Enterprise AI is built for engineers or rolled out company-wide with no role specificity. Meanwhile the product managers, designers, analysts, and product operations people who decide what gets built spend most of their day on synthesis, drafting, analysis, and translation — precisely the work generative AI accelerates most, and precisely the roles today's enablement strategies serve least.
See the operating model Book a consultThese aren't adoption problems. They're operating model problems, and they show up months after the rollout is declared a success.
Task-level gains that decay the moment the next model ships.
AI cost grows invisibly — the unit of cost never appears in standard dashboards.
Clever individual prompts stay individual instead of compounding into organizational capability.
Front-end speed quietly given back to rework and verification on the back end.
A small central enablement function owns standards, benchmarks, and guardrails. The product teams own adoption and outcomes. Five pillars hold it up.
Enablement organized around the actual work of product — strategy, research, prototyping, launch, metrics, stakeholder alignment — not around tools.
Quality measured against human performance on the same task, with accuracy standards and visibility into when people defer to or override the model.
FinOps discipline applied to AI: right-sized model routing, optimized inputs and outputs, and team-level accountability for spend.
Rewritten roles, an automated use-case discovery pipeline, AI literacy led by your own champions, and clear human-in-the-loop decision rights.
Defined feedback loops at practitioner, team, and program level that correct both model usage and the program itself.
Leaders who operationalize a model like this reinvest that reclaimed capacity into discovery, customer contact, and strategy — rather than cutting it.
In one engagement with a Fortune-100 product organization, this approach was associated with 13% year-over-year revenue growth.
Whether you're one PM with a mandate and no playbook, or a leader who needs the whole organization to move, there's an entry point sized to it.
Practice it yourself
Coaching scenarios for the exact moments enterprise PMs face under pressure. Not a prompt library — the workflow that precedes the prompt: the framing, the context, the quality check, built around situations you actually face.
Each scenario gives you the job to be done, the context to set before you open your AI tool, step-by-step prompts, a worked example built on a realistic enterprise case study, and a quality checklist so nothing leaves your hands that shouldn't.
The five scenarios individual PMs reach for most: The Evidence-Based Pushback, The Stakeholder Conversation Rehearsal, The Honest Experiment Readout, The Meeting-to-PRD Chain, and Prioritization Under Constraints. Includes the AI Ethics Audit Gate, the Prompt Library, and a Start Here guide.
Get the individual licenseEverything above, plus five more: Causal Metrics Architecture, From Noise to Insight, From Signals to Problem Statement, Pressure Test Your Roadmap, and One Update Four Audiences. Includes the 90-Day Adoption Roadmap and a 60-minute consultation to walk your team through it.
Get the team licenseTrain your team
A three-day, hands-on class that prepares product managers in enterprise environments to put AI to work across the full product lifecycle. Delivered privately, in-house, for your team.
Most PMs are still using generative AI like a faster search engine. This closes that gap. Participants work a single realistic enterprise case study from market research through to a functional prototype and an executive-ready roadmap, while carrying a product of their own in parallel. They leave with working artifacts they built live, not notes they took.
Seven product competencies on a foundation of AI fluency: Strategy & Decision Support, Market Research & Synthesis, Requirements Generation, Data Analysis & Metrics, Prototyping & Concept Validation, Stakeholder Communication, and Workflow Automation & Agents.
Format: three sessions of 4.5 hours, live online or on-site. Best for: product managers at medium-to-large enterprises, product directors, product marketing, and operations or digital transformation managers.
Bring this to your teamInstall the operating model
We partner with product leadership to tailor and install this operating model inside your organization — then transfer it to your internal team and step away.
The engagement is deliberately finite: stand the capability up, ensure it works, hand it over, leave. You end with an internal capability your own people run, not a dependency on an outside firm.
Start the conversationFeedback from product managers who worked through The PM Situation Room during its beta.
"The Evidence-Based Pushback is excellent. I have definitely come across this more than once — the premise is fantastic and the step-by-step prompts can absolutely be beneficial."
Senior Product Manager, national grocery retailer
"I'm pretty impressed after watching the video and poking through all of the guides. Clearly lots of work put in. The paid social example is actually identical to a situation we see right now with our traffic channels."
Product Manager, enterprise communications platform
"Feels like you have a live Jason, who can be coming along PM's work to deliver tremendous value."
Group Product Manager, global retail
If your team has an AI mandate and no operating model behind it, a short conversation will tell you which of the three starting points fits — and whether you need the third one at all.
Schedule a consult