The Formation Method: Building AI-Driven Personalization into Your Core Product

The Formation Method: Building AI-Driven Personalization into Your Core Product

The standard approach to personalization in education is to offer different tracks or let students choose their pace. In a recent episode of Category Visionaries, Formation founder Sophie Novati revealed a more fundamental innovation: using AI to dynamically generate each student’s entire learning experience.

The insight came from Sophie’s experience at Facebook and Nextdoor, where she learned “how to solve problems at scale using engineering and product.” She noticed a striking disconnect: programs teaching software engineering were “entirely devoid of technology.” This observation led to Formation’s core innovation in personalization.

Instead of pre-set curricula, Formation built a system where “every lesson, every class, every assignment that every student does is dynamically computed by our technology based on each person’s performance in the program.” This isn’t just about adjusting difficulty levels – it’s about creating entirely personalized learning paths.

The system works at three levels:

1. Dynamic Content Generation Formation’s platform analyzes student performance to determine what content each student needs. Unlike traditional adaptive learning that simply adjusts difficulty, their system creates custom learning sequences based on individual progress and struggles.
2. Automated Mentorship Matching Rather than random mentor assignments, Formation built an algorithmic system that “will dynamically schedule you for sessions based on your availability and your expertise.” This ensures students get help from mentors specifically qualified in their current challenge areas.
3. Responsive Support Scaling The platform adapts not just to individual student needs but to market conditions. “We’re in a market right now where people just need to be a lot more prepared for the interview process,” Sophie notes. The system automatically intensifies support when students face tougher job markets.

This technology-first approach has produced remarkable results. In 2022, Formation’s students saw an average compensation increase of $100,000. More importantly, it’s allowed them to offer unlimited support until students secure jobs – something that would be impossible with a traditional model.

The personalization extends to program duration. Rather than fixed terms, Formation’s AI system adapts to each student’s pace and goals. As Sophie explains, “It’s more of an average between people who take two months all the way up to people who take twelve to twelve plus months as well.” This flexibility is particularly valuable because “there are certain people who will only accept very narrow set of jobs versus people who just want to change.”

The effectiveness of this approach has attracted enterprise partners. “Most recently, we just launched a partnership with Netflix as part of their diversity hiring initiatives,” Sophie shares. Large companies see Formation’s AI-driven personalization as a way to develop diverse talent pipelines more effectively.

For founders building products that require personalization at scale, Formation’s approach offers valuable lessons:

1. Start with the constraint you want to eliminate (in Formation’s case, fixed learning schedules)
2. Use technology to make personalization systematic rather than manual
3. Build systems that become more effective as they gather more data
4. Let market conditions and user goals influence the personalization parameters

Looking ahead, Formation sees their AI-driven personalization as key to achieving their vision “to have an entirely open platform, free to use to start to absolutely anyone who needs training.” By making personalization core to their product rather than an add-on feature, they’ve created a system that becomes more effective as it scales.

The results validate this approach: Formation now serves 400 active learners with plans to reach all 12 million software engineers globally. Their journey shows how building AI-driven personalization into your core product can transform traditional industry constraints into competitive advantages.