Founders can get lost building complex AI systems and automations. This can become a trap, a "procrastination machine," that feels productive but doesn't contribute to the primary goal of generating revenue. Always ask if the AI work is actually making the business money.

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Before launch, product leaders must ask if their AI offering is a true product or just a feature. Slapping an AI label on a tool that automates a minor part of a larger workflow is a gimmick. It will fail unless it solves a core, high-friction problem for the customer in its entirety.

Most companies are not Vanguard tech firms. Rather than pursuing speculative, high-failure-rate AI projects, small and medium-sized businesses will see a faster and more reliable ROI by using existing AI tools to automate tedious, routine internal processes.

For a founder coding their own product, every minute spent trying a new, unproven tool is a direct opportunity cost against shipping features. This contrasts with developers in larger companies who may have downtime to experiment as a hobby or part of their job.

Early-stage startups should resist applying AI everywhere. Instead, they should focus on one high-impact area where processes already work. AI is most effective as an amplifier for a solid foundation, not as a shortcut or a fix for fundamental strategic problems. Start small with integrated tools.

Without a strong foundation in customer problem definition, AI tools simply accelerate bad practices. Teams that habitually jump to solutions without a clear "why" will find themselves building rudderless products at an even faster pace. AI makes foundational product discipline more critical, not less.

Implementing AI tools in a company that lacks a clear product strategy and deep customer knowledge doesn't speed up successful development; it only accelerates aimless activity. True acceleration comes from applying AI to a well-defined direction informed by user understanding.

After building numerous AI tools, Craig Hewitt realized many popular applications (e.g., AI avatars, voice cloning) are worthless novelties. He pivoted from creating flashy tech demos to focusing only on building commercially viable products that solve tangible business problems for customers.

Don't get distracted by flashy AI demonstrations. The highest immediate ROI from AI comes from automating mundane, repetitive, and essential business functions. Focus on tasks like custom report generation and handling common customer service inquiries, as these deliver consistent, measurable value.

The transition from AI as a productivity tool (co-pilot) to an autonomous agent integrated into team workflows represents a quantum leap in value creation. This shift from efficiency enhancement to completing material tasks independently is where massive revenue opportunities lie.

Teams that become over-reliant on generative AI as a silver bullet are destined to fail. True success comes from teams that remain "maniacally focused" on user and business value, using AI with intent to serve that purpose, not as the purpose itself.