Product Builder : The Manifesto

As a Partner of AI and Product Management at Converteo, David Spire helps organizations transform their product strategy in the age of AI and data. Specializing in AI Product Build and Agentic AI, he develops concrete, performance-oriented solutions to make AI a lever for sustainable growth.

We believe that AI is a product matter

There are moments when a technological disruption is so profound that it doesn’t just change our tools—it forces us to rethink the very way we create value. Generative AI, and even more so Agentic AI, is one of those moments. Because they redefine who builds, how we build, and what “building” even means.

In Product Management, this shockwave is particularly violent. For nearly 20 years, the profession was structured around a clear logic: understand the need, prioritize, specify, and then hand over the construction to those who can code. The PM thought. The engineer did. In between: specs, tickets, handoffs, and a lot of wasted time.

AI is tearing down this wall.

This manifesto carries our convictions about what we believe is a major transformation of the profession. About the emerging role—the Product Builder. And about why Converteo has chosen to make it its central expertise in Product.

Where we come from

The concept of the Product Builder emerged gradually within our company, almost organically, from our history and our projects.

Converteo is a consulting firm born from data. 20 years of data, pipelines, flows, dashboards, modeling, and analytics. 10 years of technological achievements for large corporations. And for the last 3 years, a Product Data & AI practice that has confronted us with a simple fact: our consultants, our POs, our engineers—all of them, upon contact with AI, started to ‘build’. Not because they were asked to. Because the technology finally allowed it. They prototyped solutions for clients, automated their own consulting tasks, and increased their impact on delivery. The Product Builder was born from the field.

And because we come from data, our approach is different. AI without mastered data is an engine without fuel. An LLM, no matter how powerful, only creates business value if it is fed with relevant flows, quality data, and a structured context that only someone who understands data knows how to assemble. Pipelines, governance, quality, analytics—all of this forms the invisible foundation on which artificial intelligence rests. Without this foundation, AI remains an impressive but fragile gadget.

This is a strong conviction, and it runs counter to a prevailing narrative that puts AI on every slide and data on none. Being a Product Builder is a data issue before it is an AI issue. And at Converteo, this data culture is built on 20 years of practice rooted in the information systems, data architectures, and operational reality of our clients. It is what allows our Product Builders not to start with the tool, but with the problem. To know exactly what happens when you connect an AI agent to a business data flow.

