What trends and shifts is developer product management experiencing?

Lots of changes are happening, chiefly motivated by the end of free money (i.e. post-ZIRP era) and the rise of AI. I know everyone has probably heard these two themes a million times before so let me break it down specifically for this area.

The end of free money has been talked about a lot on the vendor side but not so much on the buyer side. Startups are under pressure not just because VCs are a lot tighter with their funding rounds, but also because revenue is drying up for point solutions as buyers are tightening their belts & trying to consolidate spend onto a smaller number of platforms (exhibit 1: Datadog). Whereas in the ZIRP era, developer buyers had a lot more latitude to experiment with individual tools that might deliver small productivity gains (or were even of questionable value!)

This does not mean that all point solution tools will die off -- not in the slightest. What it means is that point solutions who have been in business for >5 years are trying to move up market to the enterprise and/or build a platform (or get themselves acquired by a platform), which leads to a Cambrian explosion of new point solutions. However, these products will be more laser-focused on value as expressed in direct revenue, rather than "blitzscaling" to create massive adoption first and figure out the value/revenue later. How does this impact developer product management? It means the developer PM now needs to be focused not only on whether the feature is cool and shiny, but also become more financially literate: what is the ROI and time to realize that ROI.

Financial literacy is even more critical in the era of AI, which promises to bring about a whole host of fundamental changes in human/computer interaction, yet at a very high cost today. It's critical that PMs keep abreast of macro trends in AI, but not to get distracted with the day-to-day minutiae of how this model outperforms that model (unless you are building a product solely in the AI domain for AI/ML developers, in which case, have at it.) Two things that developer PMs have to keep in mind in the AI era: 1) How do the innovations in AI change how developers specifically will interact with computers in the future & what interfaces/experiences are possible now that weren't possible before and 2) What is the cost of delay in prioritizing good AI ideas? Right now we are often seeing cost of delay as positive because the cost of AI computing infrastructure is coming down so rapidly but there can also be persuasive arguments to be made for accelerating certain features to market in areas where you don't have a good moat (you need to beat competitors to the punch).

In the last few years, I have noticed three main shifts in the field of developer product management:

1. Developer Experience (DevX):
   Developer experience is becoming a top priority. With dev tools being adopted in companies from the bottom up, developers are gaining more responsibility and autonomy, including the choice of their development tools. Although the individual developer is often the user rather than the buyer, their opinion is crucial. If developers do not like a tool, they will easily replace it, and it may not be renewed. Therefore, it is essential to provide an excellent developer experience and ensure that your tool integrates seamlessly into their daily practices rather than being yet another source of context switching.

2. Shift from Product-Led Growth (PLG) to Product-Led Sales (PLS):
   While IT spending is on the rise, economic turbulence has made it more challenging to justify expenses. Enterprises are less likely to simply insert a credit card to fulfill the wants and needs of their engineering teams. They need a person to talk to from the vendor who can reassure them about security and privacy concerns and facilitate a procurement agreement. While PLS begins with the product "selling itself," to close the deal, a salesperson is often needed. As a result, there is a growing shift towards PLS.

3. AI and Large Language Models (LLMs):
   To put it simply—be there or be square. AI and generative AI have been significant boosters in productivity and expanding product capabilities, not to mention the hottest buzz and trend. Companies that don't adopt this technology will be left behind, unable to leverage the benefits and keep up with the pace. There are many considerations to address before implementing AI in products, such as cost, security, privacy, ethics, and more. However, I encourage every product manager to learn how to utilize AI and boost their skills.