Linda Xie reviews nearly 10 years of personal angel investing: 6 of 50 companies with returns above principal all came from crypto
Scalar Capital co-founder and former Coinbase product lead Linda Xie posted on X on November 8 reviewing nearly 10 years of personal angel investing, saying she has invested in a total of 50 companies, of which 60% are in crypto, 10% are in AI, and the rest are spread across other industries.
She said that 6 investments have so far generated liquid proceeds exceeding the initial capital invested, all from crypto, with 5 from token warrants and 1 from equity, but none of them alone covered the entire portfolio’s invested capital. The investment with the highest paper return by far is an AI company; if it can be monetized, its return could theoretically cover the entire portfolio’s invested capital.
Another 12 companies have formally shut down or exited through acqui-hire, among which 7 investments returned zero, 4 returned 80% to 90% of the initial investment, and 1 remains pending. The above statistics only cover her personal equity investments and do not include her fund or directly held crypto assets such as Bitcoin and Ethereum.
Original source:
Title: After almost 10 years of angel investing in 50 companies... Publisher: Linda Xie（@lindaxie） Publication date: November 8, 2026 URL：https://x.com/lindaxie/status/2119283739658170797 Source nature: X original post (personal statement) Verification status: full original post read, figures consistent with English-language media paraphrases Supporting content: 50-company breakdown, sources of 6 above-principal returns, paper return of the AI company, details of 12 exits and the limited scope of the statistics
ABAB AI Insight
Crypto provided realized liquidity paths, mainly through token warrants rather than traditional equity exits. The AI company contributed a higher paper multiple, but has not yet translated into cash returns, showing differences in monetization timing across sectors.
The exit distribution of personal angel investing shows a typical long-tail pattern: most companies did not generate excess returns, a few crypto projects delivered realized gains, and the paper potential of a single AI project could theoretically cover the overall portfolio. This is similar to the structure in venture capital where a few projects contribute most of the returns, but on a smaller scale and entirely dependent on personal judgment.
Token warrants have become a more common liquidity tool in crypto investing, while traditional equity exits appeared only once in this sample. The high proportion of shutdowns and acqui-hires reflects the common characteristic of high failure rates in early-stage projects, and partial principal recovery indicates that there is a limited asset-recovery mechanism.
The statistics clearly exclude the fund and directly held crypto assets, so they cannot represent her overall investment portfolio performance. Points to watch include whether the AI company later monetizes, the continued liquidity of crypto token warrants, and the differences in exit paths between personal angel investing and institutional funds.
ABAB News · Laws of Cognition
Realized liquidity is concentrated in crypto, while the highest paper multiple comes from AI.
A single project could theoretically cover the portfolio, but unrealized paper returns are not equivalent to recovered capital.
Early-stage investing combines failures with partial recoveries, and exit paths depend on sector-specific tools rather than a uniform equity model.