Taking Women from Crypto Curious to On-Chain w/ Maggie Love

Maggie Love's path into crypto began in 2016 at IBM, where a colleague's repeated mention of blockchain in a meeting sent her to Barnes and Noble the same day to buy The Blockchain Revolution by Don Tapscott. She read it in two days, joined ConsenSys in 2017, and entered an industry where she had to mine Reddit just to prepare a presentation for the CEO of AMD. That friction shaped her view that crypto carries a double language burden, layering financial terminology on top of crypto-specific vocabulary, making it uniquely hard for newcomers to absorb.

She-Fi is a six-week cohort-based crypto education program for women built on three pillars: education, experimentation, and community. Two classes per week are paired with weekly on-chain quests. Participants set up an exchange, configure a Trezor hardware wallet, fund it, trade on the Base app, stake RIF on the Rootstock Bitcoin ecosystem, and download Decentraland, completing six to seven on-chain actions with no prior crypto experience required. Love cites a Harvard study, with the caveat that her figures were approximate, finding that adding a community layer to self-paced courses raised completion rates from roughly 15 percent to roughly 85 percent, which is the structural logic behind the cohort format.

Love distinguishes between presenting information and genuine education, arguing that education requires communicating new words in ways people can actually retain. Her method introduces concepts, reaffirms them, and uses Q and A sessions so students encounter the same ideas multiple times. She uses analogies to make technical ideas accessible, comparing a layer two rollup to a student presenting only a book report summary to a teacher who then accepts it into a catalog.

She-Fi's first cohort in 2020 drew largely female bankers and people from tech and finance backgrounds including Google, DoorDash, JP Morgan, and Goldman Sachs. Current cohorts include artists, creatives, MBA students from Northwestern and Columbia, stay-at-home mothers reentering the workforce, and partners of multi-billion dollar crypto protocol founders. Most members find She-Fi through LinkedIn, making the community predominantly professional. In the United States the demographic skews less technical and more professional, while in India members tend to be more technical and younger. Community members from the 2020 cohort remain active in Telegram chats organized by local geography.

Love argues that crypto marketing on Twitter relies on FOMO and hype that works for male psychology but alienates women, and that women prefer collective educational experiences over guilt-based or fear-driven messaging. She-Fi is explicitly not a women-in-Web3 organization and does not host panels about what it is like being a woman in crypto. Its summits are large one-day events focused on technology, founders, investors, and real-world use cases, attracting 400 to 600 people in person per event. Traditional financial apps use goal-based framing but fail to explain what assets are inside investment products, and She-Fi addresses this by teaching what is under the hood, including concepts like liquidity pools, so members feel confident about their decisions.

Love contends that Web3 is more meritocratic than traditional finance because contributors can work and be paid from anywhere regardless of location, though she acknowledges this may be changing as crypto matures and some organizations push for office-based work. She-Fi has had contributors working from Africa, the UK, and Asia, paid in stablecoins. She cited Afghanistan as a concrete example of why this matters, noting that women who were known to hold or earn money risked having it confiscated, making crypto wallets a tool for financial sovereignty, and that a PhD refugee from Afghanistan found it impossible to move money into that jurisdiction through conventional channels to fund humanitarian work.

On future adoption, Love predicts finance and AI will be the two dominant areas of mainstream impact. She expects crypto in payments to be largely invisible, with users unaware they are using blockchain under the hood, and sees stablecoins as a key on-ramp that does not require deep technical knowledge. She points to tokenization of real-world assets by large banks and settlement improvement from T plus three to T zero as drivers of institutional interest, and identifies agentic AI economies using digitally native currency as a major future use case, noting that Joe Lubin discussed machine-to-machine IoT payments as a crypto use case as far back as 2017. She acknowledged that the shift toward stablecoins, ETFs, and bank-custodied real-world assets represents some loss of the original cypherpunk momentum, but maintained that decentralization tools around agency, sovereignty, privacy, and custody remain relevant and intact.