Erin Kiser

This company pays $30K UNDER market rate. And yet, they have a 100% offer acceptance rate. They've just hired a senior engineer in 5 days. Everyone thinks you need a big budget to land top talent. This client proves otherwise every single time. They're a remote early-stage startup. They have no brand recognition and no fancy perks. And their compensation is consistently below what candidates could get at a bigger company. On paper, they shouldn't be hiring anyone. And yet, every candidate we submit an offer to says yes. Literally, every. Single. One. The difference is simple. And almost no one does it. The very first call a candidate has is with their CTO. He's the most senior technical leader in the company. And he doesn't open with interview questions. He opens with the vision. He speaks about the company’s track record. Then he walks candidates through the equity opportunity and tells them exactly why this role could change their financial future. He sells the mission, the technology, and the trajectory before he ever asks a technical question. By the time the first call ends, the candidate's excited. The second conversation's an HR close running through benefits, culture and start date. Compare that to another client of ours with 50 employees. They have great product, but their process starts with an HR screen, moves into 3 technical rounds, a full-day panel running from 9 am to 3 pm, and then a co-founder meeting. Every stage feels like another test. Nobody's selling the company, nobody's painting a picture of the future. And the best candidates have already accepted somewhere else by round 3. The first company wins because they understand that when you can't compete on salary, you have to compete on speed, conviction, and vision. Stop dragging your feet and start selling your future. That's how you win candidates you can't technically afford.

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Building apps in Claude as a non-technical guy is honestly kind of disorienting / incredible. I’m not an engineer. I’ve hired a lot of them. Sat in the interviews. Evaluated technical answers. Debated tradeoffs. Now I’m typing prompts and watching usable code spin up in minutes. It’s definitely not perfect. You still have to think and iterate. You still have to structure the problem well. But the gap between “idea” and “working thing” is way smaller than it used to be. That’s the part that sticks with me. I keep thinking about how different the landscape looks compared to even a few years ago. The bottleneck isn’t just technical skill anymore. It’s problem framing. Judgment. Taste. Knowing what to build and why. Instead of optimizing a Boolean, I’m deciding between Azure and AWS to host an app I built this morning. I’m still a recruiter. Still a TA strategist. Still a manager. But I’m also stacking skills I never expected to have in my toolkit. Stuff that wouldn’t have even been on my radar a few years ago. Feels early. But it also feels like the slope just changed.

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The vibe coding trend promised to make software engineers obsolete by March 2025. Five months later, it's the first AI bubble to burst. For those who missed it: influencers claimed you could build production apps through prompts alone. Ship a Netflix clone before your coffee cooled. Traditional coding was dead. The recruitment implications seemed seismic. Then reality arrived. Shipping 100 AI-generated apps is trivial. Maintaining them is chaos. The code looks structured but breaks in production. AI confidently invents libraries that don't exist. The technical debt compounds faster than any team can manage. This matters for how we hire. When evaluating candidates who built portfolios with AI assistance, ask different questions. Can they debug what they shipped? Do they understand the architecture they prompted into existence? Can they maintain code they didn't write by hand? The distinction isn't between AI users and purists. It's between engineers who understand systems deeply enough to direct and fix AI output, versus those who only know how to prompt. AI will change software development. But the vibe coding collapse proves that building software still requires engineers who understand what they're building. Adjust your screening accordingly. The fundamentals haven't changed as much as the headlines suggested.

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Ex-FAANG engineers: I'm skeptical of you. Tell me I'm wrong Every time I see "Google" on a resume for our startup role, I look for the same thing: Evidence they actually built something. Not "launched." Not "shipped." Not "contributed to." Built. Owned. Fixed at 2am. Defended in a customer call. Because "launched Google Feature X" could mean: - 6 months of design docs - 200 code review comments - 0.1% of the actual code Or it could mean: - You prototyped it in a weekend - You convinced 3 teams to use it - You maintained it solo for a year I don't care about the brand. I care about the story. If you're ex-FAANG and have the second kind of story, I want to hear it. If you only have the first kind, no hard feelings - but we're not the right fit. #Hiring #Startups #Engineering

