Send us a text We weigh the real trade‑offs of building AI in‑house versus buying and configuring proven tools, and map a practical route from pilot to production without blowing the budget. Clear steps on data, governance, ethics, and IP help you create value you can measure. Build vs buy decisions tied to strategy and IP When generic problems justify off‑the‑shelf tools Niche bottlenecks and owning differentiated capability Real costs of talent, data architecture and compute&...
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Send us a text We weigh the real trade‑offs of building AI in‑house versus buying and configuring proven tools, and map a practical route from pilot to production without blowing the budget. Clear steps on data, governance, ethics, and IP help you create value you can measure. Build vs buy decisions tied to strategy and IP When generic problems justify off‑the‑shelf tools Niche bottlenecks and owning differentiated capability Real costs of talent, data architecture and compute&...
Send us a text We dig into practical AI that saves time: personal LLMs, embedded features already in your tools, and AI‑native agents that take action, not just give answers. We share proof points, pitfalls, and simple ways teams can adopt safely and quickly. Personal LLMs as thinking partners and draft acceleratorsEmbedded AI in email, slides, CRM, and meetingsAI‑native tools mapped to roles like SDR and legalAgents that act: scrape, configure, reset, and scheduleQuality, speed, and evidence...
ReThink Productivity Podcast
Send us a text We weigh the real trade‑offs of building AI in‑house versus buying and configuring proven tools, and map a practical route from pilot to production without blowing the budget. Clear steps on data, governance, ethics, and IP help you create value you can measure. Build vs buy decisions tied to strategy and IP When generic problems justify off‑the‑shelf tools Niche bottlenecks and owning differentiated capability Real costs of talent, data architecture and compute&...
