Quanta Bits

The End of the Yes Reflex. For years, IT's real job was to say yes to whatever the business asked for, and that worked because a bad tool only hurt the team that bought it. AI changes that. An agent or a connector reaches across every system, so the damage from a bad yes now touches the whole company. This week: why AI demand needs one review process instead of a reflex, the three things that...

This week on Quanta Bits, I talk through why Notion winding down its Mail inbox is a useful signal for enterprise software. Systems of record are not disappearing, but agents may change where work starts. If an agent can read, route, and eventually write back across CRM, email, ticketing, documents, and finance systems, a new application request needs a different review lane. We need the old CIO q...

This week on Quanta Bits, I talk through why AI makes an old operations mistake easier to repeat: automating a messy process before asking whether it is consistent, simple, and owned. The episode uses deal review as the example, then connects it to OpenAI and Bain's "micro-productivity trap," Google's legal warning on AI summaries, Anthropic's capability-jump planning, Pew...

This week on Quanta Bits, I talk through why the first real demand of AI agents may be an ownership map. Anyone can build an AI prototype now, but once that prototype needs access to CRM, ticketing, email, finance systems, or customer data, it becomes an enterprise decision. The episode covers why tool ownership is often unclear, why agents make that harder to ignore, and the four questions teams...

This week on Quanta Bits, I look at why AI's public relations problem is becoming an operating problem. Student backlash, data center opposition, AI-labeled layoffs, hiring algorithms, and forced workplace adoption are all pointing to the same issue: trust is becoming part of the deployment work. If employees, customers, candidates, and communities do not believe AI is being used fairly, bett...

This week on Quanta Bits, Reza looks at a practical workflow shift: using agents to separate the source layer from the presentation layer. Markdown can hold the facts, owners, risks, dates, and decisions. HTML, dashboards, diagrams, and other visual surfaces can help people understand the work quickly enough to review and discuss it. The episode connects that idea to recurring operating artifacts...

This week on Quanta Bits, Reza looks at why the build-it-yourself AI moment is still exciting, but the cost assumptions underneath it are getting less stable. Anthropic's pricing and access changes are the hook, but the bigger issue is industry-wide: capacity constraints, massive data center buildout, model routing, and the gap between a cheap-feeling prototype and a recurring workflow that r...

AI adoption is moving from experimentation to operations. This week, I look at why the "AI bill" needs an owner, not just because of tokens and software spend, but because AI work touches workflows, data quality, reviews, exceptions, trust, and accountability. The cloud era gave us CloudOps and FinOps once spend and ownership became too messy to ignore. AI may be heading in the same dire...

This week’s episode looks at why the AI replacement math is getting more complicated. AI tools are starting to feel less like chatbots and more like junior analysts, but the economics are not as simple as “AI is cheaper than people.” Compute capacity, token costs, model availability, and human review time all matter. I also cover OpenAI and Anthropic’s massive compute commitments, GitHub’s move to...

Everyone says "AI adoption" but nobody means the same thing. This week: why the definitions problem is killing more AI projects than the technology, what BCG's survey of thousands of CEOs reveals about the "pragmatist" majority, and why MIT says 95% of AI projects never make it past pilot. Plus: the fastest-growing open-source project on GitHub is an AI agent that got bann...

Anthropic published actual data on who AI is displacing, and it's not who most people expect. The most exposed group? People with graduate degrees earning 47% more than average. Computer, math, business, legal, and management roles are all above 90% exposed. But only 33% of that work is actually being done by AI today. That 61-point gap doesn't close on its own. It closes when leadership...