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🔥 Resumes lie. Momentum doesn’t. A big logo on LinkedIn is not proof of output. It’s proof of access. If you want builders, stop screening for status. Screen for slope. → Ask what they failed at and how fast they corrected. → Test how they break down ambiguous problems. → Look for curiosity that outpaces ego. → Prioritize those who self-educate without permission. The fastest learner in the room becomes the highest performer in the room. Every time. 🔁 Repost if you care more about trajectory than titles. #SmartHiring #FounderMindset #PeopleOps #HighPerformanceTeams #StartupLeadership

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Stop Checking Boxes and Start Hiring for Growth Hiring managers love to say they want “the best.” But then they turn around and screen out anyone who doesn’t check every single box on a list of arbitrary requirements. But here’s the truth no one wants to admit: Experience alone doesn’t guarantee results. Or course, a proven track record matters. But when experience becomes the only yardstick, you overlook people with the potential to drive real impact. 👉 That candidate with 6 years instead of 10? They might bring fresh ideas and adaptability your team needs. 👉 The person pivoting careers? They could have exactly the resilience, creativity, and drive that stale teams are missing. 👉 The rising leader without a Fortune 500 name on their resume? They might outperform the so-called “safe bet.” When you hire only for past experience, you’re often hiring for the past, not the future. Here’s why impact potential deserves more weight: ✅ 1. Skills evolve. Yesterday’s best practices are today’s baseline. A curious, driven person will learn and adapt faster than someone coasting on old credentials. ✅ 2. Culture fit matters more than a perfect resume. A collaborative mindset and hunger to grow can’t be taught. Tools and processes can. ✅ 3. The best performers often come from unconventional paths. Some of the most impactful hires I’ve seen weren’t the ones with the longest credentials. They were the ones with the most to prove. ✅ 4. Bias hides behind “years of experience.” It’s an easy excuse to dismiss candidates from different industries, backgrounds, or demographics. Imagine what would happen if you evaluated candidates based on what they could become with the right support, rather than what they’ve already done. Because in the end, business isn’t moved by resumes. It’s moved by people who show up, step up, and figure it out. If you’re struggling to fill roles or wondering why your team feels stuck, ask yourself: Are you hiring for impact, or just checking boxes? What’s the best example you’ve seen of someone with “less experience” outperforming the veterans? #Hiring #Recruiting #TalentAcquisition #Careers #KBOtek

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📉 The highest-paid developer I know hasn't written code in 6 months And he just got a $400K offer Not from a startup desperate for warm bodies From a Fortune 500 that interviewed 200+ candidates Here's what he does instead of coding: He walks into a room full of executives who just spent $2M on an AI initiative that's failing He listens for 30 minutes Then he says: "Your problem isn't the model. It's that you're running inference on-device without a fallback, your app crashes on 60% of real user devices, and you're losing $15K/day in churn you're not even tracking" The room goes silent Then the CTO says: "When can you start?" This is not a tech interview This is a business conversation And that's the shift nobody prepared us for For 15 years, the path was clear: Learn framework -> Get hired -> Write code -> Get promoted In 2026, that path leads nowhere The developers getting $300-500K offers right now aren't the best coders. They're the ones who can: -> Diagnose a $200K business problem in 30 minutes -> Translate engineering chaos into executive language -> See what's broken before the metrics show it Same technical skills as everyone else. Completely different conversation. Here's the uncomfortable truth I learned the hard way: "I write clean Kotlin" = $120K ceiling and mass rejection "I found the reason your AI feature is killing retention" = $400K and they come to YOU The market didn't get harder It got pickier It stopped paying for effort It started paying for diagnosis Every doctor learns biology. But you don't pay your doctor for knowing biology. You pay them for looking at YOUR symptoms and telling you exactly what's wrong. That's the shift From engineer to diagnostician. From code writer to problem translator. From "building features" to "saving the business $200K." The developers who make this shift in 2026 will never job-hunt again. The ones who don't will spend another year sending 200 applications into the void. 💬 Which side are you on right now? Still selling your skills - or learning to sell your diagnosis? 🔁 Repost if someone in your network needs to stop grinding LeetCode and start thinking about this. The game already changed #AI2026 #TechCareers #FutureOfWork #SoftwareEngineering #RealTalk #CareerPivot

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The “Nice” Dev Who Slows You Down They’re polite. Cooperative. Friendly. But they don’t push back. They don’t cut scope. They never ask, “What’s the impact?” You hired a coder when you needed a co-founder. In interviews, ask: “Tell me about a time you said no to a feature and were right.” If they’ve never pushed back, you’re not hiring a partner. You’re hiring dead weight.