Product Builder: What we believe

• The Product Builder is the natural evolution of the Product Manager. A hybrid profile that combines the rigor of Product Management—discovery, prioritization, stakeholder management—with the ability to directly build functional solutions. They master the key technologies of generative AI and low-code: LLM orchestration, agentic workflows, prompt engineering, and AI-assisted prototyping. They know that prototyping quickly is not enough—you must prototype right, and never forget that a prototype only has value if it can scale.
• AI forces the merger of Discovery and Delivery. An AI product is probabilistic by nature. In traditional software, input A gives output B. Deterministic, predictable, testable. With AI, the same prompt can produce different results. A chatbot responds brilliantly 95% of the time and hallucinates the remaining 5%. Variability is part of the technology. And that changes everything. You can no longer specify an AI product in a document, hand it over to a technical team, and wait for the result. In the AI economy, an idea has no value until it has been confronted with the reality of a prompt and a dataset. You have to confront the technology from the very first hours—manipulate the models, challenge the prompts, evaluate the workflows—to de-risk feasibility at the same time as value. This is exactly what a Product Builder does. And it’s what requires getting your hands dirty from the discovery phase.
• The agentic paradox: more AI autonomy = more human collaboration. Agentic AI opens up a vast frontier. Systems capable of executing tasks autonomously, chaining actions, and interacting with external environments. According to McKinsey, 62% of organizations are already experimenting with AI agents. But here is what few people are saying: the more a product tends towards agentic, the more collaboration it requires with IT teams. In the Service-as-a-Software era, the Product Builder moves faster, sooner. They de-risk what needs to be de-risked, then pass the baton at the moment the solution needs to be secured, integrated into existing systems, and made scalable. The success of an AI product lies in this articulation—this co-engineering between the one who creates and iterates, and the one who industrializes and makes reliable.
• The AI transformation happens on the ground. The Product Builder is its pivot. Steering committees identify ambitions. AI roadmaps draw trajectories. But the real transformation—the one that produces measurable value—happens in contact with the business units. In daily processes, in operational irritants that no one has formalized, in manual workflows that everyone has come to accept. This is where the Product Builder becomes a pivotal role. Because they are the only profile to combine two simultaneous readings: that of the business—they understand the processes, constraints, information flows—and that of the technology—they know what an AI agent can automate, where an LLM creates value, and at what point a prototype is enough to prove a use case. They detect automation opportunities that tech teams don’t see, because they are too far from the business. And they materialize them where business teams could not, because they lack the technical skills. It is this position, anchored in reality, armed by tech, that makes the Product Builder the concrete vector of AI transformation in organizations.
• We do not believe in the chimera of AI capable of recoding everything. We are lucid: faced with the complexity of certain projects, rapid prototyping has its limits. The challenge is not to reinvent everything with a snap of the fingers or to believe that decades of IT & digital iterations and construction will be replaced by still-nascent AIs. On the contrary, the full value of the Product Builder approach lies in its ability to act as an incubator, an accelerator that prepares and facilitates the transition to scale in a second phase. Anchored in reality, our Product Builders are aware of the need to build with the existing, composing with the company’s tools and data legacy to multiply its value.

What we build with our clients

If we have chosen to specialize our Product experts in the role of Product Builder, it is because we see every day the gap between the potential of AI and the real ability of organizations to do something concrete with it. The technologies are there. The roadmaps are ambitious. But between the AI strategy and the value delivered, the same link is often missing: someone who goes into the field, identifies the processes to be transformed, and builds a first technological response in a matter of days.

This is the link that our Product Builders embody. On a Data product, they master the flows, the pipelines, the restitution layers, and transform a product intuition into something testable quickly. On an AI product, they manipulate the models to confront use cases with reality before committing to months of development. On Agentic AI, they work closely with business teams to map workflows, detect high-value automation cases, and design and test end-to-end agentic systems—in close collaboration with our clients’ technical departments.

We train them. We deploy them. We make them grow through ambitious projects at companies that want to put AI into production.

Where we are going

The AI transformation of companies will be driven by people who know how to build in uncertainty, who turn hypotheses into prototypes and prototypes into products.

Organizations that can identify, attract, and grow these profiles will have a decisive advantage in the next three years; in speed, in relevance, and in execution.

In this new world, the Product Builder-Engineer duo becomes the atomic unit of production. In these hybrid squads, the distinction between prototype and industrialization fades in favor of simultaneous construction.

As the automation of workflows by Agentic AI becomes the new norm, we believe that the competitiveness of organizations will depend on their mastery of these autonomous processes. The Product Builder architects these new digital assets.

With sectoral specialization becoming a prerequisite, technological excellence now requires an intimate understanding of the field and its constraints (regulatory, for example). It is this business depth of the Product Builder that guarantees the accuracy of the solution and its speed of adoption.

At Converteo, we have made this bet. We are betting on Product Builders forged by data, armed by AI, and obsessed with business value. Because it is this combination that will make the difference.

To those who recognize themselves

If you are already doing all this—if you are this profile that doesn’t just specify but builds, that doesn’t limit itself to discovery but gets its hands dirty with technology, that works in contact with business units while mastering the AI building blocks—then this manifesto speaks of you.

At Converteo, we have made the choice to structure, nurture, and grow this expertise. We are betting on Product Builders forged by data, armed by AI, and obsessed with business value. Because it is this combination that will make the difference.

AI is not just a tech topic. It’s a product topic. And a product is something you build.