Help users identify unique distribution advantages and master the lifecycle of acquisition channels to build a sustainable engine for growth and retention.
日本語の概要は準備中です。原文の説明を表示しています。
Help users recruit compatible co-founders, sequence early leadership hires to fill capability gaps, and manage the evolution of the executive team as the company scales.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Design and scale the core leadership layer that drives company growth from zero to one.
Help the user with founding executive team building using insights from 15 guests and posts across Lenny's Podcast and Newsletter.
From "Hiring your early team": "Over two-thirds of the companies hired an engineer as employee #1. Not a big surprise. In the rare case when an engineer wasn’t the first hire, it usually came down to the founding team having enough horsepower to build the V1."
Prioritize technical talent in your earliest hires unless the founding team already possesses the internal capacity to build the first version of the product independently.
From "This Week #8: Splitting equity with late-joining co-founders, favorite roadmap templates, and small changes that improve your org": "If they’re a true cofounder, would you consider giving them equity starting around 10% of the company — all the way up to a share equal to yours? For a very early stage company, we see “late-arriving cofounders” all the time. Otherwise, senior engineers/founding team would usually receive 1-5% of the company. These are all averages and situations definitely differ."
Distribute equity for late-joining co-founders based on their projected long-term contribution to the company rather than just their start date.
Ben Horowitz: "Look, you're a really good director of engineering because you do a great job at managing the team, get the products out, all that. But you're not really a CTO because to be a CTO, you have to be effective with other parts of the organization. You can't just be effective only with engineering."
Measure an executive's success by their ability to collaborate effectively across the entire company rather than just managing their own functional silo.
From "Pulling back the curtain on the magic of Y Combinator": "Solo founders are at a disadvantage. Although solo founders are encouraged, the data does show a steep decline in the number of them accepted to YC."
Recognize that while solo founding is possible, institutional investors and incubators show a statistical preference for teams with multiple co-founders.
From "Summary: Lessons from working with 600+ YC startups | Gustaf Alströmer (Y Combinator, Airbnb)": "Contracting an engineering team to build the product doesn’t really work because you can’t spec your way to a great product; you have to be part of the iterations."
Treat technical co-founders as full mission partners because great products require continuous iteration that cannot be captured in static outsourcing specifications.
From "Summary: Lessons from working with 600+ YC startups | Gustaf Alströmer (Y Combinator, Airbnb)": "The most important thing Airbnb looked for in early hires is how excited they were to be there. The second thing was to understand their true motivations and make sure they mapped to the company’s core values."
Screen your first leadership hires primarily for their level of genuine enthusiasm and alignment with the mission over their specific industry experience.
For all 8 sourced insights from 15 guests, see references/guest-insights.md
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Help users identify unique distribution advantages and master the lifecycle of acquisition channels to build a sustainable engine for growth and retention.
日本語の概要は準備中です。原文の説明を表示しています。
Help users build functional product prototypes from natural language or visual mocks using AI coding tools. This skill enables product leaders to bypass engineering bottlenecks and validate ideas through hands-on building.
日本語の概要は準備中です。原文の説明を表示しています。
Help users build robust infrastructure for measuring, monitoring, and iterating on AI product performance using human, code-based, and LLM-as-a-judge methodologies.
日本語の概要は準備中です。原文の説明を表示しています。
Help users interact with probabilistic models by designing interfaces that manage fluidity, intent, and agency while maintaining trust and control.
日本語の概要は準備中です。原文の説明を表示しています。
Help users decide where to apply AI effectively, manage the transition from deterministic to probabilistic software, and build long-term defensibility through verticalization and proprietary data.
日本語の概要は準備中です。原文の説明を表示しています。
Help users convert massive volumes of qualitative and quantitative feedback into high-confidence product decisions through rigorous synthesis and internal immersion.
日本語の概要は準備中です。原文の説明を表示しています。