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I stopped applying for jobs the traditional way because the odds are rigged against you. The average role gets 250 applicants and only four get an interview. Most people send a generic PDF and pray the algorithm misses their flaws. It will not. You have to manipulate the software before a human ever sees your name. I tested a sequence of four prompts that turn a standard resume into an inevitable hire. Here is the system: 1. The Gap Analysis Paste your resume and the target job description into the chat. Command the AI to act as a senior recruiter. Ask for a match score out of 100 and the top five missing keywords. Every point under 90 is a reason to reject you. 2. The Google XYZ Reformatter Stay in the same chat and ask it to rewrite your experience using those keywords. Force it to use the Google XYZ formula: Accomplished X as measured by Y by doing Z. Vague descriptions kill careers. Hard data gets you paid. 3. The ATS Stress Test Change the persona to an Application Tracking System filter. Ask it to identify every section a bot would struggle to parse or read. If the machine cannot read your headers, your experience does not exist. Clean formatting beats creative design every single time. 4. The Hiring Manager Simulation Tell the AI to act as the hiring manager for this specific role. Ask for the three hardest technical questions and the perfect answers based on your history. You are not just fixing your resume. You are downloading the script for the interview. Most candidates guess what the company wants. The best candidates use the data to tell them what they want to hear. Stop guessing. Run the prompts.

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🧠 Recruiter: "Can you tell me about your experience with distributed systems at scale?" 👨‍💻 Candidate: "Haha, that’s a silly question. Who even asks that?" 😅 Me internally: "Ah, just us silly folks trying to understand if you can actually do the job." 🚨 PSA to all job seekers: If a recruiter asks a technical question, even if it sounds “basic” or “obvious” to you — it’s not because we want to waste your time. We’re not here to stump you, we’re here to understand your experience, not read your GitHub repo telepathically. ✅ You can clarify. ✅ You can ask follow-ups. ❌ But please don’t mock the question — especially if it’s something your future team will care deeply about. We’re all on the same side (I promise). Just trying to connect dots, not break spirits. 😇 #recruitertips #techrecruiting #interviewetiquette #humbleisthenewsmart #careeradvice DONE!Berlin

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"Of your last 10 engineering hires, how many have stayed longer than 12 months?" An engineer asked this in an interview last week. The hiring manager froze. Fumbled for an answer. Got defensive. Then gave a vague response about "industry turnover" and "people finding their path." The engineer withdrew from the process that same day. That alone told them everything they needed to know. Because that question cuts through all the conversations about ping pong tables, unlimited PTO, and "rockstar culture." High attrition is not bad luck. It is a symptom. Unrealistic expectations. Weak leadership. Broken promises. Culture issues no one will say out loud. Here is the thing most candidates do not realize, you are not just being interviewed. You are also the interviewer. And the companies that get uncomfortable with this question? Those are exactly the ones you might want to run from. Strong teams answer calmly. They are proud of their retention. They will tell you the actual number without hesitation. Weaker teams deflect. They talk about "the market" or "growth phases" or give you corporate speak that means nothing. If you are interviewing right now, ask this question. And if you are a founder or engineering leader who cannot answer it honestly... That is your sign to fix something before your next hire becomes another statistic. Question for the engineers here, what is the best question you have ever asked in an interview that revealed the truth about a company?

