good morrow,
i write to you as i watch my hometown perform an interpretive dance with destruction that nobody asked for. watching places you know turn to smoke hits different than watching portfolio liquidations - though this week decided to serve us both, because why choose just one flavor of devastation?
nature's own loss porn, if you will
but hey, phoenix metaphors exist for a reason
xx c
Crypto markets suffer worst sell-off in a month. ZKsync launched its Ignite program, allocating 300M $ZK (valued at $60 million) over 9 months to boost liquidity on its Era L2 network. Wayfinder is enabling AI agents to autonomously navigate crypto rails, simplifying complex crypto interactions by translating them into natural language. South Korea plans to lift institutional ban on crypto trading. 97.8% of nft mints on Base are now coming from Rodeo. StealthSDK integrated ElizaOS into their Roblox game. Ripple President Monica Long said in a Jan. 7. Bloomberg News interview that an XRP ETF is likely next in line after Bitcoin and Ethereum's ETFs. Nicholas covered which Agent Frameworks have the highest leverage on his latest episode. In anticipation of BIO Protocol’s token launch last Friday, DeSci tokens mooned. Coinbase was subpoenaed in Polymarket investigation.
The Cognition Stack
Scott Belsky proposes a fascinating vision of future "cognicos" (cognition-driven companies) where AI and data form the core instead of traditional organizational hierarchies. These companies will be built around a "cognition stack" with three key elements: a nucleus of data and AI models at the center, function-specific "nodes" around the edges (like sales, HR, marketing), and humans serving as stewards, orchestrators, and leaders. While AI handles much of the computational reasoning and day-to-day operations, humans retain crucial roles in maintaining data quality, orchestrating AI systems, and providing strategic leadership.
Just as value in crypto shifted from infra to apps, the real opportunity lies in building companies that can effectively use these AI foundations. AI's ability to easily copy complex systems makes traditional tech moats less relevant. Instead, we see brand value and trust becoming crucial differentiators, much like how successful crypto projects thrive despite being open source. I particularly appreciate its "pro-human" perspective - rather than predicting total automation, it envisions humans retaining important stewarding and leadership roles in these AI-native organizations. This feels like a refreshing counterpoint to more doom-laden predictions about AI's impact on the workforce.
Will Capital be King in the AI Economy?
This article from L Ruldolf L argues that after labor-replacing AI arrives, capital will matter more than ever - contrary to common wisdom that "money won't matter post-AGI." This could lead to a more static, feudalistic economic structure, where those with capital today become permanently entrenched. The author uses the example of SpaceX vs Blue Origin to illustrate how currently, even massive capital (like Bezos had) can't easily buy top talent and execution. But in an AGI world, capital could directly buy virtually unlimited AI talent, potentially making it harder for scrappy upstarts to compete with well-resourced incumbents.
We had some pushback to this doom-and-gloom view though. Throughout history, technological inflection points like the printing press or even Twitter have often led to more democratization and dynamism, not less. Breakthroughs often come from "non-consensus insights" where someone can "toil away in obscurity" before breaking out - and more capital in unimaginative hands won't necessarily stop that. The key dividing line of the future might not be capital access but rather human agency and vision. Current AIs are actually quite bad at maintaining long-term objectives and focus - core traits needed for leading organizations. Highly motivated individuals who can effectively orchestrate AI tools while maintaining clear vision could still have outsized impact, regardless of their starting capital.
Crypto networks can also speedrun AI by incentivizing contributions to high-quality datasets, decentralized computational power, and open-source model development, fostering broad collaboration without requiring upfront capital investment. This approach, demonstrated by projects like Nous Research, Prime Intellect, and Bittensor, has the potential to outpace traditional, private company efforts over time.
right now is a great time to do something ambitious. Robin Hanson calls the present "the dreamtime", following a concept in Aboriginal myths: the time when the future world order and its values are still liquid, not yet set in stone.
Another interesting post's reference to the "dream time" concept, which came up at the end of the article. We're living through a crucial moment that future generations will look back on as a time of incredible change and potential. Rather than get paralyzed by pessimistic scenarios, this framing resonates - it suggests the right move is to actively participate in defining this moment, regardless of how the technology ultimately develops.
Live & online Fridays at 10am PT / 1pm ET.
A new framework to match new realities.
My essay for @collab_currency.
AI, Crypto, and America
By: Derek Edws, Managing Partner @ Collab+Currency
565
The more I think it perfectly parallels to the 19th century advent of the corporation: able to enter contracts itself, hire humans, own things, and outlive people.
Corporations were feared, and now number in the millions. We all work for them…
@rodeodotclub
@VECTORDOTFUN
@interfacedapp
@withportrait
@anondotworld
@Veildotcash
@thecastmoney
What else is worth trying?
economic alignment with the products' growth (not decentralization)
clearly there are tradeoffs--and trading off decentralization…
