Skip to Main Content

ML6

Built at Global Codex Hackathon: [London] · Apr 15, 2026 · London, UK

Demo video · Engineering growth in enterprises is still fragmented, reactive, and difficult to personalize at scale. Useful signals are spread across PRs, retrospectives, mentorship conversations, project reviews, documentation, and capability frameworks, but they are rarely connected into one adaptive system. As a result, engineers do not always know which skills to build next, managers repeat the same coaching manually, and onboarding new joiners takes longer than it should because critical guidance, context, and resources are scattered across people and tools. SkillPilot solves this by transforming real work signals into personalized learning paths that help engineers improve where it matters most for their role and level, while also accelerating onboarding by giving new joiners a clearer, context-aware path to ramp up faster. At the same time, it makes the rollout of tools like Codex more effective by embedding them into day-to-day growth, feedback, and delivery workflows instead of treating them as standalone tools that employees have to figure out on their own. Why we built this We built SkillPilot because the need for scalable, contextual learning is becoming urgent in fast-growing engineering organizations. Adding 10% more people to the team in a single week really put our onboarding and mentoring capacity to the test. The workload is tangible: senior engineers and managers spend significant time repeating guidance, pointing people to the right resources, and translating feedback into development actions. That onboarding challenge revealed a broader opportunity. The same fragmentation does not only affect new joiners, but engineers at every seniority level who are trying to grow in technical, delivery, collaboration, or leadership skills. SkillPilot was built to turn that manual, inconsistent process into an AI-native learning workflow that scales mentorship, shortens onboarding time for new joiners, and supports continuous development across the organization./…

SkillPilot is an AI-powered engineering learning platform that adapts to each engineer’s skill level, role, and growth goals. It helps in onboarding and upskilling engineers across the spectrum identify development gaps and next steps in areas such as technical depth, production readiness, code quality, evaluation rigor, collaboration, communication, mentoring, and leadership. To do that, SkillPilot can learn from various enterprise signals like pull requests, mentor-mentee input, project feedback, retrospective notes, internal knowledge bases, as well as personal info and predefined growth paths. By turning those fragmented inputs into personalized growth journeys, SkillPilot helps organizations move faster toward an AI-native way of working: engineers do not just get generic learning content, but contextual guidance based on how work actually happens inside the company. This also accelerates enterprise rollout of tools like Codex, because it helps teams learn where AI can create leverage, teaches people how to use those tools in role-relevant ways, and reinforces company-specific best practices, guardrails, and feedback loops. In that sense, SkillPilot is not just a learning product; it is an enablement layer for enterprise AI adoption. It uses Trust-by-Design principles so recommendations are explainable, humans stay in control, and feedback continuously improves both learning outcomes and responsible AI usage.

Team