KaiOnChain

Nie zacząłem szukać Fogo, ponieważ szukałem innej warstwy 1. Szczerze mówiąc, myślałem, że skończyłem próbować zrozumieć, dlaczego nowe wciąż się pojawiają. W pewnym momencie każde ogłoszenie zaczyna brzmieć znajomo — szybsza realizacja, lepsza skalowalność, ulepszona infrastruktura. Język powtarza się wystarczająco często, że ciekawość ustępuje miejsca sceptycyzmowi.

To, co mnie przyciągnęło, nie była obietnica wydajności. To było cichsze niewygoda.

Jeśli systemy zbudowane do wysokiej przepustowości już istnieją, dlaczego ktokolwiek wciąż czuje potrzebę zbudowania nowego? A bardziej konkretnie, dlaczego zbudować jeden wokół Solana Virtual Machine zamiast wynaleźć coś całkowicie nowego?

I didn’t notice Fogo because it promised performance. Everyone promises performance. At this point, speed in crypto feels less like innovation and more like table stakes — something every new chain claims before anyone has actually tried to break it.

What caught my attention instead was a quieter detail: Fogo runs the Solana Virtual Machine.

That detail bothered me more than it impressed me.

If Solana already exists, already runs the SVM, already processes massive amounts of activity, then why rebuild an entirely new Layer 1 around the same execution environment? Reusing technology usually signals efficiency. Rebuilding infrastructure around it signals dissatisfaction. I found myself trying to figure out which one this was.

At first, I assumed the answer would be technical. Maybe higher throughput. Maybe cleaner architecture. Maybe some incremental optimization hidden behind benchmark numbers. But the more I looked, the less convincing that explanation felt. Execution speed alone rarely justifies creating a new sovereign network. You don’t fragment liquidity, validators, and developer attention unless something deeper feels constrained.

That’s when the question shifted for me. Maybe Fogo isn’t trying to improve execution itself. Maybe it’s trying to change who controls the environment in which execution happens.

The Solana Virtual Machine already solved a difficult problem: how to process many transactions simultaneously without forcing everything into a single ordered queue. Developers learned how to design around accounts, parallelism, and predictable runtime behavior. Entire applications now assume those mechanics. Replacing that would mean asking builders to relearn habits they’ve only recently stabilized around.

So Fogo doesn’t ask them to relearn anything.

And that decision says more than any performance claim could.

Keeping the SVM means computation behaves familiarly. Programs run the way developers expect. Tooling translates. Mental models survive the move. But once execution becomes portable, something subtle happens. The chain itself stops being defined by how transactions run and starts being defined by the conditions surrounding them — who validates blocks, how fees emerge, how upgrades happen, how quickly coordination decisions can be made.

In other words, execution stays constant while governance, economics, and operational assumptions become adjustable.

That realization made the project feel less like competition and more like separation. Solana represents one shared environment optimized for global neutrality. An independent SVM-based chain can instead optimize for consistency, specialization, or responsiveness without needing universal agreement from a massive ecosystem.

But optimization always comes with exclusion, even when nobody says it out loud.

A network tuned for predictable high performance quietly assumes certain things about its participants. Validators may need stronger hardware. Coordination may rely on tighter groups. Decision-making may favor speed over broad consensus. None of this makes the system better or worse; it simply changes who feels comfortable building or validating there.

And comfort matters more than benchmarks.

Developers design differently when they trust latency. If execution delays are rare, applications stop hedging against congestion. Markets react faster. Games move logic fully onchain instead of keeping safety valves offchain. Entire categories of software begin assuming responsiveness rather than hoping for it.

But performance has gravity. Fast environments tend to attract actors who benefit most from speed long before everyday users arrive. Traders, arbitrage systems, and automation infrastructure usually show up first because milliseconds translate directly into profit. Their activity then reshapes fee dynamics and resource competition in ways early architecture discussions rarely anticipate.

So the real test isn’t whether Fogo can run quickly under ideal conditions. It’s how behavior changes once speed becomes economically valuable.

I keep wondering whether predictable execution widens participation or quietly advantages those already equipped to exploit it. High-performance systems sometimes democratize access; other times they intensify competition until only specialized actors thrive. The difference usually appears months or years after launch, not in technical documentation.

Another thing becomes unavoidable once applications begin depending on a network: governance stops being theoretical. Upgrade decisions become operational risk. Validator coordination becomes uptime assurance. Policy choices begin affecting real businesses rather than abstract communities.

At that stage, governance stops sitting outside the product. It becomes part of the runtime itself.

An independent SVM chain like Fogo may ultimately be judged less by architecture and more by coordination credibility — whether participants believe rules will evolve predictably enough to build long-term systems on top of them. Speed loses meaning if uncertainty replaces congestion as the primary risk.

And then there’s liquidity, the quiet constraint behind every new Layer 1. Even perfect execution cannot escape fragmentation. Users, assets, and developers already live elsewhere. Familiar execution lowers psychological migration costs, but capital moves more cautiously than code. Interoperability stops being an enhancement and becomes survival infrastructure.

I find myself unsure whether specialization strengthens ecosystems or splinters them further. A fast execution environment connected to slower networks inherits their limits; an isolated one risks irrelevance. Balancing those forces may turn out to be harder than building performance in the first place.

What remains unproven isn’t technological capability but durability. Will developers move because they can, or only when existing environments become restrictive enough to force migration? Will performance remain stable once adversarial usage appears? Will governance move quickly without undermining legitimacy? These questions can’t be answered through design choices alone.

For now, I don’t think the interesting question is whether Fogo succeeds as another Layer 1.

The more useful question might be whether separating a mature execution environment from its original network changes how blockchains evolve at all — or whether, over time, every high-performance system slowly recreates the same coordination pressures it originally tried to escape.

The signals worth watching feel behavioral rather than technical: what kinds of applications appear first, who benefits most from early adoption, how often intervention becomes necessary, and whether developers begin building things that simply wouldn’t make sense anywhere else.

$FOGO @Fogo Official #fogo

Nie zaczęłam myśleć o Mira Network, ponieważ szukałam innego projektu blockchain lub innej próby naprawienia sztucznej inteligencji. Pytanie pojawiło się znacznie wcześniej, prawie przypadkowo, podczas oglądania ludzi korzystających z narzędzi AI z dziwną mieszanką zależności i podejrzliwości.

Wszyscy ufają AI wystarczająco, aby z niej korzystać — ale nigdy na tyle, aby przestać ją sprawdzać.

Ta sprzeczność ciągle mnie niepokoiła. Prosimy maszyny o podsumowanie prac badawczych, sporządzanie języka prawnego, pisanie kodu produkcyjnego, a nawet kierowanie decyzjami, które niosą ze sobą konsekwencje finansowe lub medyczne. A mimo to ostatni krok zawsze polega na weryfikacji przez człowieka, jakby AI stała się niesamowicie szybkim stażystą, który nigdy nie może zdobyć autonomii.