By Priya Shankar, Head of Product at Glue
I spent three years as a product manager before I stopped apologizing for not being able to read code. The phrase "non-technical product manager" gets thrown around like a diagnosis, something to overcome or compensate for. But after managing roadmaps across a 40-person engineering org, I have come to believe the framing is wrong. The question is not whether non-technical PMs can succeed. It is why the industry keeps treating technical depth as the default qualification for a role that is fundamentally about something else.
This is not a feel-good piece about how everyone is special. It is a practical argument, backed by data and experience, for why non-technical PMs bring capabilities that their more technical counterparts often lack, and where they genuinely need support.
The 'Technical PM' Myth
There is a persistent belief in the software industry that the best product managers are former engineers. Companies write job descriptions requiring "3+ years of software development experience." Interview loops include system design rounds. The unspoken assumption is that if you cannot think like an engineer, you cannot lead engineers.
This belief is understandable but wrong.
The origin story goes something like this: early product management in tech companies was done by engineers who were good at talking to customers. As the discipline matured, the engineer-turned-PM became the template. And the template stuck, even as the role evolved into something that requires an entirely different skill set.
According to Product Management Festival research, 60.3% of executives are only partially aware of the value product managers provide. That statistic suggests the problem is not PM technical skills. It is that the PM role itself is poorly understood, even at the leadership level.
When companies require technical backgrounds for PM roles, they are optimizing for one slice of the job, understanding implementation constraints, at the expense of everything else. Customer empathy, market positioning, stakeholder alignment, prioritization frameworks, go-to-market strategy. None of these require the ability to read a pull request.
The real question is not whether you can read the code. It is whether you can bridge the trust gap between product and engineering, and that gap has more to do with communication and mutual respect than shared technical vocabulary.
What Non-Technical PMs Do Better
This is the part that might be controversial, but I have seen it play out across multiple teams and companies. Non-technical PMs often outperform their technical counterparts in several critical areas.
Customer proximity. PMs who cannot retreat into code reviews or architecture discussions spend more time with customers. They sit in user research sessions. They read support tickets. They talk to sales. When you do not have the escape hatch of technical work, you default to the most important PM activity: understanding the people you are building for.
Translation ability. The best PMs are translators. They take engineering complexity and explain it to leadership in business terms. They take customer pain and translate it into requirements engineers can act on. Non-technical PMs develop this skill out of necessity. They cannot rely on jargon as a shorthand. They have to actually understand what engineers mean, not just the words they use.
Prioritization discipline. Technical PMs sometimes fall into the trap of prioritizing work that is technically interesting over work that is commercially important. They get pulled into architecture discussions that do not need PM involvement. They champion refactoring projects because they understand the code, not because the business case is strong. Non-technical PMs are immune to this bias. They prioritize based on customer impact, business value, and strategic alignment because those are the only dimensions they can evaluate.
Asking better questions. When I sit in a technical discussion, I ask questions that engineers consider obvious. "Why does this take three sprints?" "What happens if we do not fix this?" "Who else is affected by this change?" These questions often surface assumptions that technical participants take for granted. The beginner's mind is an asset, not a liability.
A UXcam 2024 study found that 52% of PM time is spent firefighting rather than strategic work. Non-technical PMs who focus on customer understanding and prioritization, rather than trying to keep up with implementation details, are better positioned to reduce that firefighting percentage.
Where You Actually Need Help
Being non-technical is not all upside. There are genuine gaps, and pretending they do not exist helps nobody.
Estimation conversations. When an engineer says "this is a two-sprint project," you need the ability to ask informed follow-up questions. Not to challenge the estimate, but to understand what drives it. Without codebase context, you are taking estimates on faith. And estimates taken on faith are wrong by an average of 1.8x, according to industry research.
Dependency awareness. The most common source of planning failures is hidden dependencies: Feature A requires changes to Module B, which is shared with Team C's project. Non-technical PMs cannot see these dependencies. They rely entirely on engineers to surface them, and engineers do not always know either.
