Local-First AI

The engineering math behind preventing an agentic loop from burning through your monthly runway in one night.

What agentic workflows are actually doing to entry-level engineering, and what to do about it.

How to lead a codebase by stating intent instead of writing syntax, and the discipline that keeps it from falling apart.

Why AI-native teams are deploying micro-SaaS apps from a single codebase, and how to architect a SaaS factory that compounds.

Pieter Levels at $420K a month. Marc Lou at $1M a year across twelve micro-SaaS. Tony Dinh at $1M working twenty hours a week. The narrow real pattern, with sources, costs, and where it breaks.

A framework for finding which 20% of your tasks are agent-ready before you write a line of code.

Using Apify, Firecrawl, and a local model to monitor every move your competitors make in real time. With the architecture and the weekly digest format that actually gets read.

A research-first outbound agent that scrapes news, LinkedIn, and financials before drafting an email. With the architecture, the prompts, and the guardrails.

Triage that does not just summarize. It prepares the drafts and fetches the data, and you approve. The 60-line config that actually works.