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Why Hiring Needs a "Credit Karma" Moment Headline: The Genesis of the Suitability Engine My core experience as a recruiter—from the moment I look at an application through the phone and face-to-face interviews—has always been about determining suitability. It’s about developing trust and understanding a person's capabilities, their experience, and their fit for the job. So often in the early stages, there are hundreds of applications that are simply not suitable. I realized how helpful it would be to have a high-quality scoring tool that could be validated and trusted; a tool with no bias, so I could quickly see if someone was ready for the next step. At the same time, I knew this would be just as helpful for the jobseeker. If they could see their chances of moving forward in a simple score, they wouldn't have to waste their time anymore. We know AI has made things worse; people are now tweaking, exaggerating, or even faking their resumes to get around the ATS. They are bulk-applying in volume as if that helps, but it only adds to the noise. Fundamentally, I believe telling a jobseeker they aren’t suitable has high value for them, too. The more time they spend researching and networking around an opportunity they are actually suited for, the better. Wouldn’t it be better if a score told them that truth upfront? That was the genesis of Geescore and My Jobscore: Create a suitability engine for both sides. One of my main inspirations was Credit Karma. By telling people their credit score, you gave them an opportunity to fix mistakes and a chance to improve. They were no longer in the dark. Sometimes they were even surprised by having a better score than they thought. Credit Karma treated the consumer better than leaving them wondering where they stood. Keeping people in balance between both sides of a transaction was powerful, and it changed the consumer credit industry. I believe in that same balance for hiring. Many companies build scoring and matching only on the back end for the benefit of the hiring manager. I don't believe in that. On top of that, those systems build in a ton of bias. We have spent years stripping that bias out. I invite you to check it out. We have over 100 job boards live across states and cities, and we have a very unique way of moving this infrastructure forward. You’ll be hearing more about that soon. Take a look and check it out. #myjobscore #geescore

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🔥 Developers Trust Blogs More Than Your Entire Recruiting Team. While your job postings vanish in weeks, your competitors use technical content to build lasting trust and attract talent for years. We're no longer just hiring. We're well and truly deep into the **attention economy**. Consider this: 📌 Traditional Job Postings * Lifespan: ~30 days * Value: Immediate and rapidly depreciating * Strategy: Spray and pray 🧲 Technical Content Strategy * Lifespan: 2+ years per Ahrefs Research * Value: Evergreen, compounding * Strategy: Authentic trust-building, pre-qualified talent attraction According to Stack Overflow’s 2023 Developer Survey, developers rank technical content as the #2 most credible source when evaluating potential employers. Recruiters ranked #7 So whilst job ads might always feature in your talent attraction strategy, investing in content that consistently captures candidate attention is also worth considering. Real-world proof: * Stripe Engineering tackles deep technical insights on payments infrastructure. * Netflix Technology Blog openly showcases complex challenges in distributed systems. * GitHub Engineering dives into developer-centric issues like Git internals. Links to these in the comments section ☝️ It's clear that the attention economy rewards teams who share value upfront. The real question is how soon your team can start creating content that effectively attracts the talent you want. -------------------------------------------------------------- Here's a simple 6-point plan for implementing a content-led talent attraction strategy: Step 1: Engage help from the team. Provide an incentive, WIIFM?: * Attracting top-tier peers. * Elevating team standards and preserving engineering quality. * Building external reputation and recognition. Step 2: Pick Your Content Themes * Identify complex technical problems your team uniquely addresses. * Choose authentic topics showcasing real engineering challenges and solutions. Step 3: Create a Manageable Schedule * Aim for consistency over quantity (e.g., start monthly). * Plan an achievable editorial calendar. Step 4: Provide Easy-to-Use Templates * Simplify the writing process with clear structures or frameworks. * Reduce friction and make it easy to produce high-quality content. Step 5: Publish and Amplify * Publish content on company blog and relevant external channels. * Encourage engineers to share through personal and professional networks. Step 6: Track, Review, and Refine * Regularly check engagement metrics and feedback. * Continuously adapt and improve content approach based on data. Use these points to shape and refine a plan that works for you.

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Hiring tech contractors has become more challenging. Not because the demand isn’t there, it’s quality. The new adjusted rate cards have a lot to do with it. On paper, it’s an employer’s market as there is more supply than demand, so rates have come down compared to 12 months ago. But top talent is and will always be at a premium. Rate cards speak to the market as a whole, not the top tier. This is creating friction. Leaders are navigating exceptions, or finding creative ways to bring in the right people outside of standard staffing programs, because at the end of the day, mission-critical projects don’t slow down just because rate cards do. With regulatory pressure forcing modernization, upgrades, and system builds while AI demand is sky rocketing; top talent will continue to be essential. The new rate cards just make it more interesting in how you attract and engage them. And that’s why we’re working closely with tech leaders who need the best people in place to deliver.

