Morgan Khodayari

Most tech startup founders think the problem with their hiring is comp/benefits/equity. News flash: it’s usually none of those. The real issue is rooted in clarity. Candidates want to understand: • What problem they are being hired to solve • What success looks like • How much chaos to expect • How empowered they will be • Whether leadership actually knows what they want You don't need the perfect job description. You just need a clear one. Clarity is the new competitive advantage in tech hiring!

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Block's decision to cut 4,000 people this week got me digging into what's really happening across tech layoffs right now. The pattern looks familiar. In the last 3 months alone: Amazon cut 16,000. Meta cut 1,500. Pinterest 700. eBay 800. Mastercard 1,400. Salesforce ~1,000. Block 4,000. January 2026 saw the highest US layoff announcements since 2009, up 118% YoY. Nearly all of these companies are profitable. Many are posting record numbers. And nearly all cited AI as "a" or "the" reason. But here's what the data and my own experience actually suggests is likely happening in three phases: Phase 1 >> Cut (now): Eliminate high-cost IC roles doing routine work in expensive markets. Frame it as AI transformation. Generous severance buys goodwill. Stock jumps 10-25% overnight. The market rewards headcount reduction, and cost discipline. Phase 2 >> Shift (12-24 months): Quietly backfill those same functions at 30-70% lower cost in India, SEA, and Eastern Europe. A January 2026 Blind survey of 2,392 verified tech professionals found 38% say India hiring is replacing US roles not complementing them. Phase 3 >> Automate (2-4 years): Use the freed-up capital to build AI systems that eventually automate the offshore roles too. The lower-cost workforce is the transitional bridge, not the destination. Forrester's data backs this up: 55% of companies that cut staff for AI ended up rehiring, just not at the same price or in the same location. Their prediction is blunt: "Much of this work will be given to lower-wage human workers, offshore or at lower salary, under the guise of AI." There is no disputing that AI is the future. The cost pressure during the transition is real. But what's being sold as a technology transformation is, right now, a workforce geography play with AI as the eventual endgame. The people making and communicating these decisions aren't necessarily lying about where this ends, but they're not being explicit about the path to get there. What is your take on this?

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One of TA’s biggest problems right now is fraudulent candidates… Anyone working in-house knows the pain of inbound applications compounded with not knowing if candidates are really who they say they are. Well, my friends at Gem just announced their new AI agent that detects fraud and then assesses overall risk. Here’s what it does: Automatically scans applications when submitted Evaluates fraud risk using multiple signals (resume metadata, email, phone, LinkedIn, person verification, IP, and device) Assigns a risk level to each application (not just flags) Works where recruiters already review applications — no tool switching (if you’re a Gem user 😉) Recruiters maintain full control to advance or reject suspicious applications Enable Fraud Detection per-job for flexibility This is going to save so much time and put the power back in the hands of the recruiter. You can sign up for the waitlist the in the comments or comment waitlist if you don’t see it. Thanks Gem. #partner #sponsor

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