Maggie Appleton

Maggie Appleton is a staff research engineer at GitHub Next, a design engineer, cultural anthropologist, and visual essayist investigating how artificial intelligence changes the way people create software and share knowledge. Her work challenges a central assumption of AI-assisted programming: producing more code matters less than helping teams decide what is worth building.

From visual explanation to AI research

Appleton studied cultural anthropology at Whitman College and began her career in design and illustration. At egghead.io, she expanded from illustrating developer-education courses into art direction and user-experience design, developing visual metaphors for React that made abstract programming concepts easier to grasp.

She subsequently led design at HASH before joining Ought as the founding product designer at Elicit, an AI research assistant for finding and analyzing scientific literature. As Elicit’s first designer, she also contributed to product development and front-end engineering. After leaving Elicit in 2024, she became a researcher in residence at Ink & Switch and worked as lead design engineer at Normally. She joined GitHub Next in October 2025.

• Digital gardens as evolving public knowledge. Appleton advocates personal websites where unfinished ideas develop through revision, links, and public experimentation. Her history of digital gardening, 2020 thread collecting examples, and open-source digital-gardeners collection helped articulate this alternative to chronological blogging and algorithmic feeds.

• Tools for thought as cultural practices. Her anthropological approach to thinking tools places software alongside drawing, writing, and other collective practices that shape interpretation and learning. A tool’s value depends on how it changes human understanding and agency, not simply how efficiently it stores information.

• Home-cooked software and barefoot developers. Appleton argues that language models can help people without conventional programming backgrounds create small applications for families, friends, and communities. Her vision of home-cooked software prioritizes local knowledge, privacy, care, and needs that mass-market products overlook.

• Collaborative AI engineering. Appleton argues that individual-first coding agents accelerate duplicated effort, merge conflicts, overloaded reviews, and unnecessary features when teams lack shared context. Her work on Ace, the Agent Collaboration Environment, explores shared agent conversations, cloud microVMs, isolated Git branches, multiplayer editing, collaborative planning, and team-level summaries. The experimental GitHub Next prototype brings engineers, designers, and product teams into the same working context before implementation outruns agreement.

For Appleton, cheaper code makes judgment more valuable: the opportunity is to spend less time generating software and more time researching real needs, coordinating decisions, and building fewer, better things.