This is my new addition to the BuildBetter newsletter. I guess we all listen to a ton of podcasts, and there are so many of them that it's hard to choose. Evan among those I follow, I can't ever listen to all episodes they put out.
Hence, I've started swapping recommendations with friends, and I think we could all benefit from this — so I'm making it a weekly addition to BB below is my selection of interesting ones from the past week.
I'll be happy if you let me know any episodes that stood out for you (past week) in the comments.
Three episodes stood out this week because they connect startup mechanics to global mechanics.
Cristina Cordova shows how GTM compounds inside teams.
Eric Schmidt explains why AI infrastructure is geopolitical now.
Peter Diamandis maps the business models that will (probably) replace Google-era attention.
Let’s look at these three summaries;
Sustainable growth is built through layered feedback loops, not one-off virality.
Key Insights
Distribution is a product feature — Stripe treated every API as marketing.
Integrations and Partnerships (like Shopify) beat ad spend for scalability.
(just wrote about it last week 😃
Share Dialog
Shared metrics aligned engineering and BD teams.
At Notion, community templates became the new sales team.
At Linear, sales people hiring needed internal discussion first. No sleazy car salesman wanted.
Quote
“Your first GTM play should build leverage, not just numbers.” — Cristina Cordova
(02:56) Joined Stripe primarily for the exceptional people and their ambitious vision (“financial infrastructure for the internet”), then taught herself the API basics and grew more technical on the job.
(07:40) Early GTM at Stripe was self-serve with minimal support/sales; pricing/discounting was complex due to payment costs. She carved out platform partnerships as a growth lever.
(12:15 → 14:39) Shopify nearly churned on her first day; Stripe chose to build new APIs so Shopify could own more of the experience—a risky bet on a small but fast-growing partner that later became a template for many platform deals.
(10:26 → 11:39) Partnerships matured into a repeatable playbook (rev-share + incentives) and eventually moved under Sales (“platform partnerships”), while she shifted to product partnerships.
(16:08 → 19:32) At Notion, the unlock was community-driven growth: free consumer tier → personal use → workplace pull; ambassadors, meetups, swag, early betas; an ecosystem of templates/consultants financially aligned with Notion’s success.
(20:33 → 21:38) Through Stripe/Notion/Linear: deliberate brand & design investment signals long-term orientation; clarity on “what feels like our brand” guides decisions.
(24:49 → 28:08) How she spots breakout companies: world-class founders, evidence of a beloved product (even within a niche wedge), and the potential to expand from startups → mid-market → enterprise.
(34:51 → 37:41) What she hires for in operators: founder-mode leaders who identify opportunities and execute (not wait for directives); strategy must pair with strong execution.
(42:42 → 46:44) How she assesses/builds early GTM: get hands-on with customer calls, ensure experience quality, model staffing vs. growth, nail inbound responsiveness, then layer outbound where efficient.
(47:14 → 50:48)AI in GTM (Linear): used to prioritize opportunities (identify ICP, who to contact, next best action), not to replace the human sales experience—especially with developer buyers who prefer helpful, non-salesy outreach.
(55:31 → 57:30) Tactical brand win: high-quality, targeted swag (“Linear supply kits”) for earliest customers → organic evangelism without becoming a merch store.
(53:19) Go-to resource: Scaling People by Claire Hughes Johnson for org-building mental models; plus maintaining a peer network for real-time operator advice.
Stripe didn’t scale through luck — they scaled through instrumentation and thoughtful investment into large, vision-aligned partnerships. These are risky bets, but also a playbook every startup can copy.
Core Idea
Compute is the new oil, and AI policy is industrial strategy. I guess we all know that here but it gets totally ignored outside of bleeding edge tech circles.
Key Insights
Chip supply is the real bottleneck — TSMC and NVIDIA set tempo.
China’s state-driven data scale vs. America’s open innovation ecosystem.
Regulation is (possibly) becoming a competitive advantage.
Talent and STEM immigration are national defense issues everywhere.
Quote
“You can’t outspend a nation — but you can out-innovate one.” — Eric Schmidt
(00:00) Schmidt opens by saying the AI revolution is underhyped and forecasts that AI “agents” will start coordinating and acting autonomously.
(00:21) He highlights the arrival of nonhuman intelligence with reasoning potentially surpassing humans, and frames a geopolitical imperative: “make sure the West wins.”
(02:13) He defends in-office work (vs remote) especially for younger employees, arguing that informal learning and human debate are hard to replicate remotely.
(03:23) In comparing competition with China, Schmidt notes that China’s tech culture adopts “996” (9 a.m. to 9 p.m., 6 days/week), even though officially illegal, as a way to outwork rivals.
