The Great Product Reset of 2025

Navigating product building career uncertainty on the eve of an Artificial Intelligence Supercycle

@ezinne wrote about how the PM landscape is changing in 2024 and beyond and how to adapt to it. It's important stuff, go read it. Here we want to double click on her first point - a major factor driving impatience for strategic value in a way that is affecting PM careers.

We saw strain and pain from Product Managers in ‘23 - 24

The product management landscape feels like it’s undergoing a seismic shift. As people who have been deeply involved with product management in the tech industry for 25+ years, we've observed a troubling trend: experienced product managers are increasingly finding themselves out of work, with many of our colleagues facing extended periods of unemployment. And we don’t think this is just another cycle in tech's usual rhythms – we're witnessing a fundamental transformation driven by the advent of transformer-based ‘artificial intelligence’*. We believe there will be a rebound, but there is something afoot that will affect the nature and quality of that rebound.

As we were writing this article, new headlines that make its main point kept spilling out: Facebook decided to let go of 5% of its people and rehire about the same, around AI expertise and AI projects. Microsoft is essentially doing the same thing, without announcing layoffs - it did plenty in 2024. ChatGPT is on the path to replace Siri. Of course, Apple is hedging its bet by having them power ‘Apple Intelligence’. Everyone is affected but our main concern is the plight of founders and product managers - they are bearing the brunt of this turmoil

The Tech Market Turmoil is Fundamentally a Reshuffle

The current state of tech employment tells only part of the story. What's particularly striking is how AI has introduced unprecedented product investment uncertainty into the market. Consider this: entire spectrums of tech investment have been invalidated almost overnight. Take Siri or Alexa circa 2023 – products that represented billions in investment and millions of lines of code – now rendered nearly obsolete after experiencing a simple voice conversation with ChatGPT, especially after the rollout of Advanced Voice Mode.

This pace of obsolescence in certain tech sectors is staggering. Today, a skilled developer can approximately replicate in a weekend, what once required years of development from large teams using machine learning technology underlying features like Siri circa 2023. This acceleration isn't limited to speech recognition or summarization – it extends to any technology that relies on general knowledge and search-spanning capabilities. It will grow to encompass many aspects of mainstream computing. For example, if you think autonomous car tech stacks are not being rewritten to use GPT-driven vision, you have another think coming.

The Crystal Ball Problem

The heart of the issue lies in how best to navigate through this unprecedented uncertainty. There are many strategic questions about AI's impact and how it will shape products and services of the future AND generate profits. Given the paucity of clear answers, CEOs are finding it increasingly difficult to task product management and other builders effectively, to drive growth. Product leadership struggles to provide the certainty needed to justify continued investment in growth strategies that previously worked and don’t anymore. This is the result when there is no clarity on the new tech stack, new talent and new solutions needed to drive growth, coupled with uncertainty in the capital environment - especially for unlisted venture-funded companies.

The result? Companies are pulling back on product investment and talent, probably precisely when they need it most.

The Strategic Paradox

This defensive posture creates a dangerous paradox. Product management is fundamentally about winning the future. Most product work starts to drive return on investment in 3 - 12+ months. In our experience, only startups have a prayer of hitting that lower time-to-return range. Most large companies are fully at that higher range of an 12+ month return window. Just think of how Google is struggling to properly counter the threats to key parts of its search business - information finding and contextualization - from upstarts like OpenAI and Anthropic, given it has many smart people and crystal ball peerers. But good products at scale take time, even after 50+ years of tech industry emergence. This problem is even worse for hardware companies. Exhibit A is the Intel vs. Nvidia tussle in the AI accelerator market, given how long the lead times are when manufacturing is involved.

By cutting back on the product management, companies are effectively reducing their customer-focused R&D capability and making themselves even more vulnerable to disruption. It's a classic case of short-term thinking potentially creating long-term vulnerabilities. It's at this juncture that we like to remind readers that products win customers, not just code, new capabilities and technology. OpenAI R&D publicly released GPT 3.0 a full year before they built the ChatGPT product around the exact same transformer model, and THEN took over the world.

The Ripple Effect on Product Management

These uncertainty problems has created two distinct realities in the tech sector. On one hand, industry giants like Microsoft, Google, Meta, and NVIDIA are pivoting, reallocating resources from other business line teams to more AI-driven innovations and product lines. Sometimes that transition cuts out many product managers and engineers who have slaved on those older product lines for months and years. The prevailing narrative is: a) A lot of these professionals don’t have all the skills needed to move to the new products. b) Only the best of the best are re-purposed because it's hard to re-train everyone. While there is some merit to this framing, we find this an imprecise assessment. Great product managers and builders understand customers and while technology can change, those insights can always be put to good use to re-imagine new solutions. One of our maxims is that technology changes, but customer needs and workflows remain remarkably consistent.

