BackOps AI Builds Talent Density with DJ L as Head of People & Talent

"Before I leave for my trip THANK YOU for all the inspiration with AI. A month ago I never would have imagined I could do what I did. My first cron job is checked and works. My team is getting near-real-time prioritization based on the biggest impact. This is crazy." - from a colleague last week. Seven weeks ago I built my own AI Chief of Staff. Since then: 50+ projects, 3,000+ prompts, 200M+ tokens weekly. Outside of meetings, Claude Code is my workplace. After two years of evangelising AI internally, I switched modes: AI is no longer optional at Groupon. Amit Shah, our Board's AI committee Chair, framed it cleanly - speed is the new moat. Everyone got access to Claude and Gemini. Every manager was asked to ship an AI automation by end of April. Every leader has to build, not just direct. What's happened in the last few weeks has no parallel in my career (and I've done my share of startups). Whole teams have rewired how they work. The "addiction" I described in my earlier post wasn't unique to me - I see the same passion in many colleagues. I already hired several AI Builders but I need more. If you live in Claude Code and want to own and solve a real business problem at scale - DM me. I need fullstack Builders: equal parts business operator and AI-first engineer. Hard workers. Hands on. No one's manager but their own.

AI was cited as a factor in roughly 25% of layoffs in early 2026. 📽 While not all layoffs are solely due to AI, the technology is increasingly part of cost-cutting strategies, especially in areas like content production, marketing, and post-production, where AI tools can now handle tasks that once required large teams. Read more about it here: https://lnkd.in/epjcAf_S

⚠️ 𝗧𝗵𝗲 𝗺𝗼𝘀𝘁 𝘃𝗮𝗹𝘂𝗮𝗯𝗹𝗲 𝘀𝘁𝗮𝗿𝘁𝘂𝗽 𝗶𝗻 𝗵𝗶𝘀𝘁𝗼𝗿𝘆 𝗶𝘀 𝗹𝗼𝘀𝗶𝗻𝗴 $𝟱𝟬 𝗯𝗶𝗹𝗹𝗶𝗼𝗻 𝗮 𝘆𝗲𝗮𝗿. 𝗔𝗻𝗱 𝗻𝗼𝗯𝗼𝗱𝘆 𝗵𝗮𝘀 𝗮 𝗽𝗹𝗮𝗻 𝘁𝗼 𝗳𝗶𝘅 𝗶𝘁. Six months ago, OpenAI was crowned Company of the Year. Sam Altman was the Napoleon of AI. The world was watching with admiration. Today? The ship is sinking , and here's why every tech professional should pay attention. - 𝗦𝗼𝗿𝗮 — the "future of media" — shut down. It was burning $1M per day with almost no users. - 𝗗𝗶𝘀𝗻𝗲𝘆 cancelled a $1B partnership deal immediately after. OpenAI didn't even inform them in advance. - 𝗡𝗶𝘃𝗶𝗱𝗶𝗮 walked away from a $100B investment deal, privately citing a lack of business discipline. - 𝗘𝗹𝗼𝗻 𝗠𝘂𝘀𝗸 is suing for up to $134B in damages. - 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 — OpenAI's biggest partner — is now weighing legal action. - ChatGPT is now showing ads. Sam Altman had previously called this a "last resort." - After the Pentagon contract, 𝘁𝗵𝗼𝘂𝘀𝗮𝗻𝗱𝘀 𝗼𝗳 𝘂𝘀𝗲𝗿𝘀 𝗱𝗲𝗹𝗲𝘁𝗲𝗱 𝗖𝗵𝗮𝘁𝗚𝗣𝗧 𝗮𝗻𝗱 𝘀𝘄𝗶𝘁𝗰𝗵𝗲𝗱 𝘁𝗼 𝗖𝗹𝗮𝘂𝗱𝗲. Now look at the numbers — 𝗡𝗲𝘁 𝗹𝗼𝘀𝘀 𝗶𝗻 𝗷𝘂𝘀𝘁 𝗼𝗻𝗲 𝗾𝘂𝗮𝗿𝘁𝗲𝗿: $𝟭𝟮.𝟲 𝗕𝗶𝗹𝗹𝗶𝗼𝗻. Annual burn rate: $𝟱𝟬.𝟰 𝗕𝗶𝗹𝗹𝗶𝗼𝗻.  Revenue needed to break even: $𝟭𝟮𝟱–𝟮𝟬𝟬 𝗕𝗶𝗹𝗹𝗶𝗼𝗻/𝘆𝗲𝗮𝗿. Current revenue: ~$𝟮𝟬 𝗕𝗶𝗹𝗹𝗶𝗼𝗻. They need 6–10x revenue growth just to survive. No clear plan on how to get there. The most likely outcome? Microsoft acquires it , probably at a fraction of its peak valuation. The brand survives. The mission doesn't. ChatGPT introduced millions of us to AI. It changed how we work, write, and think. That legacy is real. But legacy doesn't pay $50 billion in annual losses. What do you think , can OpenAI pull off a comeback, or is this the beginning of the end? Drop your take below. 👇 #OpenAI #ChatGPT #ArtificialIntelligence #TechNews #AITrends #FutureOfAI #SamAltman #StartupStrategy

