For Product-First Organizations, Progress Must Be Defined By Outcomes, Not Output

This expert opinion by Louise K. Allen, Chief Product Officer at Planview, was originally published on Inc.com.

For decades, coder bandwidth has served as a natural speed bump in the journey to product launch. There is only so much a team can get done in a week or month. This is true no matter how skilled its members. While understandable—good work takes time—the resulting bottleneck has been a point of frustration for leaders. 

Organizations have invested billions of dollars in tools that can accelerate development. Many have succeeded in shrinking coding timelines and turning ideas into working tools faster than ever before. However, as is so often the case, improvement in one area revealed that product development challenges cannot be attributed to just one team or process. 

Now that traditional constraints have fallen away, organizations face an uncomfortable truth: Removing obvious sources of friction, just exposes deeper issues.

Shifting The Bottleneck

The influx of AI coding support has been a boon for development productivity. However, it hasn’t removed pressure from product lifecycles altogether. It simply shifted the bottleneck to another link in the chain, and this new challenge will be more difficult to address than the one that came before.

With AI-driven coding tools now accessible and—to varying degrees—capable of handling a great deal of coding’s most time-consuming tasks, the functions to the left of development are struggling to keep pace. Now, marketing teams aren’t waiting for coders to finish and new builds aren’t on hold until bandwidth frees up. More often, engineers and developers are waiting for everyone else to tell them what to build next. 

After all, development isn’t the first step. It’s the culmination of countless hours of ideation, strategic planning, research, and design. If those upstream decisions cannot be accelerated and lines of communication between teams remain limited, faster execution doesn’t matter. There’s nothing to build. When left-of-dev teams accelerate without the appropriate support, the outcome is even worse—the wrong product is made faster.

The reality is that the most significant delays and waste in software delivery rarely originate in development itself. In fact, most engineers spend only 16 percent of their time actually developing code. So, accelerating this element alone can only do so much. The real issues emerge well before the first line of code is written. The myth of sluggish development just provided cover for the inefficiencies happening around it.

Misalignment Is The Real Problem

Now that development constraints are loosening, product leaders need to examine what’s happening outside development with the same level of scrutiny they have for coding and delivery delays. When they do, they most often find that misalignment is the real issue. That’s where great product management must come in.

Within product-first organizations, no amount of automation can replace clarity of intent and strong strategic portfolio management. These are not things that can be rushed. This is especially true when AI systems are deployed ad hoc, as the insights AI’s offer are only as valuable as their reach. This is one part of the AI revolution that leaders have failed to address.

Exceptional Execution, From End-To-End

According to a recent survey of DevSecOps professionals, disconnected systems, processes, and communication are among the biggest time wasters for product development teams. Respondents noted that they spend an average of seven hours each week navigating fragmented tech stacks. 

As AI scales developer output, organizations must reaffirm the basics of clear strategic direction, disciplined portfolio management, and shared accountability. Progress must be defined by outcomes, not output. This means leaders must look beyond development acceleration and focus on how AI can strengthen execution fundamentals.

This includes using AI to support the discovery and synthesis of customer insights, helping teams identify patterns and unmet needs more quickly. It means applying AI to scenario planning and prioritization, enabling leaders to test assumptions and understand trade-offs before committing resources. It also means improving portfolio visibility, so decisions reflect enterprise-level outcomes rather than local optimization.

In these contexts, AI becomes a force multiplier for alignment rather than a shortcut around it. This shift in perception is critical because, as building software becomes easier, deciding what to build becomes more consequential. 

Aligned For Success

With AI coding assistants, automation, and vibe coding dramatically reducing development timelines, a new paradox is emerging. AI-driven development enables organizations to build almost anything—and fast. However, those releases still fail to move the needle toward overarching goals. 

Continuing this path may enable teams to deliver more, faster, but leaders will have nothing else to show for it. After all, speed for its own sake rewards motion, even when it’s in the wrong direction. That’s a risk that organizations cannot afford to take.