(04:01) He argues that China is not necessarily chasing AGI immediately but is aggressively deploying AI in consumer apps, robotics, and infrastructure.
(05:41) Schmidt emphasizes that China’s open-source models (open weights, open training data) may gain global adoption over more closed Western models.
(12:12) He describes how warfare is evolving: drones become analogous to rifles or artillery; future conflict will pit drone fleets (plus AI planning) against each other.
(18:18) On America’s role, Schmidt appeals to the strengths of democratic, chaotic innovation, deep capital markets, entrepreneurial base, and the importance of defending liberal values in a high-tech era.
(23:01) On AGI, he disputes the “3 year timeline” narrative: he believes we might get domain-savants (superintelligence in narrow fields) in 6–7 years, but true AGI requires more (like evolving one’s own objective function).
(26:06) He distinguishes AI as “middle to middle” (requiring prompts, validation, iteration) vs humans who are “end to end.” He expects synergy, not replacement, in coming years.
The takeaway: infrastructure always wins. If you don’t own part of the stack, someone else owns your margin. Also, listening to him felt like a reminder that technology is never neutral. The values we embed in code become the norms our children inherit.
The US may have a technology advantage now, effective capital markets with effectively unlimited funding, but China has more smart people, has orchestrated massive data collection, and the need to automate everything to survive.
Europe still has a good potential in industrial automation, albeit we'll have to use someone else's models. Most likely open-sourced Chinese ones.
Core Idea
They have good episodes that track the latest news across many tech & health related sectors. This one has focus on new rules for attention and monetization.
Key Insights
OpenAI’s Ad Pivot: ChatGPT becomes a media channel — intent is the new keyword.
Sora 2’s Impact: Text-to-video tools threaten content supply chains.
Grok + US Gov: Public-private AI contracts open new startup markets.
Google’s Fragility: Generative answers unbundle search advertising.
Lesson: Every interface shift reshapes distribution — prepare early.
Quote
“The greatest companies of this decade will monetize accuracy, not eyeballs.” — Peter Diamandis
(00:01) The video opens by announcing Sora 2 and framing a shift: not just content selection by algorithms (like on social media) but content generation becoming algorithmic.
(00:42) OpenAI plans to introduce ads in ChatGPT. The hosts warn that AI could become extremely persuasive—and monetization incentives are strong given the scale of compute costs.
(05:05–06:54) Meta launches Vibes, an AI-video app, built via partnerships with MidJourney and Black Forest Labs, rather than in-house — reflecting how fast the AI video domain is evolving.
(10:16–11:25) The discussion zooms in on video as a new frontier modality: eventually, voice + video + reasoning will merge, letting users prompt rich content via natural language.
(18:31–20:08) Anthropic’s Sonnet 4.5 is spotlighted as a leading coding agent: it nearly builds a cyberpunk shooter from a single prompt and is part of the “codegen maxing” race among models.
(23:53–24:39) They demo Claude’s “Imagine” tool, which generates GUI elements on demand—clicking a button triggers new code generation in real time.
(31:24–32:38) OpenAI’s ad ambitions are revisited: the tension of having AI capable of manipulating consumers, yet needing to monetize enormous infrastructure costs, is central.
(43:40–45:11) They analyze GDP-Val, a benchmark across 44 jobs and 9 industries: models are reportedly completing tasks “100× faster and cheaper” than human experts.
(52:18) Grok (xAI) secures a deal with the U.S. government (42 ¢ per use for 18 months) to serve federal agencies—marking a bold play linking AI and state power.
(1:10:45–1:13:11) The hosts cover the compute arms race: OpenAI’s “Stargate” data center buildout, $500 b investment plans, and rising competition among hyperscalers.
If AI becomes the interface, trust becomes the infrastructure. Whoever builds credible context layers will own discovery.
It also made me pause: when machines become storytellers, our job will be to protect meaning.
Low-friction creative process in the future can be as addictive and mindless as scrolling endless feeds today. I've been spending a lot of time with Grok as you may know 😉 and the addiction to frictionless creating feels like real.
Cordova talks micro distribution.
Schmidt explains macro infrastructure.
Diamandis shows the collision of both.
Let's connect macro views and ride waves or design our own currents.
Until next week, let's use it to build better.
BFG
Publishing every Tue morning UTC and occasionally over the weekends.
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This week's BuildBetter newsletter brings valuable podcast highlights focusing on startup and AI dynamics. Key episodes include Cristina Cordova discussing the importance of sustainable growth through innovative GTM systems, Eric Schmidt analyzing AI's role in global competition, and Peter Diamandis exploring tech developments in monetization and messaging. Each guest features critical insights that connect innovation to overarching trends. Reflect on your own notable episodes as well. Authored by @bfg.