craven capitulation as his justification. It made me wonder how many others left for the same reason, but weren’t comfortable saying so.

Personally, I’m not going to look towards Salesforce as a potential future employer, and I discourage others from doing so.

This also made me think about a lot of tough questions, and I’m curious about what y’all think.

The first question is: how do we categorize and document which companies are bending the knee?

Second: how can we fight back against them? I’ve already canceled my Disney+ account. I locked down my Facebook account, deleted my Twitter account, and moved to BlueSky. I’m not going to work for any of those companies, and I won’t be using their services. What else can we or should we do? (And I’m only asking for legal options.)

And third: when the dust settles, and if there is justice to be found in this world, what do you think the repercussions will be for those like Bezos, Beninoff, Ellison, Musk, Thiel, and Zuckerberg? The ultra-rich who abused their power and wealth to gut the social safety net, promote racism and transphobia, and subvert democracies around the world – what’s justice for them?

History, I hope, will mutter their names in the same breath as Henry Ford and Fritz ter Meer. But the near term? Sadly, probably nothing.

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Comet C/2025 A6 (Lemmon) (and Some Other New Stuff)

Comet C/2025 A6 (Lemmon) made its closest approach to Earth on Tuesday, October 21st at just under 0.6 AU – so about half the distance from the Earth to the Sun. I had a clear night last night, and was able to capture some pretty good shots. I had a very hard time keeping tracking – it was very low on the horizon, and it was a humid night with a lot of atmospheric distortion. I only got two shots that were able to keep track for longer than 10 seconds. I included the first one because I think it shows the best true-color representation: a slightly blue-green coma with two distinct tails – one dim and diffuse, and the other sharp and narrow.

The other distinct feature, visible in the last of the 3 images, is how fast the comet is moving relative to the background stars. Compare it the 4 minute picture to the 8 second picture, and you can see that the bright center of the coma moves up and to the left about 2 to 3 times its apparent width over the course of only 4 minutes.

This creates two interesting feature requests for Unistellar: 1) let us take time lapse movies. Maybe 10-20 second stacks per frame, so you get a nice bright resolved image? If that was possible, you’d DEFINITELY see the comet moving (and probably even the tail!) in the 3rd image. 2) I wish the auto-tracking software would give you the option to track the motion of the COMET rather than the motion of the stars. This comet was NOT in the Unistellar list of targets, so I had to manually enter the right ascension and declination. This was fine, but if it HAD been in the catalogue, then that feature would’ve been awesome. If that were the case, then the 3rd picture below would be a beautiful well-tracked image, and the stars would be slightly streaky – which is a fair tradeoff. I’m sure this isn’t an easy feature, but it would be a very cool one.

As always these will be added to the Solar System Objects and Nebulae pages. Enjoy!

Comet C/2025 A6 (Lemmon)

8s

2025-10-21

The best “short” shot I got of it this night, showing what it would look like if you used a pair of binoculars (which I also did). The tail was VERY long – about 3 or 4 diameters of the moon, I’d estimate.

Comet C/2025 A6 (Lemmon)

2m

2025-10-21

The first of the two decent dwells that I got, showing a beautiful pair of bright tails.

Comet C/2025 A6 (Lemmon)

4m

2025-10-21

You can really see how fast the comet is moving relative to the stars – compare the wide bright line at the center of the coma with the smaller circular dot from the 8s shot above.

NGC 7023 – Iris Nebula

56m

2025-10-22

This is another one that the Unistellar catalogue doesn’t have good data for, and you have to force it to go find it. I’m glad I did, because this is a very beautiful nebula.

M1 – Crab Nebula

13m

2025-10-22

This nebula was the result of a supernova in 1054 C.E. which was observed and documented by cultures from Central America to Asia. It’s a nice little supernova remnant, and it’s actually bright enough that you can see it pretty easily with binoculars.

Ceres

2m

2025-10-22

I’m not sure which of the dots in this picture is Ceres, but one of ’em is. I’m going to try to get another picture of it in the next few days; if I can, I’ll try to overlay the pictures, and if we’re lucky, we’ll get to see it move.

Comet C/2025 R2 (SWAN)

7m

2025-10-21

My second attempt to catch Swan in about a week, and this was about as unsuccessful as the first attempt. Either I’m missing it entirely, or it’s really small/dim. I think I might be missing it.

