Token Extensions and Solana’s Long-Term Strategy | Austin Federa

We catch up with Austin, Head of Strategy at Solana Foundation and former Head of Communications at Solana Labs. In particular, we focus on how Solana continues to differentiate itself from a fast-growing array of challenger blockchain ecosystems with token extensions. We also chat about Solana's emphasis on grassroots growth over top-down business development approaches and how Solana positions itself across a variety of strategic sub sectors within the emergent crypto economy. A great overview from the perspective of one of Solana's most prominent voices. -        - Time Stamps 0:00 - Business Development strategy 5:18 - Token Extensions program 7:55 - Why build app chains anymore? 10:06 - Native L1 private transactions 14:03 - Unlocking on-chain payments 17:05 - Why Coinbase ignores Solana 19:05 - DePIN achieving PMF 24:53 - The rise of Solana-based games 30:50 - Unlocking the abundance of NFTs through compression 33:01 - Mobile strategy 38:06 - L1 governance 40:42 - Maintaining fast updates alongside decentralization   44:12 - Surviving state-level attacks 49:57 - Human coordination is the final boss? 55:59 - What is Austin excited about? -        - Podcast Resources Follow Sal: https://twitter.com/salxyz Follow Dave: https://twitter.com/SolBeachBum Follow Unlayered: https://twitter.com/UnlayeredPod Subscribe on Spotify, Apple, or Google: https://unlayered.io/ Subscribe on YouTube: https://www.youtube.com/@UnlayeredPod -        - Episode Resources Follow Austin : https://Twitter.com/AustinFedera Follow Validated : https://Twitter.com/ValidatedPod

Om Podcasten

Think beyond Ethereum and dive deep into the world of next generation blockchains. Join us as we engage with founders, engineers, researchers, investors, and critics of high-throughput, low-fee, parallelized blockchains like Solana, Monad, Sei, and more. Unlayered is for crypto natives eager to stay updated with the latest developments, complementing shows that focus primarily on Ethereum and its layered scaling approach.