Know whether your AI is actually good — and prove it.
A flawless demo isn’t a working system — the model nails your eight prompts, then invents a policy in front of a customer. The PROVE Method is a five-stage loop for measuring AI quality you can actually trust — Pick, Reference, Observe, Verdict, Evolve. Stop shipping on vibes.
The loop you run to measure and improve any AI system.
P
Pick
Define what “good” means — the metrics and criteria that matter.
R
Reference
Build honest eval sets — inputs paired with expected or graded outputs.
O
Observe
Run the system across the set and capture outputs at scale.
V
Verdict
Score them — programmatic checks, LLM-as-judge, or human review.
E
Evolve
Fix the weak spot, re-run, and wire evals into CI — a loop, not a gate.
What’s inside — 10 modules
1
The PROVE Method
Why "it looks good" isn't good enough, why AI is hard to test, and the five-stage loop that fixes it.
2
Pick
Define what "good" means: task-appropriate metrics, quality dimensions, and what NOT to measure.
3
Reference
Build honest eval sets: real examples, golden outputs, edge cases, and coverage.
4
Observe
Run evals at scale, deterministic replay, offline vs. online, and instrumenting your system.
5
Verdict
Score outputs: programmatic checks, LLM-as-judge and its pitfalls, human review, and rubrics.
6
Evolve
Close the loop: read results, regression-test, iterate deliberately, and wire evals into CI.
7
When Evals Mislead
Bad sets, gamed metrics, judge bias, overfitting, and false confidence — and how to catch it.
8
Reusable Eval Systems
Eval harnesses, datasets as versioned assets, dashboards, and making evals a team habit.
9
Evaluating Specific Systems
Practical evals for RAG, agents, classifiers, generation, and safety — matching method to system.
10
Evals in Production
Online eval, monitoring and drift, A/B testing, guardrails, and closing the feedback loop.
Plus: 10 narrated videos (~3 hrs), slide decks & PDFs, a study guide, and 7+ templates (PROVE quick reference, metric-selection guide, eval-set builder, LLM-as-judge rubric, regression checklist, eval-harness starter, production-eval checklist) — yours to download and keep.
60-day money-back guarantee
If it doesn’t help you measure and trust your AI, email us within 60 days for a full refund. No questions.
Questions
Why so cheap?
It’s a deliberately low price so any developer or team can grab it. Lifetime access, no subscription.
Is it really lifetime?
Yes — buy once, access forever, including updates.
What do I get?
10 video modules (~3 hrs), slide decks & PDFs, a study guide, and 7+ templates (PROVE quick reference, metric-selection guide, eval-set builder, LLM-as-judge rubric, regression checklist, eval-harness starter, production-eval checklist) — plus a downloadable bundle.
How technical is it?
Built for developers, AI engineers, and technical PMs. You should be comfortable calling an API and reading pseudocode. No machine-learning or statistics background needed — there’s no math or training loops.
Which tools or frameworks do I need?
None in particular. PROVE is stack-agnostic — it applies to any model, eval tool, and framework you use.