Never seen a downturn?

Most of my colleagues today have never lived through a tech downturn. I don't count 2020, for reasons I'll come to soon.  That means the last downturn was 2008, which was 17 years ago, and I have heard leadership at my company citing that.  But I think it's a bad comparison; we should instead look at the 2001 dot-com bust before that.

In 2008, speculation in housing (and especially sub-prime lending) led to a global recession that swept the tech industry along with everyone else.  As an industry, however, tech was relatively well-balanced. When the S&L crisis exploded, the government shored up the finance sector, consumer and employer confidence improved, and in tech our recovery was fairly quick for both employment (by 2010, according to FRED) and market valuations (October 2008 to Feb. 2011).

In 2001, by contrast, the tech industry was the problem: too many companies hired too many people, and a sock puppet without an sustainable business plan commanded $400M valuation. That was a bubble in tech, and the resulting burst hurt: stock valuations took over a decade to recover (November 2007, just in time for 2008's crash), as did job recovery (2017, as a percentage of total employment).

In 2020, the pandemic and our responses caused a general downturn, like 2008, not a tech sector one. But it turns out that software is pretty easy for work-from-home, so the truly disastrous impacts weren’t so bad on our sector.  Hiring was already booming going into the pandemic, and the free money policies that kept the economy overall from tanking only made tech hiring boom more. So I don’t count 2020 as a downturn at all; it was a boom on top of a boom, in jobs and stock valuations both.  Until 2022 for stock… and the layoff headlines started in 2023. What changed? Mostly the end of free money, making the costs of hiring harder to justify.

Which means what? First, it means that even senior leaders might be working from the wrong parallel, and expecting a fast rebound.  More important, I think, is the push for LLMs aka Generative AI during a downturn. Even if you believe the AI claims, then in a boom time,  employers would still be hiring, and a productivity-multiplying tool would magnify that investment in people. But in a lean time, the bias is on cost control, so a productivity multiplier is gets the required work done with fewer people: no hiring. Alternatively, if you don't believe the AI claims... then we're riding a bubble that's going to pop while we're already down. Either way the AI boom goes, I fear we might not see hiring recover for a long while!

What does that mean? The obvious short-term problem is on the employee side; we have thousands of experts who were recently laid off. There are jobs---my mailbox is still cluttered with unsolicited recruiter spam---but mostly in shaky-sounding startups and second-tier companies; the big leaders are sitting this round out. That leads to more competition for jobs that are riskier, have lower compensation, and/or stretch engineers less. The subtle problem is on the employer side: in the constrained environment, "growth" means hiring senior people instead of, or to replace, more junior ones.  With both together, today’s new computer science grads face the highest unemployment rate of any degree; software as a field looks far less appealing.

The really big problem, however, is the future effect of this: senior job definitions entail mentoring of junior engineers, leading designs, defining and revising architectures, and we aren't necessarily creating more of that level of work. Instead, we're hiring senior people into, effectively, more junior roles, but at salaries for their seniority.  Which may keep their bills paid, but might not keep them or stretch them; instead, it leads either to finding more stimulating work, into under-contributing complacency. So whenever we catch up to AI's impact, good or bad, and come out of the cold for this downturn, it may be to a deep labor shortage, if we aren't drawing new talent into the market and are driving existing talent either out of the market or into comfortable mediocrity.

We would work our way out of that, of course, but it would take time. Maybe lots of time, if AI gets better and better, or if a post-AI crash extends the current downturn!

Forget career ladders; it's a jungle gym

Block, my current employer, does a pretty good job of defining career levels, and what each tier is asked to do that is more demanding than the previous. Between those levels and the popular terminology, it's pretty easy to talk about the career ladder, but it's a deeply flawed analogy.

To begin with, ladders have parallel sides and even rungs.  Career tiers are not evenly spaced, and above a certain level you don't need as many of them: if a company employs 1,000 new-graduate engineers in 2020, that isn't a promise to need 1,000 staff-level engineers in 2035. For that matter, if the industry needs a million new graduates, that doesn't promise a million future senior engineering slots.  At some point the track becomes a career pyramid.

