Shreg
Spent the last while building out a framework library for reading US software industry news — not "what happened," but "what should I ask to know if this actually matters." 20 interlinked models covering moat durability, pricing signals, M&A/antitrust patterns, talent signals, and AI capex risk, each anchored to a real, dated case (Adobe/Figma, the Slack-Teams antitrust fight, the MongoDB→Redis relicensing wave, OpenAI's board crisis, and more). Wired it up as an MCP server, so any AI agent can query it directly instead of me re-explaining the same frameworks every time a new headline drops. Public graph + connect URL below.
US Software & SaaS
This knowledge graph is a framework library for reasoning about the US software industry, built by a financial analyst covering software and SaaS. Rather than tracking company news or facts, it encodes 20 decision-rule frameworks — moat durability, pricing-model signals, M&A/antitrust patterns, talent/org signals, AI capex and valuation dynamics — each anchored to a real, dated case study. It's most useful when you have a piece of tech news and want to know what questions to ask about its downstream impact, not just what happened.