During an early internal meeting, founder Adam Fodd explicitly told his team, "I don't want the product to be on the generation side of things." He later reversed this stance after customer feedback, embracing the very concept he first rejected, which became the company's core breakthrough.

An app bundling various LLMs into one interface is making $300k/month. Replicate this success by targeting a specific professional niche like lawyers or teachers. Stitch together models and workflows to become the default AI assistant for that vertical.

Most successful SaaS companies weren't built on new core tech, but by packaging existing tech (like databases or CRMs) into solutions for specific industries. AI is no different. The opportunity lies in unbundling a general tool like ChatGPT and rebundling its capabilities into vertical-specific products.

Begin by offering AI consulting or services. This provides immediate cash flow and deep customer insights with a 70-80% margin. Use this experience to document workflows and then productize the solution into a scalable software product with ~95% margins.

While conducting a discovery session for an early Figma plugin, a user asked if their ideas could be turned into a visual wireframe. This single, off-hand question sparked the core value proposition for UX Pilot, which the founder hadn't previously considered.

Before writing code, Fixer ran an executive assistant agency for eight years. This allowed them to collect invaluable data on customer workflows, build a ready-made audience, and create an unfair advantage. This deep domain knowledge and GTM head start were crucial for their rapid success.

Flexport's internal hackathons are now its primary source for AI-driven innovation. With 90% of projects using LLMs, these events generate real product features and influence the company's roadmap. This demonstrates a powerful bottom-up approach where the most valuable ideas come from engineers closest to the problems.

The company originated not as a grand vision, but as a practical tool the founders built for themselves while developing a legal AI assistant. They needed a way to benchmark LLMs for their own use case, and the project grew from there into a full-fledged company.

Instead of just managing clients on HighLevel, Marketex used its white-labeling feature to create 'Marketex Engine.' This pre-built version, loaded with their recommended templates and workflows, transforms their service from billable hours into a scalable, productized offering, enabling faster client onboarding and higher margins.