Your Window Into the Innovation Economy

The largest opportunity AI unlocks isn’t better software. It’s the multi-trillion-dollar services economy. For every $1 enterprises spend on software, they spend roughly $6 on people and services to get the job done.¹ AI-native services can compete for that spend with a fundamentally different model: each outcome can generate revenue while requiring progressively less human labor, improving future performance, and unlocking more work to own.

For decades, the field of biological aging has increasingly refined taxonomies of what changes as organisms grow older. The most widely accepted framework — the hallmarks of aging — reasonably describes twelve interconnected processes: genomic instability, telomere attrition, epigenetic alterations, mitochondrial dysfunction, loss of proteostasis, impaired macroautophagy, deregulated nutrient sensing, stem cell exhaustion, cellular senescence, altered intercellular communication, microbiome disturbance, and chronic inflammation.

The Good Part, First AI agents have gotten surprisingly useful, surprisingly fast. A task that used to eat up half a day such as working through a long report, cleaning up a spreadsheet, catching up on an inbox, can now take 20 minutes.

In our first two posts, we mapped the architecture of an AI agent and the tools it reaches for once it decides to act. Both posts shared an assumption we never fully unpacked: that a model is sitting somewhere, ready to think, the instant it’s called. That assumption is a business in itself, and it’s worth being precise about a few terms before we go further.