Everyone wants a "full-stack AI engineer." Founders love it. Investors love it. Job posts are stuffed with the term. But here's the truth: the full-stack AI engineer is a myth, especially at early-stage startups. One person doesn't build models, clean data, write APIs, deploy to production, and design infrastructure. Not well. Not under real startup pressure. I've watched teams hire unicorns who "do it all." A few months in, nothing ships. The codebase is a mess. Nobody owns anything. Everything slows to a crawl. Early-stage AI is chaos. You need specialists who can cross lines, not generalists stretched thin. Stop chasing the unicorn. Build a small team where each person owns a real part of the stack. Make sure they can talk across boundaries. The hero engineer is a fantasy. A team that can actually deliver is not.

There are two AI talent markets right now: Most founders don't know which one they're operating in. Market 1: Frontier labs. @OpenAI, @Anthropic, @DeepMind. Senior ML engineers at $600K to $1M+ total comp. Equity upside in the billions. Market 2: Everyone else. Enterprise ML engineers at $170K to $245K. A completely different pool. Competing on completely different terms. What I keep seeing: seed and Series A founders benchmarking against Market 1 and losing every offer. You cannot win that fight with cash. But you can win with equity framing, mission specificity, and a sharp hiring process. Most AI startups at your stage aren't doing any of those things. The engineers you're losing to OpenAI? A lot of them would choose you. Do you know how to make the case?

AI Weekly Roundup - Tech News Edition #14 Week of May 19 - 24, 2026 ① Anthropic is closing a $30B round at a $900B+ valuation. That makes it the most valuable private AI company in the world - surpassing OpenAI ($852B) before either has even gone public. Revenue: $45B annualized. Up from $9B just 6 months ago. Investors: Sequoia, Dragoneer, Altimeter, Greenoaks, Founders Fund. IPO target: as early as October 2026. ② Meta fired 8,000 people to fund its AI spending spree. 10% of the entire workforce. Gone. $145B in AI capex planned for 2026. 7,000 more employees “reassigned” to AI pods - involuntarily. New internal job titles: “AI builder.” “AI pod lead.” Meta is also tracking employee keystrokes to train AI agents. ③ The tech industry has shed 142,000 jobs in 2026. Meta 8,000. Intuit 3,000 (17% of workforce). Microsoft 8,750 buyouts. Cisco 4,000. Oracle 30,000 quietly in March. Every company that cut jobs posted record revenues the same quarter. The market rewarded all of them. ④ OpenAI Codex can now work while your Mac screen is locked. “Locked Use” - announced May 21. Codex runs agents on your Mac even when you’re away. Temporal and behavioral safeguards. Human approval gates. 2 million weekly active users and growing. ⑤ Anthropic + OpenAI both launched Wall Street AI agents in 72 hours. Anthropic: 10 pre-built agent templates - pitch building, KYC, GL reconciliation, month-end close, underwriting, earnings review. OpenAI + PwC: procurement agents, IR management, contract processing. The race to become the operating system for finance is on. ────────────────────────────────── Here is the uncomfortable math nobody wants to say out loud: 142,000 tech jobs cut in 2026. Every company posted record revenue. Stock prices went up. The market is not punishing AI-driven layoffs. It is rewarding them. For #QA and #SDET engineers - this is not a warning. It is a deadline. The engineers who survive and thrive this year are the ones who learn to supervise AI agents - not compete with them. ────────────────────────────────── Which number hit you hardest? ① Anthropic at $900B - is this real or a bubble? ② Meta’s 8,000 layoffs - restructuring or replacement? ③ 142,000 tech jobs gone in 2026 is yours safe? ④ #Codex working while your screen is locked Drop your number, I read every comment. Follow for Edition 15 next Sunday. Every week. No fluff. Just what matters for AI & QA engineers. #AI #QAAutomation #SDET #Anthropic #MetaLayoffs #TechLayoffs2026 #GenerativeAI #AgenticAI #FutureOfWork #TechNews2026 #MCP #ClaudeAI

