Whitepapers and podcasts on AI Workforce Infrastructure, written by practitioners shipping in production.
Why organizations should manage AI like talent, not tools. Covers the AI Productivity Paradox, the $2.4 trillion management gap, and a practitioner's framework for evidence-based AI management.
The $300 billion IT services sector faces structural disruption. Revenue cliffs, margin compression, and the shift from time-and-material billing to AI-managed delivery.
AI-managed execution infrastructure for venture-backed startups. How accelerators can compress seed-to-Series-A timelines and improve founder velocity through systematic capability building.
What MIT, Stanford, UW, CMU, Berkeley, and peers must build next. A blueprint for standing up an AI Management institute inside existing research universities: curriculum, faculty model, industry partnerships, and the certificate-to-degree ladder.
Why unmanaged AI creates chaos, what the Productivity Paradox means for your team, and how evidence-based management turns AI agents into reliable team members.
Governing the AI-assisted engineering workflow with structured processes, evidence-based validation, and continuous learning. How FRAIM turns AI chaos into production-ready output.
Walkthroughs and demos showing how to manage AI agents in production with FRAIM.
Watch a first-time run of FRAIM end-to-end — from setup to managed AI execution — and see what AI management looks like in practice.
How FRAIM holds AI agents accountable to evidence, validation, and outcomes — turning unmanaged AI output into production-ready work.
A founder's-eye view of building two AI products in six months — what worked, what broke, and how AI management changed the trajectory.
More resources are on the way. Follow along on LinkedIn to catch new whitepapers and podcasts as they drop.
Follow on LinkedIn →Every whitepaper and podcast on this page was researched, drafted, reviewed, and published using FRAIM-managed AI agents. Try the same system that built them.