Why AI-built apps break in front of customers
The failure list is short and predictable: auth that expires mid-session, double taps, a dropped signal in the middle of a booking, payments that were never tested end to end. I build this way daily, so I can say what agents are good at and exactly where they leave a hole.
What an app actually costs in 2026
I publish the ladder instead of hiding it: small jobs from $49, landing pages from $299, automations from $499, websites and dashboards from $799, apps from $2,999, monthly care at $149. What moves the price is the number of decisions, not the number of screens.
One engineer doing what used to take a team
A booking app was failing at sign-up and payment, and the repair was quoted at over 100 hours. I rebuilt it instead and it went live on iOS and Android in 7 days. Agentic development is why one person can hold that pace without shipping garbage.
Cutting content cost with an AI pipeline that learns
A software company had given up on AI writing because every draft needed a rewrite. The pipeline I built compares each draft with the editor's final version and feeds the differences into the next brief. Cost per article went from about $900 to about $100, with a person still approving every piece.
Agents that act on real systems, not chat windows
MCP servers, browser automation and the guardrails that decide what an agent may do alone. Chrome Bridge is the public example: it lets an agent drive a real browser profile, logins and all, which is the part most agent demos quietly skip.
Pricing and stock decisions made from data
An engine that reads sales, costs, stock history and public competitor prices, then recommends a price and reorder level for every item in a catalogue, running as a daily job rather than a conversation.