The First Infinity Loop

Hey, it’s him again…

The ancients used Alpha and Omega to symbolize the beginning and the end. Every story has an opening point. Every empire eventually declines. Every living being is born and returns to dust. That seems to be a rule the old world has never broken

When looking at crypto and AI agents, he is starting to think that a different kind of loop is emerging. A loop no longer bound by Alpha or Omega. It is not born to reach an ending, but to sustain itself, adapt to itself, and improve itself through every cycle

Not through magic. Through data, feedback, and economic incentives. Maybe crypto is not the first industry to apply AI. Maybe it is the first place where enough conditions converge for AI to become an economic actor, operating on its own inside an almost infinite loop

AI was built for feedback loops

Many people say AI will affect finance the most because finance is where the money is. He thinks that is true, but it may not reach the deepest part of the problem

Finance benefits from AI not only because it is large. It benefits because it has one of the clearest feedback loops. A good or bad decision does not need to wait long for history to judge it. It can show up quickly through PnL, risk, drawdown, inventory, spread, or execution quality

The faster an agent receives feedback, the more chances it has to adjust. The more it gets stuck inside human waiting rooms, the more its automation power is worn down

Trading is different because the loop can almost close on itself:

• Observe: what the market is doing
• Decide: what price to quote, how much to hedge, whether to reduce inventory or increase exposure
• Act: place orders, cancel orders, rebalance, bridge, LP
• Measure: whether the order filled, how PnL changed, whether drawdown crossed the limit
• Learn: which config worked, which market is drifting, which strategy should reduce size

It is a strange environment. Not because it is easy, but because it reflects outcomes almost immediately. An agent acts, and the market answers in numbers

Crypto never closes

Traditional markets have opening hours, closing hours, holidays, brokers, compliance, market access, and many layers of intermediate control. Crypto is different. It runs 24/7. It runs on Sundays. It runs during holidays. It runs while he sleeps. It runs while he eats banh mi. It runs while he breaks production, with BTC still ticking coldly in the background, as if it never cared whether humans had time to rest

For humans, that is an exhausting environment. For agents, it is natural habitat. An agent does not need sleep. It does not need lunch breaks. It does not need coffee. It does not need a manager to remind it. It only needs data, APIs, wallets, permission to act, and a clear enough objective to follow

For example:

• Earn 20 more dollars per day, but keep drawdown below 5%
• Keep inventory inside a safe range, but quote tight enough to capture flow
• If latency spikes abnormally, reduce size or pause the strategy
• If hedge ratio drifts outside the threshold, rebalance exposure

At that point, an agent is no longer a chatbot answering questions. It becomes an operating layer above a financial system, quietly watching and adjusting the smaller loops beneath it

When agent cost drops below edge

The most interesting part, to him, is the economics of running agents. A strategy that earns 100 dollars per day may not be worth running if it requires a person to watch it all day. But if the cost of running an agent drops to 3 dollars per day, or 0.3 dollars per day, many small strategies that used to sit quietly in the dark start to make sense

In trading, edge is not always a giant opportunity. Many small edges live in corners humans do not want to look at, or do not have enough time to look at: a slightly mispriced spread between two pools, inventory drifting out of balance, a funding rate shift, thin liquidity at a strange hour, or a niche market too small for a large team to care about

Humans often ignore those edges because attention is expensive. Agents do not. When the cost of observing, analyzing, and acting becomes low enough, small opportunities can start adding up into a meaningful stream of cash flow. That is when an agent becomes a new kind of worker. Not a worker paid by the hour, but a worker that lives inside the loop, consuming data and returning decisions

Agents do not only trade, they audit

When people think about AI trading, they usually imagine AI predicting prices. He is not sure that is the most important part. In a real market making or trading system, the problem is not only whether to buy or sell. The problem is knowing whether the machine underneath is still operating correctly, or whether it has started to drift off course:

• Is the spread unusually wide
• Has inventory drifted too far
• Is PnL coming from real edge, or just short-term luck
• Is the hedge ratio still correct
• Has latency increased
• Did an API disconnect
• Is a strategy making money because it is good, or because the market has not punished it yet

This is where agents are powerful. An agent can sit above Grafana, Prometheus, Loki, databases, exchange APIs, and transaction history to audit the system continuously. It does not get tired. It does not get lazy. It does not miss things just because it had a bad day. A kind of digital gatekeeper, sleepless and not waiting to be praised

If the trading bot underneath is the executor, the agent above it can become the operator. The executor follows config. The operator sees the broader system, detects anomalies, proposes changes, rolls back bad decisions, or calls a human when risk moves outside the allowed boundary

This is the major difference between old trading bots and AI agents. Old bots run logic that has already been written. New agents can read system state, understand objectives, compare multiple data sources, and adjust behavior within a safe operating range. They do not only execute commands, they begin to understand why the loop should change rhythm

Permissionless is the final piece

If we only talk about finance, TradFi also has markets, data, PnL, and feedback loops. But crypto adds one crucial property: permissionless access. An agent in crypto can create a wallet, hold assets, trade, LP, bridge, stake, borrow, lend, or interact directly with smart contracts without standing in front of a traditional broker’s door

Of course there are risks. Guardrails are necessary. Permission limits are necessary. Private keys and access control must be audited carefully. But architecturally, crypto opens a very different possibility. AI does not only analyze the market from the outside. AI can touch the market directly

That is what makes crypto special. It is not only a place where AI gives recommendations for humans to click. It is a place where AI can enter the action loop itself, as long as humans design strong enough boundaries. In TradFi, agents are often stopped at the layer of papers, dashboards, and recommendations. In crypto, agents can go further: execute. They can cross the line between idea and action

The First Infinity Loop

He thinks future trading systems will no longer be a lonely bot running somewhere on a server. They may become a three-layer structure:

• Human
• AI Manager
• Executor Bots

Humans will no longer need to adjust every spread, every skew, and every inventory threshold by hand each day. Instead, humans define the initial will, as if giving the machine a boundary to operate within:

• Earn more yield, but keep drawdown below this threshold
• Market make this pair, but do not let inventory drift beyond this range
• Increase exposure when liquidity is healthy, reduce size when volatility crosses the limit

The AI manager observes markets, reads system state, analyzes logs, checks PnL, adjusts config, and audits results. The bots underneath only need to execute: place orders, cancel orders, hedge, rebalance

Seen this way, crypto is not just another industry that benefits from AI. Crypto may be the first environment where AI workers can generate revenue continuously, not by writing content, not by answering tickets, but by living inside a 24/7 economic loop

In software, an infinity loop is a bug. In crypto, if placed inside the right boundaries, it can become a business model

Maybe in a few years, we will no longer call this “AI in finance”. We may call it a new financial system, where most micro-decisions are made by agents, while humans define goals and risk limits

If that happens, crypto will not only be the first place where AI is applied. It will be where the economy of AI is born, an economy that does not begin with an opening bell, and may not have a closing bell at all

❤️ cowriter aethery