Technical debt trade-offs. When engineering wants to spend a sprint on refactoring, you need to evaluate whether it is worth the investment. Without understanding what the debt actually is and how it affects velocity, you are either rubber-stamping or blindly pushing back. Neither is good.
Spec writing that earns engineering trust. If your specs are disconnected from codebase reality, they create rework. Engineers spend time building what the spec describes, then discovering it conflicts with how the system actually works. Each spec error costs roughly $75,000 per year in wasted effort, according to Capers Jones research.
These gaps are real, and the traditional advice of "just learn to code" addresses approximately none of them. You do not need to write Python to evaluate a technical debt trade-off. You need visibility into the codebase in a format you can understand. If you are wondering whether learning to code is the right investment, our analysis of whether PMs should learn to code offers a more nuanced take.
Tools That Bridge the Gap
The good news is that the gap between "non-technical" and "effective with technical context" is getting smaller, thanks to a new category of tools designed for exactly this problem.
General AI assistants. Tools like ChatGPT and Claude can explain technical concepts, help you draft specs, and translate engineering jargon. They are useful but limited. They do not know your codebase. They cannot tell you which modules are interconnected or where technical debt lives in your specific system.
Documentation platforms. Notion, Confluence, and similar tools help teams document their systems. The problem is that documentation goes stale. The codebase changes daily. Documentation gets updated quarterly, if at all. You end up making decisions based on how the system used to work, not how it works today.
Engineering metrics tools. LinearB, Jellyfish, and similar platforms provide data on engineering productivity. They tell you how fast the team is shipping, but not what they are shipping or what the system looks like underneath.
Codebase intelligence platforms. This is the emerging category that directly addresses the non-technical PM's core challenge. Glue reads your actual codebase and translates it into strategic intelligence that product teams can use without writing a single line of code. You can ask "how does the billing system work?" and get an answer grounded in your real code, not outdated documentation.
For product managers specifically, the value is in the questions you can suddenly answer without filing a Slack message to engineering. Which features already exist? What dependencies does this project involve? Which parts of the system are owned by a single engineer? How complex is this change, really?
This is not about replacing engineering judgment. It is about giving product managers enough context to have better conversations with their engineering teams. When you walk into sprint planning with an understanding of the system, you ask different questions. You push back on estimates with informed curiosity rather than blind skepticism. You write specs that reflect reality.
The non-technical product manager label is not going away. But the limitations that used to define it are shrinking. The PMs who will do the best work in the next few years are not the ones who learn to code. They are the ones who learn to use the new generation of tools that make codebase knowledge accessible to everyone on the product team.
Stop apologizing for not being technical. Start demanding better visibility.
FAQ
Can you be a successful product manager without a technical background?
Yes. Product management requires customer empathy, prioritization judgment, stakeholder management, and strategic thinking, none of which require a software engineering background. The most successful non-technical PMs invest in understanding technical concepts at a conversational level and use tools that provide codebase visibility without requiring them to read code. The key skill is asking informed questions, not knowing the answers yourself.
What skills do non-technical product managers need?
Non-technical product managers need strong customer research skills, frameworks for prioritization (RICE, ICE, or similar), the ability to translate between business and engineering language, and stakeholder communication skills. They also need tools that bridge the codebase visibility gap, allowing them to understand system architecture, dependencies, and complexity without reading code directly. Curiosity and the willingness to ask "obvious" questions are underrated strengths.
How do non-technical PMs work effectively with engineering teams?
Effective collaboration starts with mutual respect and clear communication. Non-technical PMs should invest time understanding how engineering works at a process level, attend architecture reviews as listeners, and ask clarifying questions without pretending to know more than they do. Using tools that provide shared codebase visibility reduces the information asymmetry that creates friction. When both product and engineering are looking at the same system understanding, conversations become more productive.