On the other hand, the vast SaaS market – medium-sized companies (well, medium-sized in comparison, some of them are worth billions) that built their success on cloud, mobile, and web technologies – faces an existential threat about whether their businesses will adapt fast enough to match the new reality.

For these smaller players, particularly those in the $50M to $500M annual revenue range, the uncertainty has triggered a retreat into cost-management mode. Investors are now demanding profitability over growth to drive long expected exit multiples. And even growth is hard to come by when both enterprises and conumers are on the cusp of going on an ‘AI-in-everything’ buying binge . If companies don’t unlock their specific AI product genie, they may not grow as fast as they expected just 2 years ago. And even if they do, investors will be looking over their shoulders for imminent disruption and destruction of enterprise value.

When companies enter survival mode, they generally try to maintain the business they have today first, before investing in the future. This often means keeping or slimming down their product development workforce to sustain current operations, paired with a cutback in other product development disciplines and the people that support them - product management, product design, customer research, etc – the very function(s) responsible for future growth.

The Path Forward

Despite all these challenges, we are optimistic about the path forward and want to remind CEOs, founders, product managers and product builders that commercial success stems from effectively solving customer problems and delivering those solutions via a great product and customer experience. New paradigm-shifting tools have emerged but those fundamentals remain.

We’re at the beginning of this new supercycle, so everyone is playing catchup - from developers to investors to markets - there are very few AI experts in the world and the state of the art is constantly changing.

We’ve discussed some things PMs can do in the previous piece to adapt to new realities (in article referenced at the top). Here are some of additional things product managers and builders can do to adapt and thrive in uncertainty:

1. Understand what is changing: Hopefully this article is a start to understanding the currents underneath the surface of the change you can see and sense. Its not as simple as “AI is taking our jobs” - it’s much deeper and fundamental. The economy is beginning to shift, like it usually does when new important technology is emerging and is not fully established. Technology companies are the purveyors of the future and will feel some of this shift first. Those old enough to have seen the emergence of the internet circa 1990 - 2000 will recognize the fear AND excitement.

   Hopefully, this understanding starts to dispels the fear and turns your attention towards resilient adaptation.

2. Manage through uncertainty: Product managers must become experts at operating in ambiguous environments.

   This means: a) Thinking short and long term, and prioritizing revenue generation in the near term. b) Building in flexibility and optionality into your plans and roadmaps. c) Embracing cheaper, faster experimentation as you lead your team.

   As market condition shift, so should our approach, so we can avoid a wasteful false precision.

3. Position as the solution to uncertainty : In uncertain times, your ability to articulate a grasp of what and how change is happening, and helping other manage through it, is indelibly powerful.

   We recommend a) Avoiding entrenchment by questioning your team’s assumptions about the final form of new solutions b) Developing frameworks for evaluating AI opportunities against business goals c) Becoming a visionary champion of game-changing plans for paths forward d) Learning to tell compelling stories about different possible futures. e) Building trust by being transparent about uncertainties and assumptions f) Framing AI investments in terms of optionality and learning.

The key is to embrace uncertainty as a core part of the modern PM role rather than treating it as a temporary challenge. The most successful PMs will be those who can help their organizations navigate through ambiguous waters while maintaining a clear view of customer value and business outcomes. In one of the next pieces we will dive more into some hard truths about managing uncertainty properly.

Looking Ahead

The product management function isn't disappearing – it's evolving. At its core, product management remains the essential bridge between company ambitions, revenue generation, customer satisfaction, and product building. And it’s evolving to ensure that ALL of the customer experience, is altogether connected and delightful. What's changing is the toolkit and the context in which we operate, especially in the short run, on the eve of a new tech supercycle.

The future belongs to product managers who can harness AI's capabilities while maintaining their fundamental role as communicators, integrators, and customer-focused visionaries. Those who can adapt to this new paradigm will find themselves not just surviving but thriving in the AI-driven future of product development. While the tech landscape is fluid and shifting at the moment, it’s time to redefine and tell new stories about what we can do to drive higher returns on capital.

Pre-order our book! Building Rocketships: Product Management for High-Growth Companies. A Blueprint for Product-Led Companies. It’s the book for founders, product managers, and product-led executive teams that will increase the success of any company.