Seven Powers Framework for Network Moats
Score a network's durable advantage across seven distinct sources of power.
- Difficulty
- Advanced
- Time to result
- ~weeks to results
- Steps
- 9
- Confidence
- 80%
Adapted from Hamilton Helmer's Seven Powers, this framework is used to assess whether a decentralized network or protocol (like Ethereum) has a durable, defensible advantage rather than just a high price. Instead of asking 'is the token going up,' you systematically test the network against seven independent sources of competitive power: counter-positioning, scale economies, switching costs, network economies, process power, branding, and cornered resource. Because crypto networks are multi-layered (protocol, token, applications built on top), the same power can show up at several layers simultaneously, and some powers (like scale economies) can flip into diseconomies if growth causes congestion. The output is a clear-eyed map of where the moat is real, where it's assumed, and where it's actually a liability.
Origin
Extracted from Acquired
Core principles
- 01A moat must explain persistent differential returns, not just current price.
- 02The same underlying asset can have different powers at different layers (protocol vs. token vs. app).
- 03Powers can be double-edged: scale can create diseconomies (e.g., network congestion) as easily as economies.
- 04Absence of a power (e.g., no cornered resource) is a legitimate and useful finding.
How to run it
- 1
Anchor on a value metric
Define what 'differential returns' means for this specific asset before scoring anything, e.g., the market cap of the token or the fees it captures.
Pro tip Ben and David explicitly redefined the metric as 'the total combined value of all the Ether in the world' before scoring Ethereum.
- 2
Test for network economies
Check whether more users/builders make the network more valuable and secure for everyone already on it, and whether that effect compounds across layers (protocol security, app-level token loyalty).
- 3
Test for switching costs
Identify what locks participants in: rewritten code (Solidity vs. other languages), trading pairs denominated in the asset, or tokens that can't be cleanly converted to a competitor's standard.
- 4
Test for scale economies
Determine if growing bigger structurally lowers costs or raises security (e.g., a 51% attack gets more expensive as market cap rises), but also flag when scale instead causes congestion.
Watch out Scale can be a diseconomy, not an economy, if it degrades user experience (e.g., gas fees spiking as usage grows).
- 5
Test for counter-positioning
Ask whether an incumbent competitor could copy the model without cannibalizing its own economics (e.g., could AWS pay users in Amazon stock the way Ethereum pays participants in ETH?).
- 6
Test for cornered resource
Look for a unique, hard-to-replicate asset: a singular founder/figurehead, a base of long-term holders unwilling to sell, or exclusive technical talent.
- 7
Test for branding
Evaluate whether track record and trust let the asset command a premium over technically identical alternatives (e.g., Ethereum vs. a forked chain with the same code).
- 8
Test for process power
Check if embedded organizational routines create an edge; in open, forkable systems this is often absent or even a drag rather than a power.
- 9
Synthesize and flag double-edged powers
Combine findings into an overall moat assessment, explicitly noting which powers are real, absent, or currently working against the network.
In the wild
After the DAO hack, Ethereum hard-forked while a minority kept mining the unforked chain, now called Ethereum Classic. Both run identical code, yet Ethereum's market cap dwarfs Ethereum Classic's.
→ The hosts conclude the gap is branding/Lindy power plus network economies, not technical difference, since the code is nearly the same.
Developers who already built in Solidity face real friction moving to Solana's different tooling, even though Solana offers higher throughput.
→ Illustrates switching costs as a live power favoring the incumbent despite a technically superior challenger.
Common mistakes
Equating price with moat
Treating a rising token price as proof of a durable advantage instead of tracing it to a specific mechanism.
Ignoring diseconomies of scale
Assuming bigger is always better when, in Ethereum's case, growth caused congestion and $70 gas fees that hurt the user experience.
Over-crediting cornered resource
Assuming a single charismatic founder (Vitalik) constitutes a durable cornered resource without evidence the network can't function or evolve without him.
Is it for you?
Best for
Investors or operators trying to distinguish a genuine competitive moat from speculative hype in a networked or protocol-based business.
Not ideal for
Rapidly-changing early-stage projects with no track record, where most of the seven powers can't yet be evaluated with evidence.
From the transcript
“So for folks who are new to the show, the options here coming from Hamilton Helmer Seven Powers are counterpositioning, scale economies, switching costs, network…”
“To me, I think network effects are for any blockchain the number one thing that any of them have.”
From the episode
Ethereum