What Is NEAR Protocol? The Layer-1 Blockchain Built for AI
Most layer-1 blockchains are generalists. They compete on throughput, fees, and finality, and they pitch themselves as the chain that can do everything. NEAR took a different route. In the video, Brian walks through why NEAR's design started with an AI problem, not a blockchain problem — and why the third piece of its stack may be closer to mainstream than most people assume.
The Origin: An AI Project That Needed Better Plumbing
The story starts around 2017–2018. Two founders set out to build AI that could develop a piece of software end to end — full lifecycle, fully finished, ready to ship. They ran into a wall. The infrastructure they needed didn't exist, so they paused the AI work and built the foundational layer first. That foundation became NEAR.
That sequence matters when you're judging AI tokens. Plenty of chains launched as general-purpose networks, looked around at what was trending, and rebranded as "AI layer 1s." NEAR was built from the AI standpoint from day one. If you want a repeatable process for separating real infrastructure from narrative plays, this walkthrough on how to evaluate AI tokens and crypto infrastructure projects covers the questions worth asking before you buy anything in this category.
Three Building Blocks: Ironclaw, NEAR AI Cloud, and the Agent Marketplace
On top of the base layer, NEAR focuses on three solutions.
Ironclaw tackles privacy and confidentiality. A government agency, a company, or an individual may want AI's output without handing a public model their sensitive data. Ironclaw lets agents access APIs, wallets, and tools without exposing the underlying credentials. Brian's analogy in the video: it's like asking a friend to run an errand and having them reply, "Sure — what's your bank login and password?" You don't want to give it. This is the mechanism that lets the task happen anyway.
NEAR AI Cloud addresses scale and cost. Large language models are enormous, and self-hosting the infrastructure is expensive and awkward, especially with distributed teams. The AI Cloud lets you run a model in a confidential environment where nobody — not competitors, not even the cloud operator — sees what's happening.
The agent marketplace is the third piece, and the one Brian finds most interesting.
AI Agents Hiring AI Agents
Think of Fiverr, but for machines. You post a task, agents bid on time and price, an agent is selected, and payment settles on-chain.
The more interesting version is one step further out: your AI agent acting as a manager. You describe the outcome, and it delegates to research agents, design agents, and marketing agents — finding specialists, running them in parallel, paying each one, and returning the finished work. You set the budget; it runs around the clock. That's the decentralized AI economy NEAR is engineering toward, with the blockchain handling verification, coordination, and payments.
On Price — And Approaching It Honestly
Brian notes NEAR traded near $20 on the weekly chart going back to around October 2020, dipped recently to about $1 — close to its all-time low — and sat near $2.34 at the time of filming. He shares personal opinions about upside and is explicit that it's never financial advice and that you should research it yourself.
Two habits help here. First, position sizing and allocation: read through how to build a diversified crypto portfolio across sectors before concentrating into any single narrative. Second, tracking: adding NEAR to a structured list rather than watching it sporadically is exactly how you avoid the "I missed it at a dollar" problem, which is why this guide to building a crypto watchlist you'll actually check is worth twenty minutes.
If you do decide to take a position in smaller-cap AI infrastructure tokens, listing coverage matters — many never reach the largest venues. Traders who want access to altcoins with low spot trading fees on MEXC often use it for exactly this reason, though as always, verify the pair and the withdrawal terms before you deposit.
AI agents becoming mainstream, needing secure access to wallets and enterprise systems, and enterprises demanding privacy and auditability — that's the bet NEAR is making. Whether it pays off is your call to research.
If you want help working through theses like this one alongside other people learning the same skills, join the Crypto School community at skool.com/crypto-profit for live market updates and Q&A Monday through Friday.
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