Position your agent product as a job your customer's team no longer has to perform. This shifts the value from a tool's features to the direct replacement of labor costs and inefficiencies, tapping into a much larger market than traditional SaaS.
Instead of inventing new problems, find tasks for which businesses already have a budget for paying employees or agencies. This validates the market need and provides a clear ROI comparison against existing labor costs, making the sale easier.
Start with a 'Minimal Useful Agent' that performs a simple, bounded task like drafting replies for human approval or triaging inbound requests. This 'draft and approve' model reduces risk, builds customer trust, and allows you to earn autonomy over time.
An agent performs the work, but the sellable product is the SaaS wrapper around it. This 'control room' provides logs, approval workflows, and analytics that build the customer trust necessary for adoption, separating a real business from a cool automation.
Don't just use evaluation sets for internal quality assurance. Share the results—including failures and fixes—with prospects. This transparency about performance on their own data builds immense trust and acts as a powerful, low-key sales asset.
The quickest path to market is a pilot where you sell the desired outcome, not the software. Initially, perform the work manually with AI assistance behind the scenes. This validates customer value and pinpoints the most repeatable patterns to productize.