This post is taking part in the Lens x Kiwi Writing Contest
Ethereum blockspace is highly valuable, and everyone wants a piece of it. How do they achieve this? By posting whatever they can onto the L1.
I’m not here to take sides on what I’m about to describe; I’ll try to remain neutral. I don’t believe the focus should be solely on Ethereum as the primary L1. There are many L1s out there, but their blockspace is often deemed not valuable enough for L2s to post data to.
Personally, I don’t think I hold any bias towards Ethereum or any L2s. I consider myself neutral, as the project I work on—Routescan—is ‘credibly neutral.’ We index and support multiple blockchain ecosystems. While we are currently more focused on EVM chains, that’s simply a business decision and doesn’t influence my broader vision for the blockchain industry.
There’s a saying that for an L2 to succeed in the long term, it needs to meet several key requirements:
- Settle on Ethereum
- Post data to Ethereum
- Secure its validity via Ethereum
- Use ETH as the gas token
There are likely other assumptions, but I haven’t built a chain myself, so I wouldn’t know all of them.
The general idea is that L2s are meant to scale and expand Ethereum’s capacity.
There are various charts that show how Ethereum is being scaled by L2s. One well-known chart is L2Beat’s Activity chart.
L2Beat currently tracks over 100 L2s and L3s, and at Routescan, we already index more than 30 of them.
However, to truly understand whether rollups are scaling Ethereum, we need to ask: What exactly are rollups scaling right now?
The original purpose of rollups was to offload tasks that were previously handled by Ethereum and enable new activities that benefit from increased throughput. But I don’t believe that’s what’s happening.
Here’s what I see occurring in what I call the Greater Ethereum Ecosystem (L1 + L2s + L3s, all ultimately settling on Ethereum):
1. A new L2 announces its development.
2. Developers and users flock to its testnet, hoping to farm an airdrop.
3. After a while, an incentive program is launched, often in multiple “Seasons,” with more rewards for greater participation.
4. The mainnet launches, and activity spikes as users hoping for an airdrop increase their on-chain actions, leading to tens of TPS.
5. When the airdrop is finally distributed, many users are disappointed because they expected life-changing rewards.
6. Developers, however, are satisfied with the launch incentives and start deploying projects with the chain’s token and their own token incentives.
7. Users, hoping to recoup their losses from the chain’s airdrop with dApp incentives, continue high levels of activity.
8. Eventually, major dApps airdrop their tokens, but users are again disappointed and leave the chain or reduce their activity, leading to a sharp decrease in throughput.
9. Most dApps are either clones of those on Ethereum or other L1s, or expansions by the same teams.
While I understand the redundancy of having DEXs and DeFi primitives available on different L1s and rollups, the question remains: Do we really need a new rollup to test a DEX that only has a slightly different base fee? Ethereum isn’t scaling its use cases with rollups as much as it could.
At Routescan, we differentiate chains between DeFi and Gaming chains, as they exhibit distinct user behaviors. DeFi chains usually have lower sustained TPS but a larger user base, while Gaming chains often see higher TPS from a smaller number of users. We used to treat all chains equally, but that was a mistake. Now, we categorize the 1,000+ chains we monitor into these two types.
The point is, launching a new rollup should add efficiency to the broader ecosystem, not inefficiency.
If, paradoxically, no rollups existed and L1s communicated only via bridges like Wormhole, LayerZero, or Synapse, the L1s could focus on increasing throughput as a monolithic system. But that hasn’t worked before.
Now, within Ethereum, multiple sub-ecosystems promise cross-chain standards, such as Optimism’s Superchain, Polygon’s AggLayer, ZKSync’s Elastic Chains, StarkNet’s StarkEx, and Arbitrum’s Orbit.
Imagine if these ecosystems succeed in creating functional cross-chain standards. Projects would need to choose which ecosystem to join, creating competition between standards, driven by—you guessed it—incentives. This could lead us into the same trap I described earlier, but with an added layer of complexity: ecosystem → chains → dApps.
The original intent of Ethereum was to scale blockspace without sacrificing security. However, the narrative has shifted. Now, scaling blockspace seems to be about generating profits and fostering developer adoption, even if it doesn’t mean to directly drive more adoption and new use cases. The focus on increasing blockspace, rather than understanding why we need to increase it at any point, is misguided.
If we apply Parkinson’s Law to this dynamic, which states that “The demand upon a resource tends to expand to match the supply of the resource,” we can see how blockspace demand will expand with supply, even if it doesn’t make much sense.
In 2017, during the Cryptokitties craze, blockspace demand exceeded supply for a short period. However, the perceived price of blockspace was almost zero due to market dynamics and FOMO. Now, with scaling efforts, as blockspace approaches zero in cost, this law becomes even more relevant.
But when the price becomes actually zero, or really close to it, then this law is particularly accurate. A consequence of this is the theory of induced demand, where an increase in the supply (demand) of an item that has a price of zero or close to zero actually creates more demand.
Applying this to Ethereum L1 is the narrative of scaling with an enormous amount of rollups - dress it with Parkinson’s Law, and this is what happens:
X = new chains per year
k = number of chains who want to be L2s / DA layers for L3s
m = number of transactions to coordinate cross-chain intents / operations (micropolitics)
P = we will not use this, as it describes the age of workers in the original formula, and it does not apply in this context
n = number of unique operations completed (transaction or intents)
So the new equation is:
This equation is multidimensional, so we need to make some assumptions to plot a chart that we can actually understand.
The reader can make any kind of assumption for themselves, but in this post I’ll only make one example.
Let’s assume that:
- X = 100, based on how many chains were launched in the past 12 months
- n = 1 billion, reasonably the amount of transactions or intents that were executed in the past 12 months, maybe even more
- m = 3, because I assume that 3 transactions / atomic operations are needed for every cross-chain communication: 1 from the origin chain to the destination chain to communicate the request, 1 from the destination chain back to the origin chain to communicate the state update on the destination chain, and 1 to propagate the new state update to the origin chain. I may get it wrong, if so, the reader can try with m = 2 or even m = 4 to see how that changes the system.
Let’s explicit K and plot the chart as a function of X:
Increased blockspace supply, driven by the proliferation of rollups, could create an endless loop of demand. Each new rollup will increase the need for more blockspace to post data, as existing L2s become too costly.
This flow of thought makes sense to me, but I wrote this during TOKEN2049, so I may not have captured everything perfectly.
My main point is this: There’s no need for every project to launch its own chain or token. We should focus on driving mainstream adoption by building good applications that people want to use, while minimizing speculation, which only adds inefficiency to the system. And look to build an actual shared standard for all rollups, and not incentivize competition across sub (L2) ecosystems.
