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In larger systems, what looks like “overengineering” can be deliberate risk management. In my experience, senior engineers do get promoted for simplicity but only when they can articulate the trade-offs and the future costs they are avoiding.
The real question is how do you tell engineer A who can figure out how to make the complex problems simple from engineer C who can't handle complexity and so writes simple solutions when the complex one is needed.
Sure they do. You just need to spell it out in business terms, not tech terms: "Reduced incidents by 80%", "Decreased costs by 40%", "Increased performance by 33% while decreasing server footprint by 25%" Simplicity for its own sake is not valued. The results of simplicity are highly valued.
Sure they do. You just need to spell it out in business terms, not tech terms: "Reduced incidents by 80%", "Decreased costs by 40%", "Increased performance by 33% while decreasing server footprint by 25%" Simplicity for its own sake is not valued. The results of simplicity are highly valued.
> "Reduced incidents by 80%", "Decreased costs by 40%", "Increased performance by 33% while decreasing server footprint by 25%" My experience is no one really gets promoted/rewarded for these types of things or at least not beyond an initial one-off pat on the back. All anyone cares about is feature release velocity. If it's even possible to reduce incidents by 80% then either your org had a very high tolerance for b…
I’ve definitely consistently seen people who can take a wildly complex bug-ridden Rube Goldberg machine that was impossible to change and break it down into a simple understandable system get promoted. These people are generally the best engineers in the org and a get reputation for that.
In the hands of an experienced developer/designer, AI will help them achieve a good result faster.
In the hands of someone inexperienced, out of their depth, AI will just help them create a mess faster, and without the skill to assess what's been generated they may not even know it.
In smaller companies it's a lot easier to express the distinctions and values of simplicity to ears that might actually appreciate it (so long as you can translate it into what they value - simple example is pointing out that you produced the same result in much less time, and that you can get more done on overall feature/task level as a result).
AI coding tools are making this problem worse in a subtle way. When an agent can generate a "scalable event-driven architecture" in 5 minutes, the build cost of complexity drops to near zero. But the maintenance cost doesn't. So now you get Engineer B's output even faster, with even more impressive-sounding abstractions, and the promotion packet writes itself in minutes too. Meanwhile the actual cost - debugging, onb…
On the other hand, AI coding tools make it relatively easy to set and apply policies that can help with this sort of thing. I like to have something like the following in AGENTS.md: ## Guiding Principles - Optimise for long-term maintainability - KISS - YAGNI
I interviewed at a company that used a simple project to screen candidates. It was implementing a cash register checkout system. The task was soo simple that I couldn't figure out what they were looking for. So I implemented the simplest thing possible. I got the job partially because they were impressed by my utterly simple solution. I helped evaluate other candidates given the exact same problem and it's amazing ho…
In fact, simplicity often is the best future-proofing. Complex designs come with maintenance costs, so simple designs are inherently more robust to reorgs, shifted priorities, and team downsizing.