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Looking for an elephant, and finding some new clusters

Finally! It’s been weeks of high clouds, rain, smoke from forest fires, and nearly everything else imaginable that’s prevented me from getting the telescope back out on the back porch. But a few nights ago, we had a big thunderstorm roll through (which is quite rare for Seattle, actually), and the next day, we had clear blue skies. I’ve had two good nights since then, and I took advantage.

I’d tried a couple times to hunt the elephant, unsuccessfully. This time, I’d done my research. I wanted the exact right ascension and declination of the key part of the elephant’s trunk nebula, and one google search later, found this: https://noirlab.edu/public/images/noao-ic1396hapeman/ … which led me to the WorldWide Telescope, which is AWESOME.

By using that tool, I could figure out the exact coordinates, and I plugged ’em into the telescope, and told it to start a long dwell. It came up with this:

IC1396 – Elephant’s Trunk Nebula

53m

2025-10-13

It’s the right spot, and it’s a long dwell time, and you can baaaaarely make out the hints of a nebula.

Compare that to online pictures of the nebula, and you’ll get a sense of my disappointment.

If I were to speculate – and it’s pure speculation – I’d guess that the Unistellar Vivid Vision Technology (VVT) software is programmed on the basis that “the background is black,” rather than – as in the case above – “everything in the background is slightly red.” The elephant’s trunk nebula is HUGE – about five or six times the angular size of the full moon – and so ALL of the sky in that area is slightly red. As a result, you get pictures like the one above – some red highlights, and you can tell that it’s kinda there, but not a great nebula picture.

The other speculation (and it’s possible) is that the nebula is REALLY dim, and I shouldn’t be surprised that I’m not getting a great photo of it from the greater Seattle metro area. Which do you think? I’m not sure.

I was happy that I could put that one to bed, though – I now know that I’m not likely to get a better shot of the nebula in the near future.

But it was two clear nights in a row, with no moon, so … more pictures!

M71

5m

2025-10-13

The M71 globular cluster is a new one for me. It’s only about 27 light-years across, and is about 13,000 light-years away.

M15 – The Great Pegasus Cluster

6m

2025-10-13

M15 is one of the most densely packed clusters in the Milky Way, with over 100,000 stars inside a diameter of only 175 light-years. Its bright center is a dense sphere of closely-packed stars, possibly orbiting a central black hole.

NGC 0247 – The Claw Galaxy

25m

2025-10-14

I think it’s called the claw because of the large void on one side of the spiral disk – and you can see it here. I think another attempt, with a longer dwell (this one got interrupted) might be worthwhile.

NGC 7000 – The North America Nebula

35m

2025-10-14

This might be the new elephant – the North America Nebula is about 3 to 4 moon-widths across, and I just picked a spot inside it and took a picture. Turns out, I picked one of the most boring spots. Note to self: next time try 20h58m25s / +43:24:26 or 21h00m21s / +43:53:23.

Comet C/2025 R2 (SWAN)

11m

2025-10-14

I’m not sure which one of these smudges is the comet. I created the before-after below with what I think is the comet circled, but … yeah, I might be wrong.

Comet C/2025 R2 (SWAN) — maybe?

M110

5m

2025-10-13

Not a great photo – it cut off after only 5 minutes (I’m not sure why). M110 is a dwarf galaxy orbiting / interacting with the Andromeda Galaxy (like M32).

M2

8m

2025-10-13

M2 is a dense little globular cluster in Aquarius. It’s both one of the oldest (about 12.5 billion years old) and one of the largest (175 light-years in diameter) clusters in the Milky Way. It’s possibly part of an ancient galaxy that collided with the Milky Way 8-11 billion years ago.

As always, the above images will be added to their respective pages.

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What To Do When Things Go Wrong

Another one of my mantras (witticisms? Sayings?) is:

People don’t remember what you did when things were going well. People remember what you do when things go wrong.

If a leader walks up to your desk and things are going great, then they usually don’t remember the interaction. But if they walk into your office because the website is down, they’re definitely going to remember how you behaved, how quickly you solved the problem, and how you kept the problem from ever happening again.

Many people have told me that I’m calm and focused during a crisis. This is partly because of this mantra – people remember what you do when things go wrong. But it also goes back to my childhood.

I was an excellent swimmer (e.g., I set the all-time record on my community swim team for the 14-and-under 50m breaststroke). And excellent swimmers become lifeguards. And lifeguards learn CPR and first aid. And the relevant bit – how to focus in a crisis – has stuck with me.