Will we see (i) an adjustment in how pricing/billing works for AI-coding assistants (ii) more layoffs and/or increased budget allocation to AI (iii) new entrants that address this in the market in a different way or (iv) a reduction in AI-coding usage because the cost is too high? Open to opinions but interesting to note that both Microsoft and Uber claim that they burned through their entire 2026 budget for AI-coding in just a few months. Is "price per token" really workable? https://lnkd.in/g9cN9vFg

Just one afternoon. That’s all it took for over 600 OpenAI employees to collectively cash out an estimated ₹56,000+ crore ($6.6B) in a private share sale. (New York Post) No IPO. No ringing Nasdaq bell. No public market frenzy. Just a tender offer. A financial mechanism where employees sell shares directly to investors while the company stays private. Around 75 employees reportedly hit the maximum payout cap of $30M each. (New York Post) Some early OpenAI equity packages appreciated more than 100x in roughly seven years. (LinkedIn) This is what the AI gold rush looks like from the inside. And the deeper story isn’t just wealth. It’s labor market bifurcation. Because while OpenAI researchers were becoming decamillionaires overnight… The broader tech industry was simultaneously going through layoffs, hiring freezes, and rising unemployment. Two economies. One industry. The AI talent market now behaves less like traditional tech hiring… …and more like elite sports free agency. Anthropic. Google DeepMind. xAI. Meta. All competing for a tiny pool of frontier researchers capable of pushing model intelligence forward. OpenAI’s tender offer wasn’t just generosity. It was retention infrastructure. Because when competitors are willing to throw nine-figure compensation packages at elite AI talent… Liquidity becomes a defensive weapon. That changes startup economics completely. In the SaaS era: → capital chased companies In the AI era: → capital chases people And the scarcest infrastructure today may not be GPUs. It may be elite cognition. The most important shift here is psychological. For decades, startup employees accepted “paper wealth” with the hope of a future IPO. OpenAI just showed that in the AI era, employees may achieve generational liquidity before public markets even enter the picture. Private markets are becoming the new public markets. Retail investors increasingly arrive after: → VCs → insiders → sovereign funds → employees → strategic partners have already captured most of the upside. This is why AI feels different from previous tech waves. The speed of wealth creation is compressing. The concentration of rewards is intensifying. And the gap between frontier AI firms and the rest of the tech industry is starting to resemble an entirely separate economic system.

This is spot on. The strongest AI talent right now doesn’t even look like traditional “engineering talent” anymore. Some of the most impressive people we meet are: - ex-founders - MIT/Stanford PhDs (top ivys) - insanely inquisitive operators - engineers who own product like founders do But honestly the resume matters less than the mindset. The people who stand out are the ones who WILL find the answer. scrappy. The ones who can sit in ambiguity and still ship. The ones who own features end-to-end instead of waiting for perfect requirements. The ones who care about customer outcomes, not just model benchmarks. 0 → 1 AI product building is a very different game. You need people who can: build, debug, talk to users, rethink workflows, move fast, and make good decisions with incomplete information. That combination is still incredibly rare. The gap between “can use AI tools” and “can build AI products that actually work at scale” is becoming very obvious.