For twelve years, Product School has been the engine behind the world's most successful product careers. We have trained 2 million professionals, issued more certifications than any program in history, and served the product teams at Fortune 500 companies, including JP Morgan, Visa, GSK, Nike, and Walmart. I have watched our alumni ascend to CPO roles at some of the best companies in the world.
We have seen every trend – from the rise of mobile to the transition to product-led growth.
But yesterday, we made something official.
We've launched Product Partners – the AI consulting firm of Product School.
Why This Moment is Different
In February 2026, the "SaaSpocalypse" arrived: public SaaS companies lost over $1 trillion in market cap in a single week. Meanwhile, the valuations of AI natives reached heights unthinkable just two years ago – with xAI hitting $250 billion and OpenAI reaching a massive valuation of $852 billion.
The market is no longer speculating. It is pricing in a fundamental question: which existing enterprise product organizations will survive the transition to AI-native operations?
The reality is that AI capability has exploded, but deployment has lagged. Over 6.5 billion people have never used AI even once. The gap between what is possible and what is actually deployed inside the enterprise is enormous – and it is not closing by itself.
The Valley Most Organizations Don't See Coming
At ProductCon London this past February, I shared a framework that explains exactly where most enterprises are stuck: the AI Productivity J-Curve. It begins with a quick pilot bump as individuals experiment with tools. Then comes the valley – a zone where high investment meets flat returns because teams are forcing AI into workflows that were never designed for it.
Most organizations are stuck at Level 1: AI as individual productivity. Velocity is higher. Core product metrics stay flat. Individual AI wins are swallowed by a legacy system that cannot follow. I call it the false summit. It looks like progress. It is not compounding.
The organizations breaking through have moved through Level 2 (AI as Team Automation) and Level 3 (AI as Agentic Workflows) to reach Level 4: AI as Operating Model – where closed feedback loops let agents monitor outcomes, refine their logic, and compound improvements over time. They got there not by running more pilots, but by rebuilding the operating model underneath the investment.
Product Partners was built to lead you through that transition.
The Gap Consultants Aren't Closing
The capability gap closed faster than anyone expected. Today, the models are powerful and accessible. The real question is: how do you change the way your product organization actually works so that AI is embedded in the process – not bolted on as a feature?
Traditional firms are not built to answer this. Strategy firms provide decks and board alignment. They are advisors, not practitioners – they do not sit with your PMs as they rewrite discovery workflows. Boutique AI shops are brilliant at building agentic pipelines, but they optimize for the build, not the organizational change required to sustain it.
Product Partners exists in that gap, and we work differently in three specific ways.
Why Product Partners
Most AI transformation efforts fail not because the technology does not work, but because the knowledge walks out the door when the consultants leave. We designed our model specifically to prevent this. Three things set Product Partners apart from every other firm in this space.
1. We focus exclusively on product teams
Product Partners focuses on product management, engineering, and design. This is not a positioning choice. It is what allows us to go very deep on the specific nuances that drive successful AI transformation for product teams, as opposed to taking a generalist approach across the entire organization.
The CPO and the CHRO face different AI transformation challenges. The operating model changes that unlock compounding returns for a product organization are not the same changes that work for finance or operations. We have spent twelve years inside enterprise product organizations at the practitioner level. We know how product teams think, how they are organized, and most importantly, where they get stuck. That depth is what competitors cannot replicate.
When we run an AI Assessment inside your company, the people doing it have built discovery processes, rebuilt prioritization frameworks, and shipped features at scale inside organizations like yours. The diagnosis is faster because we have already seen the pattern. The roadmap is sharper because we know which interventions compound and which ones plateau.
2. We build, not just advise
Our AI Product Leaders and Forward Deployed Engineers (practitioners who built AI products and operating models at companies like Google, Amazon, and Meta) embed directly inside your environment. They write code, deploy agents, and redesign workflows alongside your team. They do not sit in a conference room and hand over a plan.
We keep engagements lean by design: senior practitioners only, no layers of junior staff. You will always know exactly who is working with you and why they were selected for your engagement. The deliverable is a working AI operating model and a team ready to harness it. Not an implementation plan that sits on a shelf.
Product Partners is tool agnostic. In most cases, we work with the tools your team already uses, so there is no requirement to buy new ones. We build inside your environment, not on top of it. We respect your guardrails, access controls, and compliance requirements from day one, including GDPR, ISO 27001, and SOC 2. Every solution is built in close collaboration with your team, integrated into your existing stack, and rolled out with regular checkpoints.
We are committed to delivering meaningful business value within 60 days. Not a report. Not a roadmap. A working operating model, with evidence of compounding.
3. Training is built into every engagement from day one
AI Training runs in parallel with AI Implementation from day one. Programs are hands-on, customized to your stack and your team's roles, and tailored to the gaps surfaced in the AI Assessment. Three tracks: Core Product Skills covers the craft of building products customers love; AI Product Skills builds the fluency to design, evaluate, and ship AI-native products; Product Leadership develops the strategy and judgment that scales high-performing teams.
Our AI Product Leaders and Forward Deployed Engineers build alongside your team, not instead of them. Every agent, workflow, and way of working we implement is documented, transferred, and owned by your people. By the time the new operating model is live, your team understands everything we built and is ready to run it. The AI operating model belongs to your team, not to us. The capability stays. The dependency does not.
The 60-Day Commitment
We are committed to delivering meaningful business value within 60 days. Not a report. Not a roadmap. A working operating model, with evidence of compounding.
Every engagement begins with an AI Assessment – a focused two to three week engagement where we work in partnership with your product executives to map your current state across five domains: Workflows, Governance, Tech and Data, Operating Model, and People and Skills. The output is a prioritized roadmap, including the first AI deployments your team will put into production, backed by clear ROI projections. Leadership leaves with clarity: what to build, who to upskill, and where to start.
From there, AI Implementation and AI Training run in parallel. Our AI Product Leaders and Forward Deployed Engineers install the operating model: deploying agents, redesigning workflows, and delivering working AI solutions inside your existing environment – respecting your guardrails, compliance requirements, and data governance policies from day one. We build inside yours. We do not bring our own tools and impose them on your organization.
At the same time, AI Training runs – hands-on programs customized to your stack and your team's roles, built around the same operating model we are building together. By day 60, you have real AI in production and a team equipped to keep building on it. Every iteration compounds on the last.
Why Product School?
For those who have been part of our community for years, this connection is intuitive. We spent twelve years building the best product practitioners in the world – serving the product teams at 1,400+ enterprises and earning the trust of a community of over 2 million product professionals. We know how product teams think, how they are organized, and most importantly, where they get stuck.
The Product Partners team is not a group of strategy consultants who pivoted to AI last month. We are product people. We have the language, the credibility, and the trust that comes from working alongside these teams long before "AI Transformation" was a board mandate.
While Product School continues to serve individuals through its AI training programs, Product Partners was built as the natural extension – to serve entire product teams at large enterprises with a holistic approach that combines training and implementation. Product School builds the practitioners. Product Partners transforms the organizations they lead. Same DNA. Different scope.
Carlos Gonzalez de Villaumbrosia,
Founder, Product School & Product Partners
Updated: May 14, 2026
