It was very context specific, but the critical advice YC gave us: 1. Start a new class monthly, not every 6-12 months, which is why we’re about to start cohort 13 not cohort 2. 2. We wanted to sell future cashflows on the blockchain. They pointed out you don’t need cryptohttps://twitter.com/lpolovets/status/1011490957521444865 …
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Replying to @AustenAllred
#1 is great -- optimizing for more iterations/at-bats can be truly game-changing.
2 replies 0 retweets 17 likes -
Replying to @lpolovets
Seriously revolutionary. A competitor ended up having had 40 students after two years. We’ll have had at least 1,500 by then. Learning to do Lambda at scale is completely different than 20 ppl at a time. Funnily enough it’s actually better there because then you can specialize.
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Replying to @AustenAllred
I once saw a talk (by
@SeanEllis iirc) on running growth teams. I may be misstating it, but the speaker suggested using "# of experiments/time period" as a KPI. I always thought that was good advice for startups in general. The more tests you do w/customers, the faster you learn.3 replies 4 retweets 43 likes -
Replying to @lpolovets @SeanEllis
I think that’s a great metric. Lambda employees will tell you that whenever we have an idea on something to try we try to figure out how to launch an MVP of it in thirty minutes or less. Most experiments don’t work, but if a test only takes 30 mins we have almst infinite swings
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1. “Trials” - an easy way to interview a handful of students and if you like one contract it for n months. That was landing page + calendly -> Slack then manual work 2. Inviting outside engineers to capstone defenses. We invited 4 engineers, 2 hired students (!), now scaling
2 replies 0 retweets 12 likes
Yup, but instead of a thesis you’re defending your final project, its code, and your understanding of it to Lambda staff, hiring partners, and outside engineers. That was also an experiment at one point. Everything was.
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