Having spent eight years in the Web3 infrastructure space, I am very familiar with the套路 of storage projects—whitepapers filled with black technology, testnet data that’s been doctored, and all talk about commercial implementation. So when the Walrus project suddenly appeared, I didn’t jump on the bandwagon to praise it; instead, I remained cautious. Labels like Mysten Labs incubation, $140 million in funding, and a $2 billion valuation sound impressive, but the real questions are: Can the technology be practically implemented? Will the economic model work?

I spent three weeks thoroughly reviewing the technical whitepaper, testing the performance data of RedStuff encoding, visiting existing implementation cases, and re-evaluating the tokenomics from scratch. The results showed that the common one-size-fits-all evaluations in the market are too superficial—either blindly praising or outright criticizing. The reality is far more complex than expected.

First, let’s talk about the technology. The survival of storage projects hinges on whether their technical performance is genuinely usable. Walrus’s core advantage comes from RedStuff’s 2D erasure coding, which essentially uses mathematical encoding to make data storage more efficient. It sounds impressive, but the key question is: how does this encoding perform in real-world scenarios? I tested several data sets, and the results were a mix of surprises and disappointments. I will elaborate on the performance validation details later, but at least one thing is clear—RedStuff is not just a hype on paper; it’s a genuinely usable technical solution.

The tokenomics logic also warrants in-depth analysis. No matter how large a project’s funding or how shiny its background, if the token model is poorly designed, the ecosystem will ultimately collapse. Walrus’s token distribution, release cycle, and incentive mechanisms all determine whether the project can sustain itself. I dissected these data points one by one, trying to identify potential risks.

The subsequent analysis will cover three aspects: first, benchmarking the authenticity of RedStuff’s performance data; second, assessing the sustainability of the tokenomics model; third, evaluating existing implementation cases and commercial prospects. Throughout, I will rely on test data and real-world cases to highlight the project’s core strengths while also acknowledging its potential shortcomings.