Within the professional setting, I learned that when things go wrong, that’s the time for you to think very hard about what the BEST thing you can do is, and then DO IT. Don’t let fear hold you back or drive up your anxiety. Don’t hesitate, but be slow, thoughtful, and calm. In a crisis, slow is smooth, and smooth is fast.

And I also learned that the best way to deal with a crisis is to be prepared for it, train for it, and make dealing with it routine. That’s the reason that CPR has a book, and why ER doctors ask you what day it is when you roll into the room, and critical software systems have disaster recovery plans.

Good leaders invest time to ensure that your best practices and SOPs are well documented. Ideally, get them done before the code goes live, but realistically, as soon after the launch as you can. Document what you should do when things go wrong, BEFORE they go wrong, because they will go spectacularly wrong.

The first and most important thing is “stop the bleeding.” On the internet, this usually distills down to “never roll forward; always roll back,” because 9 times out of 10, that’ll stop the problem. Yes, it means that feature you rolled out earlier today isn’t live anymore, but hey, the checkout page is back, and we’re back to selling products, so that’s a good thing.

During this phase, don’t ask why it happened. Don’t focus on finding the bug in the code, and don’t try to blame someone for writing that bug. Sometimes, yeah, you need to understand the bug to understand the problem. But most of the time? Roll back the deployment. Get to the last good state. Stop the bleeding.

But sometimes rolling back isn’t an option, or doesn’t solve the problem. In those cases, take in all the information available. Scour your dashboards. Listen carefully, find the thing that smells fishy, and relentlessly poke at every assumption. When you’re brainstorming hypotheses, look for one that explains more symptoms than the others. Then look for other signs and symptoms that would be related, if that hypothesized root cause was true. If they’re there, then you’re closer to truth. If not, try another idea. Again, your goal is to stop the bleeding; prioritize the thing that does that.

Once you’ve stopped the bleeding, then start doing the investigation into why it happened. This can happen right away, or the next day, or during the next ops review meeting, but it has to happen. If you want to learn how to do that, check out the “5 whys” [https://en.wikipedia.org/wiki/Five_whys] for a great summary. Amazon uses the 5 whys because ultimately, you need to be able to ask, and then answer, the real question: how can we do better next time, or ideally, keep this from ever happening again?

To answer that question, you’ll have to ask others: What changes to our processes should we make to prevent a recurrence? Did the SOP tell you how to identify the root cause? Did it tell you how to stop the bleeding? Was it clear enough for you? Do we need to update it? If things had gone worse, how would they have done so? Assuming that worst-case scenario, what should we do that we didn’t do this time?

Every time an engineer gets paged due to an issue, as a leader, you should ask those questions. My goal was always to create a culture where we get paged less often next week than we did this week. This kind of continuous improvement means that two weeks (or six months, or two years) from now, we’ll be building new code, rather than fixing the code we’re writing today.

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Don’t Be Afraid

Another one of my mantras is: don’t be afraid. It’s easy. I tell it to myself all the time. When I get worried, or stressed, and I’m not sure what to do, I’ll tell myself: don’t be afraid.

Why? Because fear is an overweight counterbalance in the risk equation, and measured risk creates progress. When you give into fear, you’re sacrificing potential for comfort. You’re giving up the long term for the short term. You’re saying safe is better than awesome.

Don’t be afraid…

… to ask questions. Questions are the best way to learn. It’s not showing that you’re stupid, it’s showing that you are curious and want to do the right thing.

… to look for answers on your own. You’re getting paid to solve problems. Getting better at the meta-problem of how to solve problems is the best way to create long-term success.

… to try something that you’re not sure you can do. We grow by getting slightly outside our comfort zone, trying something new, and learning from it.

… to ask for help. Nobody can solve every problem. Not all problems can be fixed by one person. Your boss’s job is to help remove roadblocks and obstacles. They can’t remove obstacles that they don’t know about.

… to try to do it on your own. You’re usually more capable than you think. Even if it’s scary, it’s usually the fear that undermines your success, not your skill.

… to make a mistake. We learn from our mistakes. Good leaders embrace mistakes as learning opportunities. Bad leaders criticize or fire people that make mistakes. If they do, it’s their problem, not yours.

… to escalate. If you think you’re right, and they’re wrong, push it up a level. If a peer manager is blocking you, escalate to their boss and your boss. Talk to your skip-level manager if your boss is being a bad boss. Speak up when your boss is screwing up.

… to move to another role. We grow not only by being promoted, but by trying new things. Go back and read my article about how you gotta do what makes you happy, because it talks a lot about how to do this.