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I feel like I am writing a post about a new skill set I am running into every week. This week I have received 3 inbound requests for AI SDET’s. This isn’t traditional QA. The best SDETs right now are: * Using AI to generate tests from plain English, tickets, even designs * Running agent-based testing that explores apps like real users * Managing self-healing test suites that don’t break every deploy * Acting as a layer between AI-generated code and production It’s less “tester” and more: AI output validator + systems thinker + engineer For candidates: If you can combine Playwright/Cypress + LLMs + real system thinking… you’re in a top 10% bracket overnight. For companies: If you’re shipping AI-assisted code without upgrading your QA function… you’re taking on more risk than you think. If this is you get in touch I have jobs for you! #ai #aijobs #bostonjobs #hiring

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Had a great chat this week with a hiring manager (and one of my favorite people I have met on my recruitment journey) at a mid-sized product company. They said: “We’re not trying to compete with Big Tech on comp. We just want smart, practical engineers who can ship AI into real products.” Tbh this is a hard find. Honestly though, that’s the right mindset. This is a people leader who does not live in theoryland. Not every AI hire needs to be a researcher. Not every AI role needs a PhD. In fact, most companies prefer M.S. or B.S. degrees where they are working on the tangible and have real practitioner skills. Sometimes, the best move is finding an engineer who gets how to use models, not build them (probably my least crazy take), can move fast without over-architecting (I feel like I am on repeat here) and knows when to push back on hype. This client has scaled so effectively because they do what they need to do to be successful and have blinders on to the noise when it is not productive. At People In AI, we’re seeing more teams take this approach and it works. If you're trying to scale practical AI, you don't need a unicorn. You need clarity and speed. Let’s make it happen.

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Quick tip for the engineers in my network who are trying to reduce recruiter spam. I know the instinct is to keep your LinkedIn pretty minimal - less info means fewer random messages, right? Actually, it's the opposite. When your profile has limited information - sparse bio, vague title, empty experience section, but you check the basic boxes on YOE and work at target companies, you're accidentally inviting more spam, not less. I'll tell you why: most recruiters aren't actually reading your profile. They're filtering by a few criteria (years of experience, company names, job title keywords) and blasting messages to everyone who matches. If your profile is light on details, there's nothing there to help them self-select out. You look like a potential match to everyone. But when your profile has actual information: your tech stack, what you've built, what you care about, what kind of work you're looking for, recruiters who do read profiles (and some of us do) can look at it and go "okay, not a fit" before ever bothering you. The clarity doesn't invite more emails. It filters out the wrong ones. I look at every single profile before I reach out. If your bio says you're deep in ML infrastructure and I'm recruiting for a full-stack role, I'm not going to waste your time or mine, but if your profile just says "Software Engineer" with no other context? I have no way to know if it's relevant or not. The unfortunate reality is that the bulk-blast recruiters aren't going to stop. They don't read profiles anyway, but the recruiters who are trying to be thoughtful and targeted? We need something to work with. So if you're getting buried in irrelevant messages, adding more detail to your profile might actually help cut down the noise. Counterintuitive, but true.

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Let's talk about the hire that's quietly bleeding your budget. A Senior Full-Stack Developer. 7+ years of experience. The kind of person your product depends on. In the US, you're looking at $15,500–$19,500/month all-in. If you can even find one. Through Nir-Yu, in Latin America? $6,450/month. Total. That's it. And before you say "yeah but what's the catch"... let me show you exactly where that $6,450 goes, because that's kind of the whole point. ✅ Developer salary: you see it ✅ Benefits, taxes, compliance, EOR services: itemized ✅ Our management fee: fixed, visible, $299–$599/month No bundled mystery rate. No 80%+ markup buried in "overhead." No finding out 8 months later your developer was earning a fraction of what you thought. We call it Cost-Plus. The industry calls it unusual. I call it the only way to actually build trust with someone you're betting your product on. The savings? 67–75% compared to a US equivalent hire. But here's what I want you to sit with for a second: that's not just a cost win. It's a signal. When your developer knows exactly what they're earning and gets fair compensation, real benefits, career growth baked in, they stay. They perform. They give a damn. That's the difference between short-term savings and long-term leverage.

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For years, they hired through agencies. It was expensive. Reactive. Always chasing. We made one simple change. Brought in a single embedded recruiter. The result? - No more scrambling. - Steady pipeline of qualified candidates. - Better hires, faster. Hiring became much more calm. The team got focused. And growth became predictable again. Sometimes the smartest move isn’t a big one. It’s replacing “the old way” with a better system. #Hiring #BusinessGrowth #Leadership #Recruitment #Scaling #KoreRPO

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