Leaders win bull markets by engineering demand, aligning with VCs and exchanges, and executing a distinct thesis with durable moats.
Speakers: Haseeb Qureshi (Dragonfly), Cecilia Hsueh (MEXC), SY Lee (Story Protocol)
Bull markets can make expansion look effortless, but sustained growth is designed, not accidental. We attended this TOKEN2049 panel to understand what do protocols and builders need to actually grow.
During the discussion, the panel argued that compounding outcomes come from clear theses, disciplined execution, and early attention to the mechanics of supply and demand. Attractive narratives may draw initial interest; enduring usage depends on precision around who the product is for, what problem it solves, and why users will return.
They added that resilience is built in the up-cycle for the next down-cycle. Partnerships, governance choices, and measurement frameworks should be set before volatility arrives. Teams that pre-build acquisition and retention systems, hire deliberately, and commit to a realistic roadmap are better placed to keep momentum when conditions tighten.
Supply, Demand, and Product Discovery
Trend cycles compress launch timelines and invite look-alikes within days. With a significant share of activity driven by professionals and institutions, the onus is on teams to segment audiences, articulate value clearly, and tailor journeys from discovery to retention. Building features is insufficient without funnels that translate attention into habits.
Qureshi noted that projects and exchanges should minimise discovery friction and reinforce engagement with fair, transparent pricing and straightforward access. Investors can amplify this by funnelling attention towards assets that are easy to find and simple to trade, using distribution, research, and listings to convert interest into durable activity.
Venture Capital: Prevent Avoidable Errors Early
Founders often view VCs as recruiters, introducers, and PR conduits. The panel suggested the greater value lies in pattern recognition applied before months of sunk cost, including stress-testing market choice, token design, and go-to-market while risks are still malleable.
Investors should also operationalise their networks to close key hires and validate early customers. By setting decision gates, aligning on milestones, and clarifying unit economics, VCs can help teams avoid unforced errors that are expensive to unwind later.
Exchanges: Create Usage, Not Just Listings
An exchange becomes more than a price page when distribution is paired with habit-building. Rapid listings may generate attention; depth on the order book encourages genuine trading. Simple incentives—daily rewards, discounts, low-fee pairs—help establish routines that compound liquidity.
Always-on campaigns can anchor steady traffic for token communities. Before listing, exchanges should ask whether an asset is easy to discover, straightforward to trade, worth returning to, and affordable for newcomers. These criteria tilt launches towards repeat usage rather than one-off spikes.
Protocols: Be Your Own First Customer
New networks typically require seeding by the team. Shipping reference applications, underwriting early integrations, and offering clear tooling can demonstrate viability and reduce time to first useful activity. Being the first customer clarifies product gaps faster than external feedback alone.
Where protocols intersect with intellectual property and clean datasets, licensed content can confer an advantage. With appropriate agreements, teams can position the network as a compliant data source for AI and other consumers, creating defensible demand that is less sensitive to market cycles.
Be the Thesis, Not the Meta
Differentiation is a necessity, not a flourish. The panel’s view was that protocols and exchanges should resist derivative “meta” plays and instead execute a distinct thesis that compounds advantages such as distribution, data rights, liquidity depth, or developer tooling.
That means using investor input to avoid preventable mistakes, collaborating with exchanges to manufacture demand, and building revenue moats that endure through volatility. Teams that design for repeat usage are better positioned to outlast the cycle.
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