… to persevere through difficult times. Perseverance and grit usually lead to better long-term happiness. You get a salary because what you do is sometimes hard, boring, or annoying. Get through those tough times, to get to the good ones.

For me, the key is that you need to check yourself when making a hard decision, and ask if fear is what’s holding you back. If it’s a reasonable fear – meaning the risk of something going horribly wrong is reasonable – then yeah, don’t do it. But if it’s irrational fear (as it usually is), and the likely outcomes range from “good” to “meh, kinda bad, maybe?” then you should go for it.

Particularly if one possible outcome is “awesome.” Never devalue awesome!

Now, I also recognize my privilege. I talked about it in my post about luck. I’ve had the luxury of never being afraid to speak to power. What are they going to do, fire me? For me, that’s always only been in the “meh, kinda bad, maybe” category. Therefore, I recognize that ideas like “don’t be afraid to escalate may not always be the best advice. If you’ve got a job that’s keeping your head barely above water, and you’ve got a boss that’s a jerk, and you’re sure you’re going to get fired if you go over his head, then yeah, maybe don’t escalate. Remember, if the fear is rational and reasonable, then don’t do it. (But maybe look for another job? If you can, of course.)

Unfortunately, I’ve also worked at companies where, if you make a significant mistake, the CEO will walk down the aisle and fire you on the spot. The result is stagnation – people will put in a lot of effort to look busy, without actually doing anything. At those companies, “don’t be afraid to make a mistake” can be bad advice (and yes, I looked for another job).

So… what are you afraid of?

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How To Ask For Help

So the last article was about gophers vs. hair-on-fire, and how they do (or don’t) ask for help. In it, I alluded to coaching people on HOW to ask for help – and that’s what this article’s going to be about.

First, before you ask for help, you need a problem. I recommend against asking for help when you don’t have problems – in fact, it’s a good way to get fired.

I’m not going to go over basic problem solving, like sizing problems, effective searches, and the like. That’s perhaps a different article for a different day; if you’re interested, let me know. Today’s article is how to ask for help.

So, assuming you’ve hit a wall, and assuming you’ve invested a reasonable amount of effort to get over it, the right thing to do is to go to someone that you think can help. When you do, say the following three things:

  1. This is what I’ve done: …
  2. This is what I plan to do next: …
  3. Am I on the right track?

If you say those three things, in that order, it tells people:

  1. You’ve thought about the problem, and
  2. You have a plan (maybe not the BEST plan, but A plan), and
  3. You’re open to feedback if it’s not the most effective or efficient one.

The key to this problem-solving technique is that it lets them help you with the meta-problem of how to solve problems, rather than asking them to solve the specific problem for you. This is the best possible outcome for the long-term: you expand your library of resources, you learn new things, and (hopefully) you can solve the next problem on your own.

So you’ve gone to someone, used the three lines, and asked for help. Their possible responses are:

(1) Yeah, you’re on the right track, go for it! – this is great! Congratulations! And if you’re the type of person who leans towards the hair-on-fire approach to problem solving, this question and response shows that you’ve done the leg work, and they can tell that you’re approaching problems in a reasonable way. It’s much less annoying to them, and much better for you in the long run.

(2) No, the wiki’s wrong, the answer’s actually over there… – this is also great! You’ve short-circuited the issue, and you’re on the right track quickly. You also learned about a new source of information, which will be useful in the future. If you’re the type of person that leans towards the gopher approach to problem solving, this means that rather than wasting an hour on your (bad) plan, you have an answer in seconds. Oh, and if you can fix the wiki, that means the next newbie’s not going to have the same problem you did, so probably do that too…

(3) I don’t know, but person X knows more about it. – also great! You’ve found something out about the team, and the people on it. Next time, you’re short-circuiting the problem again and can approach the right person the first time. Go find them, use the same three lines, and lather, rinse, repeat until you’ve made progress. Don’t forget to update your library (and the wiki)!

(4) I don’t know, that’s a good question! – the best! You both get to learn the right answer! This is the best possible response, because you’ve found an interesting and difficult problem, and you’re probably going to make the team, the org, and the company better by solving it.

I’ve used this pattern – this is what I’ve done, this is what I plan to do next, am I on the right track – at every stage of my career. It’s the most useful approach I’ve found to not only solving the immediate problem, but also getting better at the meta-problem of problem solving. The best leaders (and the best employees) are the ones that are good at the meta-problem, because it makes every problem easier.

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