06-reference/concepts

products for agents

2026-04-05·concept·status: active

The emerging category of products designed for consumption by AI agents, not (only) human eyeballs. As agents become the primary interface for knowledge work, the products that serve them — structured knowledge, machine-readable context, real-time data feeds — become the new infrastructure layer.

The Shift

Yesterday: products for humans (dashboards, reports, articles, apps) Today: products for humans + agents (dual-format, structured + readable) Tomorrow: products primarily for agents (APIs, context graphs, knowledge packs)

Most of today's enterprise data is locked in formats optimized for human consumption — PDFs, dashboards, slide decks, wiki pages. Agents can parse these, but poorly. The opportunity is in building data products that are native to agent consumption: structured, semantic, queryable, and composable.

Where This Shows Up in Our Work

Data Dots ([[01-projects/newsletter/data-dots-product-concept|product concept]]) — human-readable flashcards that double as an agent-ingestible knowledge base. The novel positioning: "download this to give your AI context about data engineering." This is [[06-reference/2026-04-04-karpathy-llm-wiki-idea-file|Karpathy's idea file pattern]] applied as a product.

The vault itself — our Obsidian vault indexed by QMD is a product-for-agents that we built for ourselves. The pattern (structured markdown + semantic search + wikilinks) is productizable.

Data Marketplace ([[01-projects/data-marketplace/index|project]]) — curated industry datasets with semantic context, not just raw data. The value isn't the data itself — it's the context that makes the data useful to an agent. This connects to the [[06-reference/2026-04-04-context-graphs-trillion-dollar-opportunity|Foundation Capital thesis]] that decision traces are the next trillion-dollar platform.

Sanity Check newsletter — articles structured as both human-readable AND agent-ingestible (frontmatter, wikilinks, structured sections). The [[06-reference/2026-04-04-art-business-online-writing-cole|Nicolas Cole]] approach of writing for platforms, adapted: write for humans AND agents.

phData consulting — helping enterprises make their internal data "agent-ready." The [[06-reference/2026-04-04-steam-steel-infinite-minds|context fragmentation problem]] from Ivan Zhao's essay: agents can't work because context is scattered across dozens of tools. The consulting play is consolidating that context into agent-consumable formats.

The Underlying Pattern

Every product-for-agents needs three things:

  1. Structured content — machine-parseable format (JSON, markdown with frontmatter, APIs). Not PDFs, not dashboards, not slide decks.
  2. Semantic context — not just data, but what the data means, how it relates to other data, and when to use it. This is what [[06-reference/2026-04-04-building-the-event-clock|event clocks]] and [[06-reference/2026-04-04-ontology-taxonomy-knowledge-graphs|knowledge graphs]] provide.
  3. Composability — the product should be a building block that agents can combine with other products. This is the [[06-reference/concepts/skills-as-building-blocks|skills-as-building-blocks]] pattern applied to data products.

The Market Signal

[[06-reference/2026-04-04-steam-steel-infinite-minds|Ivan Zhao]] reports Notion runs 700 agents alongside 1,000 employees. [[06-reference/2026-04-04-silent-sirens-import-ai|Jack Clark]] predicts "great and mostly invisible seas of tokens being used for thinking and exchanging information between silicon minds." [[06-reference/2026-04-04-100x-business-with-ai|Vasuman]] is at $3M ARR deploying production agents for enterprise.

The agents are arriving. They need products built for them. Whoever builds the best ones early has a [[06-reference/concepts/compounding-knowledge|compounding]] advantage — because agent-consumed knowledge gets better with use, unlike static human-consumed content.

Open Questions