Topic
career paths
Edge Curriculum's reference pages, reports, and field notes filed under career paths.
Coverage in this beat collects the working reference pages, reported essays, and contributor interviews we have published on this topic. Newer pieces appear first; reference pages are dated and updated as the underlying programs change.
Self-Taught AI Founders — How They Actually Built Their Curricula
A working reference on how the cohort of self-taught AI founders actually assembled their learning paths — stacked micro-credentials, open-source contribution, and real shipping. Andrew Rollins, Anton Osika, João Moura, Amjad Masad, and Paul Klein IV as worked examples.
Polymath fundamentals
A 9-month cross-disciplinary sequence for builders pursuing the polymath curriculum we cover in The New Polymath Curriculum — AI literacy, systems thinking, design, and communication.
Founder-track AI literacy
A 4-month sequence for founders and operators who need to be conversant in AI without being the model builder. Heavy on strategic and operational layers; lighter on the engineering-track depth.
Career-transition stack
An 8-month sequence for non-engineering professionals moving into AI-adjacent operator and consulting roles. Heavy on institutional legibility, foundational vendor credentialing, and a portfolio piece.
AI safety primer
A 6-month sequence for candidates interested in AI safety, alignment, or governance work. Covers technical safety, governance-track preparation, and the working organizations doing the relevant research.
AI researcher preparation
A 12-month sequence for candidates building toward a research-oriented role at a frontier lab or applied research team. Heavy on mathematics, foundational ML, and publishable work; light on vendor credentials.
AI engineer in 6 months
A 6-month sequence for engineers transitioning from a non-AI engineering role into applied AI. Heavier on hands-on, lighter on institutional legibility — the working assumption is that the candidate already has engineering credibility.
How to Build an AI Career Without a CS Degree
A practical guide to building an applied AI career without a four-year computer science degree. Stack-pattern, shipping evidence, and the credential choices that actually move the needle.
The New Polymath Curriculum
An essay on the curriculum the emerging cohort of polymath builders is actually assembling — technical credentials plus artistic practice, treated as two surfaces of one learning project.
Self-Taught AI Founders: A Generation Built on Stackable Learning
The cohort of AI founders who built their companies without a CS degree are not, on closer inspection, self-taught. They are stack-taught — and the stack is increasingly legible as its own pedagogical model.