Philosophy Mondays: Human-AI Collaboration
Today's Philosophy Monday is an important interlude. I want to reveal that I have not been writing the posts in this series entirely by myself. Instead I have been working with Claude, not just for the graphic illustrations, but also for the text. My method has been to write a rough draft and then ask Claude for improvement suggestions. I will expand this collaboration to other intelligences going forward, including open source models such as Llama and DeepSeek. I will also explore other moda...

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Web3/Crypto: Why Bother?
One thing that keeps surprising me is how quite a few people see absolutely nothing redeeming in web3 (née crypto). Maybe this is their genuine belief. Maybe it is a reaction to the extreme boosterism of some proponents who present web3 as bringing about a libertarian nirvana. From early on I have tried to provide a more rounded perspective, pointing to both the good and the bad that can come from it as in my talks at the Blockstack Summits. Today, however, I want to attempt to provide a coge...
Philosophy Mondays: Human-AI Collaboration
Today's Philosophy Monday is an important interlude. I want to reveal that I have not been writing the posts in this series entirely by myself. Instead I have been working with Claude, not just for the graphic illustrations, but also for the text. My method has been to write a rough draft and then ask Claude for improvement suggestions. I will expand this collaboration to other intelligences going forward, including open source models such as Llama and DeepSeek. I will also explore other moda...

Intent-based Collaboration Environments
AI Native IDEs for Code, Engineering, Science
Web3/Crypto: Why Bother?
One thing that keeps surprising me is how quite a few people see absolutely nothing redeeming in web3 (née crypto). Maybe this is their genuine belief. Maybe it is a reaction to the extreme boosterism of some proponents who present web3 as bringing about a libertarian nirvana. From early on I have tried to provide a more rounded perspective, pointing to both the good and the bad that can come from it as in my talks at the Blockstack Summits. Today, however, I want to attempt to provide a coge...
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Today our portfolio company Sift Science announced not only their $30 million Series C, led by Insight Venture Partners, but also several new product offerings. This is exciting because it reveals the team’s larger vision of “Powering Trust Online” and makes that concrete by going beyond payments fraud to address content, promo and account abuse. These products have been developed with customers and are available now (content abuse, promo abuse, account abuse).
Sift’s execution is a great illustration of what I refer to as having a “big vision and an on-ramp,” when people ask me what it takes to build a big business. The idea of fighting many different types of fraud and thus helping to create trust on the internet was always what excited the team and us as investors. But when you have a very big vision it can often be challenging to get started. A common failure mode for startups is to try to solve lots of problems all at once and as a result not solve any of them well.
Instead, Sift Science remained focused on payment fraud as their on-ramp for several years. This focus helped build a superior service and a wonderful customer base and along with it a massive data set. Sift applies machine learning techniques to this data to provide realtime decisions at scale. As we had originally expected, it turns out the same approach and much of the same data works well for other types of fraud.
Congratulations to the entire team at Sift and a warm welcome to Insight Venture Partners as a new investor. For everyone looking to join the exciting mission of building trust on the internet, Sift Science is hiring!
Today our portfolio company Sift Science announced not only their $30 million Series C, led by Insight Venture Partners, but also several new product offerings. This is exciting because it reveals the team’s larger vision of “Powering Trust Online” and makes that concrete by going beyond payments fraud to address content, promo and account abuse. These products have been developed with customers and are available now (content abuse, promo abuse, account abuse).
Sift’s execution is a great illustration of what I refer to as having a “big vision and an on-ramp,” when people ask me what it takes to build a big business. The idea of fighting many different types of fraud and thus helping to create trust on the internet was always what excited the team and us as investors. But when you have a very big vision it can often be challenging to get started. A common failure mode for startups is to try to solve lots of problems all at once and as a result not solve any of them well.
Instead, Sift Science remained focused on payment fraud as their on-ramp for several years. This focus helped build a superior service and a wonderful customer base and along with it a massive data set. Sift applies machine learning techniques to this data to provide realtime decisions at scale. As we had originally expected, it turns out the same approach and much of the same data works well for other types of fraud.
Congratulations to the entire team at Sift and a warm welcome to Insight Venture Partners as a new investor. For everyone looking to join the exciting mission of building trust on the internet, Sift Science is hiring!
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