HeyJaredNotes from an Impatient Innovator
Real-world insights on AI, data, and decision-making for business leaders who want results, not noise.
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- Sep 22, 2026
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PayPal taught me the hard part isn't the AI model (opens the original)
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The most valuable asset a company can build is a single source of truth (SSOT), and that’s a hill I would gladly choose to die on. After more than two decades of building models, advising leadership teams, and now building a product, I’ve watched more companies stall for lack of one than for lack of talent, tools, or budget combined. It rarely makes it onto a CEO’s priority list because it sounds like plumbing; however, it quietly decides how fast the company can make decisions, how much the boa
Ep. 09: The 10x Number Anthropic Showed Us (And Why They Told Us Not to Switch) (opens the original)
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In this episode of Not Another AI Podcast, Shanti Greene, Sandeep Dhamale, and I talk about a trend I’ve been thinking about a lot lately: how AI is changing the way we build, use, and think about software.We talk about collapsing application stacks, smaller teams, micro-apps, and what happens when AI can connect directly to the systems and data we already use. We also get into the economics of AI, and a surprising conversation Shanti had with An
Someone Has Been Paying for Your Tokens. They Would Like to Stop Some Day Soon (opens the original)
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In April, GitHub—the Microsoft-owned platform where most of the world’s software developers host and manage their code—published a post that most people read as a billing notice, and I read as a confession. From June 1, GitHub Copilot, their AI coding assistant, stopped counting “premium requests” and started metering actual token consumption. Tucked into the explanation was a line that deserves to be noticed: GitHub had been absorbing much of the escalating inference cost (the cost of actually
7 steps to putting AI into finance, and why none of the first three involve a vendor (opens the original)
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Somewhere between 30-40 million in revenue, the CEO becomes the least certain person in the room about the company’s own numbers. I have watched this happen inside enough companies now that I treat it as a stage of growth rather than a failure of any particular finance team. For most executives we talk to at AskEnola, revenue lives in the CRM, cash sits in bank accounts consolidated into NetSuite or QBO, the books live in accounting, and the version that reaches
The CFO-100: What Your Data Needs Before AI Touches It (opens the original)
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Most of my conversations about AI in finance eventually turn into a conversation about data, but they rarely get treated with that weight from the start. This explainer is my attempt to rectify that.The data problem is the AI problem, not a step before it, and solving it in the wrong order means no model, however capable, will save the outcome. In fact, getting the sequence wrong is why so many AI-for-finance rollouts stall before they ever produce a number anyone trusts.The data reconciliation
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