But it isn't zero-sum, either.  Some engineers will plateau and not reach the next higher level... but some will become engineering managers.  Or product managers.  Or something else; I have a colleague now in technical support (very technical support, to external developers) working with me to become a product-focused software engineer; I had an earlier engineering colleague who did the reverse. You literally can't climb your way to "the top" because there isn't only one top.

I can be pretty competitive in the right contexts, but in life, I don't see the point: find the path that makes you happiest.  And for careers, it's something more multi-path than a ladder, and should be something more fun, so I use the analogy of a career jungle gym.  Play on it.  And if, to you, that means knowing the endgame you want and exactly how you want to get there, then you do you.  I more often look for what rung I want to swing to next, and maybe the one after that. But don't think there's only one choice!

(Edit: In 2025, I heard it called a career lattice, which I liked.  But the same speaker thought that "career pathing" was an acceptable phrase, so... I dunno, it worked for them, but my grammar police says a hard no for "pathing.")

Credit and Collaboration

I was listening to an old Hidden Brain podcast that made reference to the phenomena of overclaiming: that if you ask collaborators what percentage of the work they do, that total comes to over 100%, which is mathematically impossible.  The point to the episode is the usual one, that we need to recognize we're probably over-stating our impact and under-valuing others, and need to check that bias.  (About minute 23 here, if you care.)

First of all, that's true: we do all over-emphasize our work, because we did it, viscerally; we either didn't even see, or saw but didn't feel, the contributions of others, so the natural tendency is to under-weight them. Got it.  But also... that isn't how collaboration works.

That percentage-contribution idea might be how execution works, sort of, if there's a list of things to do and we can count how many we each did and how easy or hard those items were as a percentage of total work.  But that subtask execution is only a piece of good collaboration.  Good collaboration requires shared ownership, and there isn't a good way to allot credit for that except by giving joint credit.

As an example, in a recent meeting a teammate mused that something-or-other would be great if only we could do it, I agreed by said that the problem was this-and-such, so we'd need this to be able to, and between the two of us and a suggestion from a third we discovered with might have a solution.  Who "did" that? We all did; without any of us, the idea wouldn't have come together. Or I had a colleague who was doing the work on something and had gotten stuck; I made a suggestion for what to do on that roadblock.  I didn't "do the work," they did---but it wouldn't have happened on time without my suggestion, and the plan they were working from was mine (but with review and input from others), so I want some credit also.

If you're in an environment in which credit is being apportioned at all, then I argue you're in a toxic mindset, and need to break that mindset. It's a common joke that leadership is going to "take credit for" their employees work---but they should, and it should be a both/and concept of credit.  For that matter, in my career I have several times had the role of fielding all the inbound distractions---bug reports, oncall pages, support queries, whatever---to let the team focus on "the important thing." If an engineer takes on that role of sponging up "everything else" so the team can deliver the crucial thing, that teammate made the crucial delivery happen.  So did the ones people the feature work, of course, but the impact can be both/and. 

First, this is how good leadership should work and be evaluated: the engineers get credit for doing what they do, and the leads get credit for the team's delivery, and the other teammates do also. It's perfectly appropriate to brag in your performance evaluations about how you're responsible for the team's successful work, and you have to call out who did what so they get their credit also; the shout-out doesn't diminish your leadership impact but enhances it.

Second, this is how good culture works. If you can't build a culture in which collective delivery begets widespread individual credit, then you are building a culture in which people have an incentive to be selfish about their own perspectives, which leads to selfish decisions about time and effort. If you instead build a culture about collective delivery, you build a culture about collaborative support.  And in that worldview, you do need a way to ensure that performance reviews and eventually raises include valuing that kind of teamwork.  There is still going to be a need to evaluate individual performance, obviously, and a way to catch an underperformer being carried by the collective team; those cases need to be noted and managed. But the mechanism shouldn't be bean-counting the amount of direct contribution without also acknowledging the role of indirect and of shared contributions.