Pricing AI Agents, Headcount, and the Economic Reality¶

Today I spoke to an executive about SaaS products, and they told me something that shifted my perspective entirely: AI agents need to be compared to budgets that companies draw from headcount, not tooling.

This is one of those insights that seems obvious in retrospect, but completely changes how you think about positioning AI tools in today's market—especially in this era of widespread tech layoffs and economic uncertainty.

The Conversation That Changed My Thinking¶

We were discussing their company's approach to selling an AI content generation product. Originally, they had built it as a tool for users to interact with directly—like most SaaS products. But they discovered something fascinating: most of their customers didn't care how the tool worked.

What these customers actually wanted was something like:

"It's Monday. I need four blog posts that I could publish this week... And I don't really care how you do it."

The exec explained how they pivoted their approach. Instead of selling access to a tool, they positioned their offering as an agent service. A team member would use their product to generate content, do a bit of quality control, and deliver polished results to the customer.

Budget Allocation¶

Here's where the perspective shift happens. The executive explained that typically, businesses allocate budget in two major categories: tools and people. And in the current economic climate, the people budget has become increasingly scrutinized.

Layoffs¶

The timing of this insight couldn't be more relevant. Tech layoffs have been dominating headlines. Companies that were hiring aggressively just a year ago are now cutting staff by the thousands. Hiring freezes have become the norm rather than the exception.

In this environment, proposing a new SaaS tool is an uphill battle. But positioning an AI solution as a headcount alternative? That suddenly aligns with what many businesses are desperately trying to do: maintain output while reducing personnel costs.

I've seen this firsthand with multiple organizations. Teams that lost members to layoffs aren't getting approvals for replacements, but they might get budget for solutions that help them "do more with less."

Comparing Costs¶

When I thought about my own spending habits, this made perfect sense:

• I'm running multiple AI coding assistants simultaneously, paying around $800 monthly, and it doesn't feel expensive
• Yet a tool like Loom at $200 monthly for just four people feels costly

Why? Because I'm mentally comparing the AI tools to what it would cost to hire additional help, while I'm comparing Loom to other SaaS products.

Implications for Builders¶

If you're building AI tools right now, this framing matters enormously:

1. Position against headcount, not tools: Frame your solution as replacing or augmenting roles, not as another tool in the stack
2. Focus on outcomes, not process: Customers care about what gets delivered, not how your system works
3. Consider the human-in-the-loop approach: A hybrid model with AI doing most of the work but humans providing quality control seems to be a pragmatic transitional approach
4. Acknowledge the economic reality: Position your solution within the context of hiring freezes and budget constraints

The Last Stand Mentality¶

What struck me in our conversation was a subtle undercurrent of what I'd call "last stand" thinking. Many founders are feeling the pressure—if their current approach doesn't work, they might have to shut down. The economic pressures aren't just affecting big tech; they're creating existential questions for startups too.

In this environment, pivoting to meet the market where it is becomes not just smart strategy but a survival necessity. For many companies, the last pivot is to position themselves as headcount alternatives rather than new tools.

What This Means Going Forward¶

I think we're entering a phase where the most successful AI tools won't be the ones with the most impressive technology, but those that position themselves correctly within organizational budgets.

Does a VP care if your system is fully autonomous or semi-autonomous with human oversight? Probably not. They care if it can deliver consistent results at a fraction of the headcount cost.

As one example made clear during our conversation—a simple, secure API gateway positioned for the CSO can immediately land a $30,000 contract, while a complex developer tool might struggle to find budget.

The world is changing faster than most of us realize. The question isn't just "What can AI do?" but "From which budget can companies pay for it?" And in today's economic climate, the headcount budget is where the opportunity lies.

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