In the current economic climate, the most dangerous line item on a B2B technology company's P&L isn't the server costs—it's underutilized headcount.

For the modern SaaS / PaaS CFO, the marketing budget is often a black box of "brand awareness" that is difficult to attribute to revenue. But the specific role of Product Marketing (PMM) presents a unique financial conundrum. It is a critical function for bridging the gap between product and sales, yet the traditional hiring model is increasingly inefficient given the advances in Gen AI.

If marketing content is the product that enables revenue, then prompt engineering becomes a core product capability.

Bad prompts create generic content.
Generic content kills differentiation.
And undifferentiated messaging stalls deals.

If your launch materials sound like every other SaaS announcement on LinkedIn, the issue isn’t the model. It’s how you’re instructing it.

If the Generalist is dead, who replaces them?

The answer isn't a single person. It is a modular stack of specialists augmented by AI.

For the last decade, the "Generalist Product Marketer" was the unicorn hire every CMO hunted.

But in the era of Generative AI and hyper-specialized SaaS, "safe" has become dangerous.

Early in my career IBM set out to revolutionize the development of large systems with an ecosystem it called AD Cycle, where AD was an abbreviation for Application Development. AD Cycle was undoubtedly the ultimate expression of the traditional waterfall method of building software systems, where development projects moved en masse through distinct stages.