That’s an interesting comparison...
The licensing point highlights how much of the burden in software hiring sits on explanation rather than verification. Without shared baselines, candidates end up narrating their competence instead of pointing to an accepted signal.
The expectation gap you describe also explains why requirements feel flexible in practice but rigid on paper. When the real goal is “get someone productive soon,” standards tend to bend quietly rather than evolve explicitly.
Do you think the absence of clear baselines is something the industry could realistically converge on, or is software work too varied for that to work in the way it does for licensed engineering?
That makes sense, and I think your skepticism is reasonable.
From the candidate side, it’s almost impossible to tell whether criteria are being refined thoughtfully or just drifting based on recent hires or strong opinions in the room.
What strikes me is that without explicit feedback loops, iteration can easily turn into reinforcement, people conclude “this worked” without ever seeing the counterfactual of who was filtered out.
From the outside, it often looks less like a calibrated process and more like accumulated intuition. I’m curious whether that matches what others here have seen from the inside.
I don’t think the gap you’re describing is about quality of work as much as how it gets interpreted.
What you described, building something end to end, making real tradeoffs, and caring about the problem is exactly the kind of signal people say they want, but it doesn’t always map cleanly to how hiring filters operate.
Being early in your career makes that mismatch louder, not smaller. Without context, depth can look like “small” and polish can look like “impact”.
One thing that might help is making the reasoning behind your choices visible, not just the output.
When reviewers can see why you built things the way you did, it becomes easier to compare substance to surface.
It’s normal to feel unsure at this stage, but from the outside, what you’re describing sounds like a real foundation, not a disadvantage.
I wish you all the best!
Austin, that makes sense.
The signaling problem cuts both ways:
Resumes try to compress complex ability into keywords, and job descriptions try to describe real work with abstract labels. A lot gets lost in between.
The unclear goals point is important too. When a role isn’t well-defined, hiring ends up optimizing for proxies rather than outcomes.
Do you think this is mostly a language problem (how roles and experience are described), or a structural one where teams don’t actually agree internally on what success in the role looks like?
I think that’s a fair list, and it highlights how much of the process sits outside the candidate’s control.
Macro forces, internal incentives, and human bias all stack on top of each other, and the candidate only sees the outcome, not the cause.
What feels particularly hard is that all of these factors collapse into a single signal for the job seeker, a rejection with no explanation.
From your perspective, which of these has the biggest impact in practice, and which ones do you think are most invisible to candidates going through the process?
I agree with this. What stands out to me is that the hiring process often treats one internal mental model as “correct”, and anything outside of it as a flaw in the candidate.
The example you gave about solving the same problem differently is common; different approaches get mistaken for lack of competence.
I like the negative testing idea a lot. If a hiring process never examines who it’s rejecting, it has no way to know whether it’s filtering quality or just filtering familiarity.
Have you seen teams actually test or evolve their hiring criteria this way, or does it usually stay fixed once defined?
I’m one of the co-founders and went through this process myself.
Not promoting anything here - genuinely interested in how others experience this and what helped create clarity.
Do you think the absence of clear baselines is something the industry could realistically converge on, or is software work too varied for that to work in the way it does for licensed engineering?