Narek Kazarian

There’s a quiet trend happening - Rust engineers leaving comfortable FAANG roles for small, high-ownership teams. Not because they want ping-pong tables or startup chaos - but because they want meaning. They want to build things where their fingerprints actually show up in the product. Every week I hear the same line: “I just miss building.” That’s why early-stage Rust hiring is taking off. The best engineers want to feel the impact of their work again. If you were choosing between stability and impact, which way would you lean right now? 🦀

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Your GitHub might be the reason you're getting ghosted by recruiters. Not your resume. Not your cover letter. Not your lack of “networking.” GitHub is where hiring managers actually see what you can do. And if you're a software engineer not treating it like your code portfolio... you're leaving serious opportunities on the table. Employers will often ask us to submit candidate resumes AND GitHub links And often, their GitHub profile told a better story than their CV ever could. Just like a designer needs a portfolio — so do you. But here’s the catch: Not all GitHub profiles help you. Some actively hurt you. ✅ What works: Clean, focused, easy-to-navigate projects A few solid repos > 20 half-baked experiments Clear README files with real context Projects that show progression, not just college work from 2016 ❌ What doesn’t: Dead projects with broken code Activity with no documentation Code dumps that show zero care or quality GitHub isn’t just storage.  It tells employers: How you think What you value Whether you can work like a pro Treat it like your LinkedIn, but for your code. If you haven’t set up your GitHub yet, or need to refresh it, start here: 👉 https://lnkd.in/e_4ApmAW 💬 Not sure if your GitHub would impress or repel a hiring manager? DM me, I’ll take a look. #GitHub #SoftwareEngineering #JobSearch #TechHiring #PortfolioTips

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GitHub just moved AI coding from autocomplete to architecture. Copilot Workspace now handles the entire development cycle—from issue to pull request. Early adopters report 55% faster feature completion. That's not incremental. That's structural. What this means for technical hiring: The value hierarchy is shifting. Junior developers who primarily translate requirements into boilerplate code face compression. Mid-level engineers who understand system design and can validate AI-generated solutions become more valuable. Senior architects who can decompose complex problems into AI-actionable tasks are suddenly force multipliers. This isn't about AI replacing developers. It's about redefining what "coding skill" means. The bottleneck is moving from syntax to judgment. For hiring managers: Start evaluating candidates on problem decomposition and code review capabilities, not just greenfield implementation speed. The engineers who thrive will be those who can effectively collaborate with AI tools as thought partners. For developers: If you're spending most of your time on implementation patterns that Copilot can generate, invest in the layers above and below—requirements analysis and architectural decision-making. The technical interview that asks candidates to write a sorting algorithm from scratch is becoming less predictive. The one that asks them to critique an AI-generated solution and identify edge cases? That's your signal. We're not losing coding jobs. We're compressing the implementation layer and expanding the strategy layer. Adapt your hiring lens accordingly.

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The recruiting in tech has been an absolute mess lately, from "check out this repo" scrapers/hacks & fake positions with companies that don't exist to minimum requirements that look like a whole engineering department & ones that ask senior/staff engineers to do l33tcode assignments. I wanted to share a recent experience with an application to a senior position at a company - not going to name them, but they're a large player in the recruiting/ATS arena. Getting a rejection email is something that you eventually get used to with experience & it doesn't bother you too much, there's a lot of candidates you're competing against & the best course of action is simply asking for feedback regarding your application - if you're lucky, they might answer you with constructive criticism that you can apply in your applications going forward. You could imagine my surprise when an email came through, not because it was a "we decided to go with someone else", but because it already contained some feedback for me! Fantastic, I can use this to improve. Or so I thought. As my eyes glazed over the list of things that were highlighted as a potential mismatch & that they "can't specifically say which apply to your background", I was... stumped, at first. Analyzing the points one by one, I realized none of them applied to my background or experience. Now, I understand that sometimes there can be contention or ambiguity in this regard, but these were things that would've been obvious to anyone that even looked at the resume for more than 5 seconds. Then it hit me - it's highly probable nobody actually did. While it's not uncommon to have recruiters use AI tools within their ATS systems to parse through massive amounts of applicants & have a template rejection reply, this one rubbed me wrong - because it was veiled as some constructive feedback. At least the "no" templates are obvious & as unfortunate as they are, the applicants understand them as an industry solution to large amounts of responses required. This one was pretending to be something it isn't & insulting, to be completely honest. Nevertheless, to try to exclude my own bias, I decided to ask for a second opinion. I took my resume, their response & my analysis of it and chucked it into Claude AI to see if it's valid or am I just being a biased crybaby. My electron-brained friend not only confirmed I was 100% correct, but crafted a conclusion I couldn't have written better myself. See the first reply for what Claude said.

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I see so many startups claiming they want to hire elite Software Engineers, but then demanding a coding task before even having an intro call. That’s not how you attract top talent.

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Most software engineers negotiate too late. Standard advice: wait for the offer, then counter. But here's what the data shows for tech hiring. 58% of candidates accept the first offer without negotiating. They leave money on the table. Of those who do counter, 85% get at least part of what they ask for. But here's the thing everyone misses about tech compensation. Timing matters before the offer stage. You don't negotiate salary expectations early. You establish them. When hiring managers ask about comp expectations before an offer, most developers either dodge the question or anchor too low. Both hurt you. The move: give a range based on market data for your role and city, then pivot to learning more about the full package. In the GTA, that's $110K-$150K for senior developers, $80K-$110K for intermediate. This isn't negotiating. It's alignment. 45% of tech companies increase their initial offer when candidates counter. But those offers start higher when expectations were set clearly up front. Once you get the offer, 73% of employers expect you to negotiate anyway. So set the baseline early, negotiate the details later. Have you ever negotiated salary before receiving an offer, or only after?

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You're testing for algorithms knowledge. You're evaluating system design skills. But you're missing the single best predictor of success. 🧠 What performance patterns suggest: 🔍 One question can be particularly revealing in technical interviews: "Tell me about a time when you had to learn something completely new under significant time pressure." This question reveals: 🌱 Learning agility under constraints ⏱️ Response to pressure 🧩 Problem-solving approach 🔄 Adaptability to change Engineering leaders often design interview processes that select for known skills rather than learning capacity. The most innovative technical organizations don't just hire for current knowledge - they select for the ability to acquire future knowledge rapidly. What's your best question for assessing learning agility? In a rapidly changing technical landscape, that might be your most important screening tool. #TechnicalInterviews #LearningAgility #HiringStrategy #EngineeringTalent #AdaptiveSkills

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Software Engineers are some of the smartest individuals I've had the pleasure of interacting with. However, I still find myself scratching my head when startups make offers and engineers use flawed logic to weigh one offer against another. Higher equity dollar value does not = better offer. I don't care if Startup A offers you $500k in equity, and Startup B offers you $100k in equity. If Startup A isn't around a year from now, that $500k is worth nothing. Z-E-R-O. It means nothing. Some put such a heavy emphasis on total compensation, that they forget the basics: -Is the startup's business model viable long-term? -Can the company survive in a market downturn? -Can the leadership team can deliver through the good times + the bad? -Do they have an exit strategy? -Do their customers actually like the product compared to their competitors? -Are the people you interviewed with excited about the outlook of the company? ^more of these types of questions will give you better odds of hitting the 'startup lottery'. not pie in the sky numbers on a spreadsheet

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