Product management has always been a role in flux: part business, part tech, part UX/UI, part strategy, part execution. It requires just enough knowledge to bridge gaps between stakeholders, but not necessarily deep expertise in any single domain.
As AI, no-code/low-code tools, and the pace of product development accelerate, I believe we’re witnessing the emergence of a new breed: the Full-Stack Product Developer.
Shortly, product managers will be expected to build rapid prototypes, validate hypotheses with working MVPs, and make data-driven decisions. All without waiting for engineering resources. And, at the same time, junior PMs and even junior developers might struggle to find a place in this new ecosystem.
Note: Some teams already pretty much have these expectations, especially fast-moving startups I worked with
Let’s unpack what this means.
What is a Full-Stack Product Developer?
Think of a Full-Stack Product Developer as a product manager with technical execution skills, or a (junior) software engineer with strong product thinking. They can:
- Build and validate ideas independently using low-code/no-code tools (Retool, Bubble, Webflow, GPT-based app builders like Bolt or Replit, etc.).
- Understand and write basic code (Python, JavaScript, SQL) to build lightweight features and automations.
- Analyze data and make informed product decisions without needing a dedicated data team.
- Handle early-stage UX/UI using tools like Figma.
This doesn’t mean they replace engineers. Instead, they help reduce dependencies and increase speed in the early stages of product development.
Why This Shift is Happening
1. AI and No-Code/Low-Code Tools Are Lowering the Barrier
Tools like ChatGPT, Copilot, and Bubble enable non-developers to build functional applications with minimal technical knowledge. PMs who embrace these tools will ship faster and iterate without waiting in engineering backlogs.
2. Speed Matters More Than Ever
The faster a product team can move from an idea to a live experiment, the higher the chances of success. Removing dependencies on engineers for every minor iteration means better learning cycles.
3. Startups and Lean Teams Already Work This Way
In early-stage startups, PMs are often expected to hack together prototypes and early features. This skillset is already in demand in small, fast-moving teams—and will likely extend into larger organizations.
4. The Role of Junior PMs and Developers Will Change
Junior PMs mostly handle execution: backlog management, (Jira) tickets, stakeholder coordination. But in an AI-driven world, much of this will be automated. Similarly, junior developers handling repetitive coding tasks might be replaced by AI-generated code. This means:
- Entry-level PMs will need to develop execution skills beyond process management (e.g., technical fluency, data analysis, UX understanding).
- Entry-level devs will need to either specialize (e.g., AI, backend architecture) or shift toward product-building roles.
- The reality is that companies will prefer hiring a single Full-Stack Product Developer over a separate junior PM and junior developer.
What This Means for Product Folks
If you’re in product management, you have two choices:
- Adapt: Start learning basic coding, no-code tools, and data analysis to become a Full-Stack Product Developer.
- Specialize: Move deeper into strategy, leadership, or UX to differentiate yourself.
(I’ve personally started experimenting with learning Python, using low-code solutions and AI-assisted development)
The good news? If you’re willing to learn, this shift creates massive opportunities for those who can bridge the gap between product and technology.
So—where do you want to be in this evolution?
Counterarguments & Challenges
While the Full-Stack Product Developer model has clear advantages, it’s not without its downsides:
- Engineering Complexity: Not all products can be built with no-code tools. Scalability, security, and backend performance often require deep engineering expertise that PMs may not have.
- Cognitive Load: Expecting PMs to balance product strategy, coding, and UX could lead to burnout and lower-quality outputs in each domain.
- Teamwork & Specialization Still Matter: Larger organizations still benefit from having dedicated specialists in PM, UX, and engineering. A generalist approach may not work for every team.
Would love to hear your thoughts. Do you see this shift happening? Are you already seeing demand for these skills? Let’s discuss!
Note: This whole blog post was written and published in 16 minutes with AI assistance. Featured image is AI-generated