When trust cracks, most projects reach for louder narratives.
Vanar is trying something harder: rebuilding from the bottom up.
After months of weak price action and growing doubts, its latest long article drops the hype and focuses on one narrow problem—AI agents can’t be economically useful without persistent memory. No grand “AI chain” pitch. Just infrastructure: the Neutron API as a durable storage layer for agent state, integrated through tools like OpenClaw so models can remember, evolve, and survive restarts.
Vanar even acknowledges what the chart already says: real usage hasn’t shown up yet. The response is a usage-driven burn model meant to counter unlock pressure over time—slow, unflashy, and dependent on actual adoption.
This feels like a project moving from narrative mode to repair mode.
Whether it works won’t be decided by essays or threads, but by on-chain signals in 2026: burns, real deployments, real migrations.
Right now, Vanar is trying to mend the trust gap behind the price.
