Between 2000 and 2020, private equity firms acquired roughly two-thirds of all large companies that later went bankrupt. By 2021, leveraged buyouts were running at over a trillion dollars a year. That sounds like a recent story, but it's just the newest chapter of an old pattern.

Under every extractive regime, across every era, one mechanism repeats: someone knows something others do not. The names and tools change. The pattern does not. The first step in building anything better is to see that pattern clearly.

Call it what it is: extraction runs on information asymmetry.

Feudal lords knew how land, tithes, and obligations accumulated into power. Peasants knew only that they owed grain and labor. Industrial capitalists understood surplus value and capital structure. Workers saw wages and prices. Financial engineers know how tranches, covenants, and leverage work. Pensioners see quarterly returns. In Web3, protocol insiders understand tokenomics, governance mechanics, and smart contract risks. Most users see yields, airdrops, and voting UIs.

The pattern is simple. If one side understands the system and the other does not, the knowledgeable side can extract. If understanding is broadly shared, extraction gets more complicated and more expensive. Every era's "innovation" in extraction is just a new way of maintaining that asymmetry when old methods stop working.

Premodern extraction relied on restricting knowledge itself. Literacy, numeracy, legal, and religious understanding were confined to the priesthood and nobility. You didn't need complex systems. You needed people who could not read the rules.

Modern extraction, facing mass literacy and public education, shifted the game into the realm of system complexity. Legal codes, financial products, and corporate structures became so intricate that only specialists could navigate them. Information was technically available, but functionally opaque.

Postmodern extraction, facing expanded access and growing suspicion of institutions, directly attacked sensemaking. Trust in expertise eroded. Conspiracy and polarization became ambient. People were taught to distrust those who actually understood the systems they lived in.

Web3 arrived promising to break this cycle with transparency. Everything on-chain, nothing hidden. But transparency without comprehension is just noise. The new move is to keep data public while understanding remains private.

We need a term for this pattern, the whole cycle that keeps extraction alive across eras and forms. Call it 'Devolution': the system-wide phenomenon in which extraction, backlash, and institutional disruption spiral into greater asymmetry, creating conditions for a new round of extraction.

Here's how it works.

Extraction intensifies under one regime. A system develops extractive patterns. Insiders understand the game. Outsiders do not. Value flows to those with superior knowledge.

When extraction intensifies enough, people push back. Sometimes that looks like regulation. Sometimes it looks like a revolution. Either way, the intention is to reduce abuse by checking or replacing those in power. But here's the critical move: revolutions throw out institutions, but also the accumulated knowledge of how those institutions worked. New elites come in with their own opaque methods and loyal experts. External shocks give cover for emergency powers. In the chaos, very few people understand what is really happening. Extractors thrive in that environment.

Regulatory waves can have a similar effect. Complex new regimes get written by and for specialists. Those who can afford the best lawyers and lobbyists adapt quickly. The public hears "reform" and "protection." The reality is often a new layer of rules only insiders can navigate.

The disruption itself creates information gaps- larger ones than before. Actors who understand the post-revolution landscape take their positions. They study the new rules faster, understand the new levers better, and begin to extract accordingly. Then, the extraction resumes, often more sophisticated than before. We end up back where we started, but with new methods, new extractors, and worse asymmetry than we had initially been.

The result: we revolve and devolve instead of evolve- the surface story changes. The information power gradient does not.

'Devolution' is not just extraction. It's the entire cycle that keeps systems stuck in a repeating loop. We call it "devolution" because the net effect is that systems do not improve. They revolve, periodically, and cumulatively devolve. They spin through different forms and faces, but the underlying dynamic remains: power concentrates around those who understand the system better than everyone else.

The cycle operates through multiple channels simultaneously. Extractors work to maintain advantage in several ways at once.

They keep knowledge concentrated and teach people to distrust those who understand. They create cultures where "only insiders really get this" becomes normal. They attack expertise itself. Meanwhile, complexity expands in ways that limit outsiders' ability to act meaningfully. Mechanisms become more complex to decode. Participation is allowed, but is often performative; your vote happens, but you don't understand what you're voting on.

