Garrett Lord
@GarrettLord
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CEO/Founder of @joinhandshake
San Francisco, CA
Joined November 2011
That’s the idea - train the humans before the robots do.
But I thought AI would take all jobs ?
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The mind-blowing tech behind microchip manufacturing. Lasers fire 50,000 times per second at tin droplets moving 100 m/s, creating extreme ultraviolet light plasma — and that’s just one step inside ASML’s chip-making machine. https://t.co/fahBNoadDa
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This is rad. Congrats @sundarpichai and team!
An exciting milestone for AI in science: Our C2S-Scale 27B foundation model, built with @Yale and based on Gemma, generated a novel hypothesis about cancer cellular behavior, which scientists experimentally validated in living cells. With more preclinical and clinical tests,
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At #ConnectedStack, @AnthropicAI's new CCO Paul Smith joined @joinHandshake CEO @GarrettLord. Up for discussion: 👉 Why join Anthropic as CCO now? 👉 What does this signal about enterprise adoption + scale? 👉 What does it really take to win enterprise AI? 🎥Below ↓
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Disruption is coming, and luck won’t cut it. But Gen Z holds the biggest toolkit humanity has ever built: AI, technology, and endless options. That’s the real advantage.
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We want to accelerate this growth. That’s why we built a course anyone can take to develop AI skills before graduation.
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The job market is about to change dramatically. But it'll need early talent more than ever. Our data shows employers agree: 73% of managers say entry-level hires are more comfortable with generative AI than senior staff.
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Gen Z is adopting AI faster than anyone: 2× the rate of Gen X and 5× faster than those 65+. College seniors are listing AI skills on resumes at twice the rate of students just four years ago. This is in every field, not just tech.
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One in three CS grads already regret their degree because of AI. Higher education institutions are trying their best to keep up with seemingly daily advances. But there are bright spots.
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Our platform shows a challenge for early talent right now. Software developer postings have fallen to just a quarter of their March 2022 peak, far outpacing the slowdown in overall job availability nationwide.
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The debate over AI's impact on early careers is stuck between two extremes. Some believe today's students are the luckiest in history. Others talk about a "white-collar bloodbath." Both are wrong. I run a $200M+ career network and this is what the data says 🧵:
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9-week old: RLHF milestone reached ➡️fake cries get faster mom-response
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Insights I derived: 1) AI writes with you and not for you. 2) Habits are already forming. 3) Consumer use is driving enterprise adoption. I have left out many smaller but fascinating trends revealing countless opportunities for anyone building on AI.
OpenAI published a 64-page report breaking down exactly how 700M people use ChatGPT. Some interesting observations:
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17. Occupations Patterns repeat across jobs. Managers and business roles lean heavily on writing. Computer professionals use it more for technical help. But across fields, decision-making is a top-2 activity.
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16. Education & work use People with college or graduate degrees send a higher share of work messages. The more educated the user, the more they lean on ChatGPT for job tasks.
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15. Geography Growth accelerated in lower-income countries. AI adoption is global, not just a Silicon Valley toy. This means opportunities for OpenAI for localized UX and billing models.
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14. Age adoption Nearly half of all users are under 26. This is Gen Z’s default productivity tool. They will carry these habits into the workforce.
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13. Usage by Gender: Women typically use it more for writing and practical guidance. Men more often use it for technical help and seeking information.
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11. Gender Adoption ChatGPT started male-skewed but flipped. By 2025, a slight majority of active users had female-coded names. Adoption is broadening.
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10. Quality has been improving steadily. Good interactions now outnumber bad by 4:1. Model upgrades and UX tuning are making outputs consistently better. Retention follows quality.
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9. Work-specific activities For work-classified messages, the top are: 1) Documenting (writing things down) - 18.4%, 2) Decision-making - 14.9%, 3) and Creative thinking - 13%. This is why enterprise copilots often start with email, contracts, and planning.
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