It doesn't matter one bit what other SaaS founders are saying. What matters is what your customers are saying. Are they happy with the feature set? Then you are fine. Don't over-engineer a product just to keep up with founders who have nothing to do with your product or market.
Of course, if your customers start asking for such features, go ahead and respond to that demand.
In 2024, "AI" was the value prop. Now, for many enterprise buyers, it's becoming a liability (compliance risk, hallucinations, unpredictable costs).
If you are solving a high-friction, "boring" problem—like plumbing compliance, legacy database migration, or payroll—nobody cares if there is an LLM involved. In fact, marketing "Deterministic Output" (i.e., it does exactly what you tell it to do, every time) is starting to feel like a premium feature again compared to the probabilistic nature of GenAI agents.
It doesn't matter one bit what other SaaS founders are saying. What matters is what your customers are saying. Are they happy with the feature set? Then you are fine. Don't over-engineer a product just to keep up with founders who have nothing to do with your product or market.
Of course, if your customers start asking for such features, go ahead and respond to that demand.
But my question is more so about new customer acquisition. Existing customers are happy, but what about for growth and traction?
The pendulum is definitely swinging back.
In 2024, "AI" was the value prop. Now, for many enterprise buyers, it's becoming a liability (compliance risk, hallucinations, unpredictable costs).
If you are solving a high-friction, "boring" problem—like plumbing compliance, legacy database migration, or payroll—nobody cares if there is an LLM involved. In fact, marketing "Deterministic Output" (i.e., it does exactly what you tell it to do, every time) is starting to feel like a premium feature again compared to the probabilistic nature of GenAI agents.
Build for the pain, not the buzzword.
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