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How Substack Creators Are Covering This Strange Markets Era
Brief
How Substack writers and independent researchers are covering AI-era market dislocation was the focus of a live-panel conversation hosted by Tracy Alloway and Joe Wisenthal that featured James van Gelan (Satrini Research), Jasmine Sun (Substack writer on AI culture) and Sam Ro (newsletter editor). The discussion moved from the role of journalism in market ecosystems to the concrete technical and geopolitical dynamics reshaping AI. James opened from his viral scenario about mass job losses (a post that ran around February and drew intense public response and even threats), framing his worry as less about the long-term promise of AI and more about the unprecedented speed of the transition. Jasmine emphasized that most AI coverage caters to insiders and that readers outside tech need clear explanations about AI's effects on parenting, education and affordability; she also argued that alignment and safety work is not a luxury but central to a model’s practical value because controllability determines utility.
The conversation turned empirical as Jasmine reported from China: she described Chinese labs operating in a more academic, collaborative mode with less cultural emphasis on alignment, hamstrung in part by compute/chip constraints because of export controls. James flagged hardware as a strategic frontier — not models alone but chips and memory — noting recent DRAM/memory rallies and predicting that bottlenecks will attract engineering fixes. On content and distribution, Sam admitted experimenting with Claude to mimic his voice, raising the practical risk that newsletters and analysis could be replicated; nevertheless all three argued that human reporting — secrets, gossip, tacit, in-person observation — remains a durable advantage because models are trained on past public material. They closed by highlighting physical automation: Jasmine described humanoid and quadruped robots operating in factories and a robotic pharmacy in China, and James pointed to a broader robotics boom in logistics. The guests converged on one central tension: broad long-term benefits from AI vs. near-term political and economic disruption driven by the pace of change, which will push debates over reskilling, universal supports and how journalism itself should evolve.
Why it matters
James van Gelan (founder of Satrini Research) wrote a widely read viral scenario about mass AI job losses (first published around February) that generated intense online reaction — he says it even led to credible death threats and has changed how he thinks about distribution and research.
Key details
- Jasmine Sun (Substack writer on AI and Silicon Valley culture) argued most AI media is 'by AI people for AI people' and that more coverage should focus on how AI affects parenting, education, politics and affordability; she also said alignment/safety work is tightly coupled to a model's economic usefulness because controllability determines real-world utility.
- Sam Ro (editor of the 'stocks usually go up' newsletter t K) said he remains nervously bullish — he checks his 401(k) daily, worries about market peaks and acknowledged experimenting with Claude to build a 'Sam robot' trained on his public writing, highlighting the near-term risk that models can replicate individual voices and cadence.
- On China, Jasmine reported from the field that Chinese AI appears to be in a more academic/collaborative phase, with labs less focused on safety/alignment and more constrained by compute (because of chip controls); Chinese companies adopt open-source tools quickly because government direction and domestic competition prioritize fast uptake.
- James flagged hardware as the next strategic battleground: he expects the 'next Chinese deep-tech moment' to be about chips/hardware rather than models, noted the recent DRAM/memory price rally and warned that investor bets on bottlenecks invite technological responses that will widen those bottlenecks.
- All three emphasized the enduring value of human, on-the-ground reporting and tacit knowledge: first-person investigations (James' examples like the Strait of Hormuz reporting and Jasmine's China visits) produce private or timely knowledge that current models — trained on scraped public data — cannot replicate.