1️⃣ AI needs decision plumbing Deloitte’s latest tech leadership study says 81% of executives think they can govern AI at scale, but nearly 75% expect their operating model to change within 12 to 18 months.
💡 Why it matters Scaling AI is moving from tool rollout to decision rights, funding, risk ownership and who coordinates human-agent work.
☕ Coffee talk Who actually owns the decision rights when the AI pilot leaves IT and starts touching margins?
2️⃣ Professionalism is a design choice MIT Sloan Management Review argues that leaders should define what professionalism means in their own context, instead of inheriting old norms around meetings, appearance and conduct.
💡 Why it matters Culture gets expensive when standards stay implicit. Teams need clear norms, and leaders need to separate useful discipline from inherited bias.
☕ Coffee talk Which rule is really protecting the work, and which one is just protecting someone’s comfort?
3️⃣ Supabase scaled by staying operationally weird First Round’s interview with Supabase CEO Paul Copplestone points to a remote async team, near-zero attrition, one tagline that clarified PMF and product-led sales paid only on incremental uplift.
💡 Why it matters The useful lesson is constraint. Scale gets cleaner when teams know which habits are non-negotiable and which GTM motion actually adds value.
☕ Coffee talk If sales only gets paid for incremental lift, how much of the old GTM theatre survives?