AI Update, October 2026: Notable Shifts for People Who Build Products
Trends we have been seeing: CLI agents are maturing, subscriptions come in more tiers, local models are worth a look, and verification tooling is moving to the center.
4 min read
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Practical AI for small teams
We run AI coding agents every day to build and operate real products. Here we write down what works, what breaks and what it costs, and we build the tools we wish we had, starting with Tower.
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Welcome to JPECOM: notes from building with AI every day
What this blog is for, what we write about, and how we try to keep every post practical and honest.
1 min read
Using AI for Customer Support in Your Online Store: Practical Lessons
Reply templates, when to hand off to a human, why AI must never invent product specs, and how to check every message before it reaches a customer.
5 min read
AI for Small Businesses: Where to Start Without Burning Money
A three-step roadmap for small businesses: audit your workflows, pilot a single process, measure before and after, and only then scale up.
5 min read
Local-first AI tooling: what stays on your machine and what doesn't
A plain description of data custody when you use AI agents: what lives locally, what providers see, why bring-your-own CLI helps, and the honest limits.
5 min read
Prompt → contract → verification: how we make agent work checkable
Write the done-criterion first, decide what a machine can check versus what needs a human, and keep evidence receipts so agent work can be trusted.
4 min read
Multi-agent orchestration: the mistakes that cost us weeks
Agents that say done without evidence, retry loops, file ownership clashes, and our rules: two failures means stop, measure output not activity.
5 min read
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- Tests. Each task ends with a check you can rerun.
- History. See what changed and when, next to the work.
- Review. Read the diff before it lands in main.
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