Early Stage Markets Rarely Look Like Markets

Key insights

4 slides

The core claim

High-value opportunities emerge as niche behaviors before industry maps.

The article argues that founders must learn to spot nascent markets before they become visible on conventional market maps. Early opportunities rarely resemble mature markets; instead they appear as strange, niche behaviors within small communities.

What to track

Three indicators signal an emerging market.

The article identifies three behavioral indicators that signal an emerging market: pre-launch momentum reflected in active waitlists and organic sharing; the spontaneous formation of communities that discuss a product before it exists; and intense, unplanned usage by a handful of power users who either replace…

Three indicators. Founders should identify nascent markets by tracking three specific indicators: pre-launch momentum via waitlists, spontaneous community formation around non-existent products, and intense usage by power users replacing existing tools.

Where to look

Market maps lag behind behavior and early demand.

The conclusion warns that market maps lag behind behavior; founders who observe and act in the “weird corners” of technology—Discord servers, niche subreddits, or early pre-order pages—will capture the first wave of demand.

Lagging maps. Market maps are lagging indicators that fail to capture early-stage demand, making them unreliable for identifying the most valuable entry points.

How to engage

Deep immersion in early adopter workflows beats feature expansion.

The author stresses that founders should focus on a limited group of early adopters, deeply understand their workflows, and iterate rapidly rather than chasing feature expansion.

Immersion first. Early-stage strategy requires deep immersion in the workflows of a limited group of early adopters rather than broad feature expansion.

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Summary

Emily Bennett, an investing partner at a16z speedrun, argues in this guest newsletter post that spotting early markets is a learnable skill, and that founders who wait for a sector to become legible enough for a market map have already missed the most valuable entry points. Maps are described as useful to investors but dangerous to founders, since they lag behind the behavior that creates a market. The most promising opportunities, she says, tend to arrive looking strange rather than looking like opportunities.

Her central thesis is that behavior precedes categories. Markets begin as behavioral shifts in small, overlooked communities, such as a few hundred developers fixated on a tool, and the intensity of usage matters more than the volume. She distinguishes between an app people open often and one that changes how they work. As an example she cites OpenClaw, an open-source developer project requiring terminal fluency, which restructured its adopters' workflows. Within a week or two of its launch, speedrun saw pitches to make such agent systems accessible to non-engineers, followed by pitches for agents running whole business functions like legal and HR, which helped accelerate the agentic workforce thesis.

Bennett offers three signals of real demand before a product is fully built: genuine intent around pre-launch waitlists, including unprompted sharing and referrals; organic early community, where users create tutorials and explainers without company prompting; and intense use by a small group, who either replace existing tools or bend the product toward unplanned use cases.

She also advises founders to avoid endlessly adding features and instead pick ten or fewer users, study them closely, and ship constantly, arguing that what ten power users want generalizes directionally to thousands. She concludes that founders should build the habit of watching fringe spaces like Discord servers and subreddits. Reader comments include one critique that investors rarely back such markets early, and another applying the lesson to go-to-market discipline.