YouTube: senior engineer explains hiring

Software hiring is having a weird year. Layoffs are still loud, AI panic is everywhere, and a lot of candidates feel like the market is dead. But a May 10 YouTube video from software engineer Maddy Zhang makes a narrower point: the market is not dead so much as split in two. (youtube.com) Her argument is that companies are still hiring, but they are hiring more selectively, with much less patience for vague experience or shallow project work. ### What changed this week? The timing matters because Zhang’s video landed just after fresh April hiring data showed new tech job postings at a three-year high. (comptia.org) CompTIA said employers listed 271,483 new postings for tech occupations in April, with more than 575,000 active postings overall. (youtube.com) That does not mean every applicant suddenly has leverage again. But it does mean the simple story — “AI killed software jobs” — is too blunt. ### So why do people think hiring is frozen? Because the visible signals still look bad. Layoffs make headlines. Hiring processes are slower. Rejections pile up fast, especially for junior applicants. (youtube.com) Zhang’s setup is basically that both things can be true at once — companies can cut headcount in some areas while still opening roles in others, especially roles tied to AI systems, cloud infrastructure, security, and higher-skill software work. ### Why does “split in two” fit? Because the demand is not evenly spread. Zhang frames the market as stronger for senior engineers and weaker for entry-level candidates, and that lines up with the broader 2026 workforce picture. CompTIA’s outlook for the year shows net tech employment still expanding, but the growth is happening inside a market that increasingly rewards specialization and applied skills, not just generic coding familiarity. (comptia.org) ### What are companies filtering for now? The short version: proof, not vibes. Zhang says employers want stronger fundamentals, deeper project work, interview readiness, and signs that a candidate can build like an engineer working in production, not just finish tutorials. That means cleaner project execution, clearer tradeoff thinking, and evidence that someone understands debugging, systems, and shipping habits — not just syntax. (youtube.com) ### Why do projects matter more? Because projects are one of the few ways candidates can show judgment before they get the job. A résumé can say “built an app.” A strong project shows architecture choices, edge cases, deployment decisions, monitoring, and iteration. Basically, companies seem less impressed by application volume and more impressed by signals that a person can take messy work from idea to working software. (youtube.com) That is especially useful when hiring teams are trying to avoid expensive misses. ### Where is the demand moving? Zhang points to demand shifting inside software engineering rather than disappearing from it. Her video description calls out AI, software engineering, and career growth, and the broader market data points the same way — employers are still looking for developers, systems engineers, cybersecurity engineers, and people with some AI fluency. (youtube.com) The catch is that “AI fluency” is becoming table stakes in more roles, not a magic substitute for engineering basics. ### Does this mean juniors are locked out? Not exactly. But the easy path looks narrower. If companies are favoring candidates who can already show fundamentals, production habits, and clear execution, then junior applicants need stronger evidence than they did in looser markets. (youtube.com) That can come from internships, serious projects, open-source work, or unusually strong interview prep — but the bar for standing out is plainly higher. ### What’s the bottom line? The useful takeaway is not “ignore layoffs” or “AI changes nothing.” It’s that software hiring in 2026 looks selective, uneven, and skills-first. Zhang’s video lands because it explains the contradiction people are feeling: there are real openings, but companies want candidates who already look close to productive on day one. (youtube.com 1) (youtube.com 2)