Stories shift to justify current arrangements. "Move fast and break things." "We need efficiency." "Only professionals can handle this." These narratives become so normal that people stop questioning whether extraction is even happening. The rules themselves consolidate in ways that benefit those who understand them. New layers of complexity get added. Barriers to meaningful participation harden into the system itself. What was once a choice becomes an inevitability.

When all of these shift toward extraction and away from comprehension simultaneously, you have 'devolution' in motion. And when backlash comes, it often disrupts all of them at once, creating the chaos in which new extractors thrive.

Web3 was supposed to be different. "Don't trust, verify." "Code is law." "Everything is on-chain." In theory, transparency should have killed the old information games.

Instead, it created a new kind of asymmetry: transparent but incomprehensible systems.

Smart contracts are public, but most people cannot read Solidity or reason about contract interactions. Governance votes are visible, but the implications of each proposal require deep knowledge of the protocol. Token distributions can be inspected, but understanding what concentration patterns mean for future control is a specialized skill.

Meanwhile, actors coming from traditional finance and large crypto funds brought existing extraction playbooks with them. They know how to spot mispriced risk, arbitrage governance, and quietly accumulate control over cash flows. They have research teams, analysts, and years of experience.

On paper, everyone has the same access to information. In practice, only a few can interpret it at the necessary level. That's information asymmetry in a new outfit.

The result is precisely what you'd expect: protocols that look decentralized but have governance effectively controlled by a small set of holders. Public goods narratives are used to market systems whose underlying economics favor capital concentration. "Community governance" processes where most participants cannot realistically evaluate proposals. Web3 didn't end asymmetry. It forked it. It created a frontier for 'devolution' to operate in new forms.

When you strip away branding and era-specific jargon, extractors tend to follow a recognizable sequence.

First, they get ahead on understanding. Study the system until you understand its real levers better than almost anyone else. That might mean reading legal codes, modeling capital flows, or analyzing contract dependencies. In web3, it means deeply understanding protocol governance, incentives, and upgrade paths.

Then they keep that understanding scarce. Don't lie about how the system works. Just don't go out of your way to teach it. Let public documentation stay partial, highly technical, or marketing-driven. Encourage a culture where "only insiders really get this."

Next, wrap it in a story. Frame your position as natural and beneficial: "providing liquidity," "professionalizing governance," "de-risking for users," "aligning incentives." The story doesn't have to be false. It just has to be incomplete in a way that justifies your advantage.

Then influence the rules. Use your superior understanding to shape formal constraints: regulation, standards, protocol parameters. In web3, that looks like governance proposals that simplify or centralize under the banner of efficiency, security, or compliance.

Finally, scale the extraction. Once your position is encoded into the rules, extraction becomes routine. Fees, yield skims, governance capture, and preferential access become normal operations, not visible exceptions.

At no point is this primarily about hiding raw data. It's about staying ahead on comprehension, then solidifying that lead in code, law, and narrative.

If systems are going to escape 'devolution', the extraction/backlash/disruption cycle, then they have to start here: no lasting change is possible if information asymmetry remains structurally intact.

You can introduce new tokens, DAOs, municipal ownership models, and cooperatives. If a small group understands how they really work while most participants do not, 'devolution' will repeat. Maybe with nicer branding. Maybe with better intentions. But structurally, the same cycle.

Breaking free of 'devolution' means no more pretending transparency alone is enough. No more assuming "community governance" is meaningful when only a handful understand the system. No more cycles of "innovate, extract, revolt, reset, repeat." It means treating shared understanding, not just shared ownership, as a first-class design constraint.

That's what Prevolution means: designing systems before the cycle needs to trigger, in a way that makes 'devolution' structurally more complex to activate.

The following article looks at four real systems: Gitcoin, Lido, Uniswap, and Octant. It asks a simple question: in each one, is the system evolving or devolving right now? How do you read the signals?

The third article lays out the Prevolutionary Architecture: the layers that, taken together, make it structurally more complex to maintain information asymmetry and structurally easier to keep extraction tamed rather than dominant.