Dave de Céspedes

We're baaacccccckkkkk!! After 1.5 year hiatus, we’re excited to announce the return of the Miami Tech Pod! For our first episode post-relaunch, I sat down with @gabednconfused, co-founder of @Material_HM, to talk about his path from childhood dreams of Formula 1, to winning 7 F1 championships at Mercedes, to now building a hard tech startup in Miami focused on 3D-printed batteries. It’s a conversation about the level of ambition and persistence needed to build something meaningful. Listen in and subscribe for 🔥 conversations with the founders, operators and investors shaping the future of Miami Tech. miamitechpod.com/from-winning-7…

Last week (while stalking around the SKO 😅), the same topic came up across different conversations with @OHB13 , @mschoening and @sbcatania: what would it look like to go from 10 clients, to 100, or to a 1,000? My first instinct was to scale a team. Hire more consultants. But the more I thought about it, it actually didn't seem all that interesting. The question stuck with me because of how closely consulting projects mirror each other. There are some nuances when comparing different verticals – say VCs vs. growth stage startups. But there's also a lot of overlap. After 50+ team workspaces over five years, the patterns are almost identical. The friction points are pretty predictable. Building custom workspaces has gotten incredibly easy w/ Notion AI, but teams almost always get stuck on workspace structure, defining guardrails, and (lately) clarifying the role agents can play across teams. The 1:1 time with clients is rarely about the 'what'. It's all about 'how.' Like how will we set milestones everyone needs to hit for new workflows to not only stick, but to keep improving over time. The question is how to deliver it to 1,000 teams at once. That's my top priority right now: building an AI-powered system that does what I do — proactively guides teams through workspace structure, trains them on new ways of working, and coaches them into building something that has a meaningful, tangible impact on their success. The thought experiment really opened a pandora's box of design problems I'm working through: How does a product like this live across multiple workspaces? When and where is there a human in the loop? Are there tiers that transition from agent-driven to human-driven? And I guess the biggest one — can a predominantly AI-driven system actually deliver measurable results at scale? It's early days but will continue to build this out and validate it. clementine.workcraft.co Would love to hear what you think!