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Guides for deciding where AI is worth it

Plain, practical writing on cost, decisions, and building well, plus how AI applies across the industries we have worked in. No hype, and honest about where AI is not the answer.

AI by industry

AI for vehicle certification
Answering routine queries and escalating the restRead → AI for mortgage qualification
Screening and scoring leads without approving loansRead → AI prospecting for retail
Finding and scoring compatible stores at scaleRead → AI for digital preservation
Where AI helps, and where it must not goRead → AI for financial literacy
In-app education people actually finishRead →

Cost & ROI

How much does a custom AI tool cost?
What drives the price, and why the model is rarely itRead → What is the ROI of AI workflow automation?
A simple calculation you can do before you commitRead → Proof of concept vs production: what actually costs money
The demo was the cheap partRead →

Decision frameworks

How to tell if an AI project is worth building
The AI Project Scorecard, a five-question scorecardRead → Build vs buy vs wait: the AI decision
When each is right, for mid-sized companiesRead → Why most AI projects fail (and the ones that don't)
Six predictable causes, all decided before the buildRead →

Comparisons

Lovable vs traditional development
From a studio that ships on bothRead → No-code vs custom code for internal tools
The default, the exceptions, and the middle pathRead → In-house AI vs an AI studio
Which makes sense when, kept fairRead → Real AI systems vs ChatGPT wrappers
Five questions to tell them apartRead →