US Software & SaaS

40 nodes · 86 edges

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.

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Does it actually help? (5 test questions)

4/5
Graph-augmented wins
1/5
Baseline wins
0/5
Ties

Avg scores (groundedness/framework/specificity) — baseline 3.2/3.6/2.8, graph 4.2/4.2/4.2

  • Graph-augmented won · Show answers

  • Graph-augmented won · Show answers

  • Graph-augmented won · Show answers

  • Graph-augmented won · Show answers

  • Baseline won · Show answers

Posts about this graph (1)

  • derek@derek·4h ago·Finance

    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.