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Most writing about AI is either marketing or math. If you're a beginner or a non-technical person, both leave you in the same place: unsure what any of it means for you.
Tangible Ideas Lab exists to close that gap. Founded by Daniel Montgomery — a designer and no-code builder, not a machine-learning PhD — we're an independent AI lab that spends its days testing models and tools against real work, and its evenings writing up what we found in language anyone can use.
If you can read a nutrition label, you can read our lab reports.
If a finding needs a computer-science degree to understand, we haven’t finished writing it. Every report, guide, and grade is written for the person who is new to this.
No affiliate links. We pay for every token we test with, we publish the exact prompts we ran, and we show the failures next to the wins. You get evidence, not a sales pitch.
Synthetic benchmarks tell you how a model performs on benchmarks. We run models against real invoices, real code, and real support tickets — the work you actually have.
Experiments that failed, models that looped, prompts that flopped — it all gets published. Watching something break is how most of us actually learn.
We put AI tools and models on the bench and run them against real work — two attempts per test, graded blind against a baseline.
We turn the results into grades, plain-English verdicts, and guides that a non-technical reader can act on the same day.
We ship our own AI-powered tools — many no-code friendly — and document every decision and dead end in public.
We run workshops and consulting for teams and beginners who want to get comfortable with AI. No prerequisites, no gatekeeping.
No affiliate links. No sponsored verdicts. We paid for every token — so our grades only have one customer: you.