Decision frameworks for serious AI builders
Most AI readiness frameworks ask about your roadmap. We ask about your reality. Most prioritization models ignore operations. We weight MLOps at 30%.
We built pmhucks.pro because we were tired of AI assessments that optimize for consultant hours rather than actual deployment success. This is a tool by practitioners, for practitioners.
Evaluate your organization's capability to ship AI products. 15 minutes, 4 dimensions, actionable recommendations.
Prioritize which AI projects to tackle first based on impact, feasibility, and strategic fit.
Model the true cost of your AI product. Includes inference costs, monitoring, retraining, and hidden ops.
Assess your compute, storage, and MLOps infrastructure against production requirements.
The best model is useless without deployment, monitoring, and iteration capabilities. We weight MLOps heavily because that's where most projects fail.
We ask about current state, not roadmaps. Honest assessment of where you are today leads to actionable next steps, not wishful thinking.
"Garbage in, garbage out" is especially true for AI. We assess data governance at 25% of your score because no amount of engineering compensates for bad data.
Your results include comparisons with companies in your industry and size. All data is anonymized and aggregated—we never share individual scores.
pmhucks.pro was built by product managers and engineers who've shipped AI products at scale. We've seen what works, what fails, and where organizations consistently underestimate complexity.
This tool captures lessons from dozens of AI deployments across industries—from startups racing to market-fit to enterprises managing compliance risk.