Everyone says: hire people better than you, then get out of the way.
One of my biggest mistakes at Algolia was taking that literally.
Yes, hire people better than you. But don’t confuse seniority with earned trust.
Stay close at first. Inspect the work. Pressure-test the judgment. If you’re still micromanaging after 3 months, you hired the wrong person.
And trust your gut.
As a founder, you are the most fine-tuned model in the world on your own company. If something feels off, it probably is, even when the exec says, “Trust me, I’ve done this for 20 years.”
In 2013, Yale professor Ben Polak gave a legendary 1-hour lecture on Game Theory.
It will change how you make decisions in negotiations, business, and life.
His frameworks:
• Dominance arguments
• Backward induction
• The proactive bias
12 lessons to make better decisions:
i'm mass-releasing everything.
the complete automation playbook i use to run a $600K/month agency:
→ 47 n8n workflows agencies charge $5K-$15K each for
→ the one-sentence prompts that build any of them in under 3 minutes
→ my "consultant pricing" spreadsheet (what they charge vs what it costs)
→ 12 plug-and-play templates for the automations every business needs
→ the exact Claude prompts i use to debug workflows instantly
here's what's in it:
LEAD GEN (agencies charge $18K+ total):
- lead enrichment + scoring pipeline
- competitor monitoring system
- social listening engine
- cold outreach sequencer
OPERATIONS (agencies charge $24K+ total):
- client onboarding automations
- invoice recovery system
- meeting no-show rescuer
- daily CEO dashboard
CONTENT (agencies charge $15K+ total):
- blog-to-social repurposer
- AI content calendar builder
- review response drafter
- newsletter automation
every workflow is described in plain english.
paste into Synta → deploys to n8n → running in minutes.
no code. no courses. no $200/hr "experts."
i built my entire agency on these.
now you can too.
reply "PLAYBOOK" + retweet
i'll send the entire vault.
(must be following so i can DM)
taking this down friday. this should be a $997 product.
My biggest learnings from Jeanne DeWitt Grosser (ex-Chief Business Officer at @Stripe, now @Vercel COO):
1. What failed seven years ago now works with AI. In 2017, Jeanne tried to build a system at Stripe that would automatically personalize outbound emails based on company data. Despite working with world-class data scientists, it failed due to too many errors. Today, that exact same approach works. This shows how AI has made previously impossible ideas suddenly viable.
2. A single GTM engineer at Vercel reduced a 10-person sales team to 1 (in just 6 weeks). Jeanne’s team at Vercel had an engineer build an AI agent that handles inbound lead qualification, outbound prospecting, and deal loss evaluation. The agent costs $1,000 per year to run versus over $1 million in salaries for the sales team. The nine displaced team members moved to higher-value work rather than being laid off, and the remaining salesperson is 10 times more efficient.
3. Their AI deal-loss bot has become better at understanding what went wrong than humans. When Jeanne analyzed her biggest loss of the quarter, the salesperson blamed pricing. But an AI agent reviewed every email, call transcript, and Slack message and discovered the real reason: they never spoke to the person who controls the budget, and when ROI came up, the customer clearly didn’t believe the value claims. They are now using AI to analyze sales calls in real time and send alerts like “You’re halfway through the sales process and haven’t talked to a budget decision-maker yet.”
4. Wait until $1 million in revenue before hiring your first salesperson. Founders should continue selling themselves until they reach around $1 million in annual revenue with a repeatable process. The key is having a defined ideal customer profile—customers who look alike.
5. Segment customers on what drives their buying decisions, not just company size. OpenAI has roughly 3,000 employees, which would typically put them in the “mid-market” category. But they’re a top-25 website globally by traffic, so Vercel treats them as enterprise customers requiring complex sales. Effective segmentation combines company size with growth rate, web traffic, workload type, and industry—because selling to e-commerce companies requires completely different language than selling to crypto companies.
6. Most customers buy to avoid risk, not to gain opportunity. About 80% of customers purchase to reduce pain or avoid problems, while only 20% buy to increase upside. This means you should focus your sales messaging on what could go wrong without your product—like falling behind competitors or damaging their reputation—rather than just talking about exciting features. This is especially true when selling to larger companies, where individual careers are on the line.
7. Sales teams should be indistinguishable from product managers—for a bit. Jeanne hires salespeople who have such deep product knowledge that if you put one in front of a group of engineers, it should take 10 minutes to realize they’re not a product manager. This credibility allows sales teams to serve as an extension of research and development—a 20-person sales team talks to hundreds of customers weekly and can translate those conversations into product insights at scale.
8. Building your own AI sales tools may beat buying off-the-shelf software. Because AI is so new and every company’s sales process is unique, Jeanne finds that building custom internal agents often delivers more value than buying vendor solutions. A single go-to-market engineer built their deal analysis bot in just two days, perfectly tailored to their specific workflow. These engineers shadow top salespeople to understand their workflows, then build automation that would have taken months or been impossible just a few years ago.
9. Make every sales interaction great, whether customers buy or not. Jeanne replaced boring discovery calls at Stripe with collaborative whiteboarding sessions where customers drew their payment architecture. Many customers had never visualized their own systems before. They left with a useful asset and a feeling of collaboration, regardless of whether they bought. Many returned years later to purchase. Think about your go-to-market process like a product, not just a sales function.
10. Product-led growth has a ceiling—no $100 billion company runs on it alone. While product-led growth (where users can sign up and start using a product without talking to sales) works well for early growth, customers generally won’t spend a million dollars through a self-service flow. Every major technology company eventually builds a sales team for larger deals. The mistake is waiting too long, since building a predictable sales process takes time.
Our TPUs are headed to space!
Inspired by our history of moonshots, from quantum computing to autonomous driving, Project Suncatcher is exploring how we could one day build scalable ML compute systems in space, harnessing more of the sun’s power (which emits more power than 100 trillion times humanity’s total electricity production).
Like any moonshot, it’s going to require us to solve a lot of complex engineering challenges. Early research shows our Trillium-generation TPUs (our tensor processing units, purpose-built for AI) survived without damage when tested in a particle accelerator to simulate low-earth orbit levels of radiation. However, significant challenges still remain like thermal management and on-orbit system reliability.
More testing and breakthroughs will be needed as we count down to launch two prototype satellites with @planet by early 2027, our next milestone of many. Excited for us to be a part of all the innovation happening in (this) space!
He who becomes a Prince through the favor of the people should always keep on good terms with them; which it is easy for him to do, since all they ask is not to be oppressed.