How Every turned AI product experience into a 7-figure consulting powerhouse

Every’s evolution into a 7-figure AI consulting business illustrates the convergence of hands-on AI product development with strategic advisory services. Their unexpected success emerged from being practitioners who built real AI products before teaching others, highlighting a crucial advantage in the rapidly evolving artificial intelligence consulting landscape where experience trumps theoretical knowledge. Their approach demonstrates how consulting firms can deliver more effective AI implementation by focusing on cultural transformation rather than technical deployment alone.

1. Become a practitioner before consulting

• Building actual AI products like Cora, Sparkle, and Spiral gave Every firsthand experience with real-world implementation challenges.
• This hands-on approach helped them identify practical issues that pure management consultants might miss, including how tools break, how users interact with them, and what drives adoption.
• Experimentation with formats like “TL;DR” podcasts and interactive forms provided insights that theoretical frameworks couldn’t capture.

2. Address cultural barriers to AI adoption

• Every discovered that technical capability is rarely the primary obstacle to successful AI implementation.
• The most significant barriers are cultural: teams need psychological safety, organizational support, and explicit permission to experiment with new AI tools.
• Successful AI consulting requires acknowledging and addressing these human factors rather than focusing exclusively on technology deployment.

3. Specialize deliberately in specific use cases

• The most effective AI consulting engagements shared two critical elements: clearly defined use cases and structured frameworks for assistance.
• By narrowing their focus, Every avoided the trap of promising overly broad “AI transformation” and delivered tangible results instead.
• This specialization approach counters the industry tendency toward generic AI consulting solutions.

4. Build client capability rather than dependency

• Every prioritized teaching clients to build with AI rather than simply building for them.
• This philosophy recognizes that understanding—not access to technology—is the true bottleneck in AI adoption.
• The approach creates more sustainable client relationships and better long-term outcomes than dependency-based consulting models.

The big picture: The current AI consulting landscape resembles early web development—characterized by significant opportunity, limited clarity, and rapid innovation without established roadmaps.

Why this matters: Despite the novelty of AI consulting, Every’s experience confirms that timeless consulting principles still apply: solve real problems, share knowledge transparently, maintain focus, and empower clients to eventually succeed independently.