The oldest people on Earth don't have complicated morning routines, do ice baths, or sleep in hyperbaric oxygen chambers.
They wake up every day with purpose, walk a lot, eat home cooked meals, and in their free time they hang out with friends.
The oldest people on Earth don't have complicated morning routines, do ice baths, or sleep in hyperbaric oxygen chambers.
They wake up every day with purpose, walk a lot, eat home cooked meals, and in their free time they hang out with friends.
If anyone is creating a company that helps companies that pulls companies up these levels, I'd love to meet. Particularly around legibility and/or non-engineer usage of AI
Students who took notes by hand scored ~28% higher on conceptual questions than laptop note-takers.
Writing forces your brain to process and compress ideas instead of copying them.
“Of course, it mean something to me to be the son of immigrants. How could it not? How the hell could it not? I grew up for a few years thinking I was just another American kid. Then I discovered at—what? five? six?—I discovered that some people thought I was a dago. A wop. A guinea. You know, like I didn't have a fucking name. That's why years later, when Harry [James] wanted me to change my name, I said no way, baby. The name is Sinatra. Frank fucking Sinatra.”
-Frank Sinatra
We have raised a $61M Series A to automate customer operations.
The world’s leading companies like DoorDash trust Giga to supercharge customer experience with AI.
We just led the Epiminds round @lightspeedvp!
I’ve spent $100M+ on performance marketing as a founder. Agencies are essential and AI changes everything.
Excited for Epiminds to power the world’s top performance agencies.
CREDENTIALS DON’T MATTER
Over the last few months, I’ve seen several A+ execs and operators flounder and fail at AI startups, while young “inexperienced” builders have crushed execution and performed superbly.
It’s the biggest discontinuity in talent evaluation I’ve seen in my 25+ years in technology.
All of one’s prior experiences, credentials, and traditional markers of success have become nearly irrelevant when the fundamental rules of the game have changed so dramatically.
The shift to AI represents such a paradigm break that institutional knowledge often becomes institutional baggage. The executive who masterfully navigated enterprise sales cycles finds themselves lost when the product builds itself. The operator who optimized for predictable growth metrics struggles when the core capability improves exponentially overnight.
Meanwhile, the 22-year-old who’s been fine-tuning models in their dorm room intuitively understands token economics, reasoning patterns, and capability scaling in ways that no MBA program ever taught. These “inexperienced” builders don’t carry the weight of how things “should” work. They don’t waste time trying to force AI capabilities into traditional product frameworks or business models. And so, they win.
If you’re an executive wanting to find a role at an AI company, be humble. Put in the work. Use the tools and create a personal AI stack. Train yourself to think differently - probabilistically, not deterministically. Be open to an IC role if needed. It’s not magic, but it will take real work.
If you’re an AI company founder, ensure your hiring process is not blinded by credentials. What matters is raw building ability (in EVERY role, not just Eng/Product/Design), comfort with uncertainty, and the ability to iterate and experiment exceptionally fast.
It’s a new era.
Proud to co-lead @reflection_ai Series A as they emerge from stealth with $130M in funding. Huge congrats to Co-Founders @MishaLaskin and @real_ioannis, and the incredible team they’ve built—one of the strongest Reinforcement Learning (RL) research teams in the world.
Misha and Ioannis bring unparalleled expertise from their time at @GoogleDeepMind, where they contributed to groundbreaking advancements in AI, particularly in reinforcement learning and decision-making.
AI-driven code generation is far more than just copilots—it’s about building autonomous systems that can truly reason, iterate, and debug like a software engineer. Reflection AI is tackling this challenge head-on, applying RL to train AI models capable of solving complex programming tasks end-to-end. Their system is designed to write, optimize, and debug code autonomously, changing how software development is approached.
Excited for what’s ahead! Read more: https://t.co/tD1iS4PkMr
Cc: @lightspeedvp@JamesAlcorn94
@JoshuaSchriver if you care about Michigan, try focusing on things that actually affect your constituents instead of whatever those who buy you want.
Why do you want to disrupt thriving families?
Mike Krieger (@mikeyk) is the CPO of @AnthropicAI ($10B+ raised) and the co-founder of Instagram, which he sold to Meta for $1B. Here's the full video of my recent conversation with him.
Mike has one of the AI industry's most interesting jobs. He shared with me how he and his team craft product strategy for the company that's leading the charge on AI in the enterprise. Specifically, we discussed how frontier model innovations both drive product and vice versa (how product ideas inform AI research).
We also talk about the long term defensibility of models (inspired by the emergence of DeepSeek), and how Mike believes that not only will individual models have specific strengths over others (such as in areas like coding, science, etc), but that a model's "vibes" will also be a major factor for driving customers' choice.
Mike also shared his view on how AI will reinvent media and the business model of advertising on the internet, drawn heavily from his work building one of the most successful ad products ever built (Instagram) and his work on Artifact, an AI news product he also co-founded.
Lastly, Mike dove deep into what it's like building for the Enterprise for the first time in his career, and how lessons from Instagram and Meta inform not only product development, but how Anthropic thinks about scaling its team in this period of hypergrowth.
Chapters:
00:00 Introduction
00:54 Mike Krieger's Journey to Anthropic
03:17 Building Product Strategy at Anthropic
07:43 Rapid Iteration and Safety
10:58 Differentiating AI Models and User Experience
17:57 Impact of AI on Consumer Products and Business Models
24:39 Enterprise vs. Consumer Product Strategy
29:19 AI in Personal Life Management
30:15 Open Source and Claude Integrations
33:09 AI-Assisted Product Development
37:13 Scaling Teams and Processes at Anthropic
42:17 Reflections on AI and Future Prospects