Tag: 70/30 Method
11 posts
The 70/30 Method Fixes Your Team’s Fear of AI
Senior engineers stall on AI because they are being asked to vouch for code they did not write. The 70/30 split gives them a boundary they can trust, and the resistance disappears.
The Rescue Bill: What It Costs to Fix a Vibe-Coded Product
Most startups that shipped AI-built production apps have already needed a rebuild or rescue engineering. The speed was real. So is the invoice. What the cleanup actually costs and how to avoid needing it.
The 70/30 Engineering Audit: What to Automate and What Must Stay Human
A practical five-question audit for deciding which parts of an engineering or business workflow to automate, assist, approval-gate, or keep human-owned.
Your Engineers Aren't Resisting AI. They're Afraid of It.
Your team isn't resisting AI out of laziness. They're afraid of being blamed for code they didn't write. The 70/30 method draws the line that makes adoption feel safe.
How to Calculate the ROI of an AI Agent (Without Lying to Yourself)
The ROI math everyone does for AI is wrong in a specific, optimistic way. Here's the honest version, including the costs and the one assumption that quietly inflates every estimate.
Your AI Doesn't Have a Model Problem. It Has a Data Problem.
You upgraded the model and the output is still wrong. That's the tell. Almost every 'the AI isn't good enough' problem is a data problem wearing a model costume.
What a Manager's Job Becomes When Agents Do the Work
If agents do the producing, what's left for the manager? The job doesn't shrink. It moves up: setting the standard, designing the system, and owning the judgment.
If You Can Build It in a Weekend, So Can Your Competitor
Wrapping a model isn't a moat. Where AI actually creates defensibility for a startup — and where it just commoditizes you alongside everyone else.
The Problems AI Can't Fix (No Matter How Good the Model Gets)
A contrarian take: the categories of business problem where reaching for AI is the wrong move, why founders keep doing it anyway, and what to do instead.
Your First AI Agent Is a New Hire. Onboard It Like One.
Your AI agent isn't failing because the model is weak. You skipped its onboarding. Give it a job description, access, context, and a feedback loop like any new hire.
The 70/30 Method: Building With AI Agents Without Betting the Company on Them
Why I let AI agents handle about 70% of the work and keep 30% for senior judgment — and how that ratio keeps AI projects out of the ditch.