The Machine Speaks
Published articles tagged AI Economics, listed newest first. Usually filed under AI Strategy.
The count includes the article cards across the pages below.
Who is expendable now that we have AI agents is the wrong question wearing an urgent voice. Agents make tasks expendable, not people, and a role is a bundle of tasks around a core of ownership. The real instrument is a seat audit: what does each seat own that a gate cannot verify, versus merely relay?
The operating record shows what the team did. The business still needs a credible comparison.
Energy, water and money for one query, read off the primary sources with their dates. The boundary you draw changes the answer by more than a hundred times.
Generation made features cheap to produce, so a line that names a feature names something a competitor copies this weekend. The lines that hold name a commitment you will defend.
We renamed Orbyt Jobs to Orbyt Labs on August 20, 2026. Two of our products help you get a job. The third is an experiment in not needing one. A company named after one product could not hold that contradiction, and a lab can.
In 2023, wrapper was an insult: a thin app over someone else's model, doomed when the model ate it. In 2026 the application layer captured the value while frontier models commoditized into swappable engines. I replaced the model under Orbyt twice, once by government order, and nothing broke.
Your moat is now an anchor when the scale, codebase, and process that protected you become the reason you cannot rebuild AI-native. The challenger starts on the foundation you cannot afford to switch to. Incumbents do not lose to AI startups on talent.
Build vs buy is not dead. The calculus inverted. You used to buy because building was slow and expensive. AI collapsed both. The old buy-for-speed default is gone. The new rule is to build what compounds your edge and rent only true commodity.
AI agents are becoming buyers. Gartner expects 25% of enterprise software purchases to involve agent mediation by the end of 2026, and zero-click commerce is moving discovery, comparison, and checkout inside the AI conversation. GEO got you quoted.
Per-seat pricing is not dead, but in AI-native categories it is on borrowed time. It still works for tool SaaS where a human logs in to do the work. When the software does the work, the seat stops measuring value, and usage and outcome pricing take over.
Kimi K3 landed July 16: a 2.8 trillion parameter open-weight model at frontier level for 70% less than Fable 5. It does not beat Fable overall. It changes the market anyway, because an open frontier cannot be export-controlled away. I watched Fable vanish for 19 days.
I run Orbyt with a fleet of Claude Code agents instead of a team. Managing agents means you specify instead of motivate, write specs and tests instead of holding 1:1s, and verify everything. Clarity, delegation, taste, and review transfer. Motivation, politics, morale, and mentorship do not.
The industries everyone calls too slow for AI, tax, fintech, healthcare, proptech, insurance, are built to win it. Governance, auditability, and data discipline are exactly what production AI demands. Move fast and break things loses where the stakes are real. Governed AI compounds.
Tiny AI-native teams now out-ship incumbents. One operator with agentic tooling builds what used to take fifty people. Orbyt is the proof: production SaaS, solo, 32 days, about $400. Incumbents cannot match the speed, because their bottleneck is headcount and process, not talent.
Ten days, one codebase, both models. Opus 4.8 shipped nine days of features. Fable 5 wrote 34% less per response, thought more often, and still cost 69% more.
AI drove the cost of competent to near zero, so average is now free, and free supply is worthless supply. The market is splitting into two states: best-in-class and free. The middle is being deleted. Best-in-class is the only defensible position left, and it is the only product worth shipping.
Free tools, four-tier pricing, the Unlimited plan debate, and why the funnel starts with generosity. The growth strategy of a solo founder with zero users and zero budget.
Every stat from building a 243,000-line SaaS in 32 days, broken down honestly. Lines of code, test coverage, commit history, token usage, cost, and the real AI multiplier.