Opus 5.5 + Jev is actually the most insane AI trading bot you could build right now.
I've spent the last week trying to crack the code on how I can combine these two models to build the ultimate trading bot, and I finally did it.
In this article, I'll show you how it works and how to set up your own version of the high-frequency trading bot I've built.
I'm quite excited about this one. It's unlike any of my previous AI trading bot builds. Jev has introduced an entirely new element to probabilistic trading.
You can use the latest Opus 5.5 model as the brain, and take advantage of Jev's cheap inference decision-making to make fast, cheap, high-quality trading decisions.
For reference, here's the bot trading $HYPE just last week:
My Trading Bot \live\
What I'm covering today:
- Brief Intro to Jev
- Trading Bot Architecture
- Setting up the Technicals
- Finding Profitable Strategies
- News Trading with Jev (use case)
- Final Tips
Let's get right into things:
Brief Intro to Jev
If you haven't heard of Jev, let me be the first to introduce it to you.
Jev is essentially a new type of AI model from TypeSafe AI that works quite differently from the LLMs you're probably used to.
https://x.com/CompleteSkeptic/status/2099925682726002904
Jev doesn't write any text at all; TypeSafe calls it a "System One" model.
In simple terms, I like to think of Jev as an AI decision framework.
You give it possible decisions upfront, then Jev evaluates the outcomes and returns a probability score.
Jev Explained
In the example of trading, that could look like:
→ Is this headline bullish, bearish, or neutral? 72% bearish
→ Is buying pressure building? 81% yes
→ Which way is price moving? Up, 64%
Jev versus a Typical LLM
The easiest way to understand Jev is to compare Jev versus a typical LLM.
At its core, Jev does not try to “predict” tokens the same way a model like Claude would.
Instead, it grades the fixed set of outcomes you provide.
Jev ELI5
Why use Jev for Trading?
Put simply: Speed and cost.
Claude and ChatGPT can take several seconds to reason through a decision and are quite expensive to do so.
Jev is 200-400x cheaper AND faster than models from GPT/Claude.
Jev answers in roughly 70-500 milliseconds and costs around $0.042 per million input tokens, with output free. In my demo above, Jev is running at ~400 milliseconds.
For high-frequency and news trading, Jev is perfect. It's fast and cheap, and it was designed to basically assign probabilities to fixed outcomes (trading is essentially just up/down, so this is great).
Trading Bot Architecture
The actual trading bot setup is made up of four key components:
- Claude (Opus 5.5) is the brain. It runs the backtests and designs the final strategy that Jev runs on.
- Jev is the decision layer. It ingests live market data and returns a probability for a trade setup.
- Your strategy (stop loss, take profit, etc.)
- The exchange serves as the execution layer.
Trading Bot Architecture
How a trade actually fires
Claude designs the strategy → Claude turns the strategy into questions to ask Jev → Jev reads live market data and answers with probabilities → Trades fire
Why I've designed the architecture this way
Opus 5.5 is the LLM that handles the thinking that happens once (high-level strategy), and Jev handles the decisions that happen constantly.
You get the best of both worlds here.
The best decision model to design the strategy, and the cheapest/fastest model to actually execute it.
Possibilities with Jev + Opus 5.5
With this trading architecture, the possibilities are endless.
Some ideas:
- Jev executing trades based on news headlines (I built this - shown below)
- High-frequency trading
- Prediction market probability trading
- Momentum/volatility-based trading
- General investing/portfolio management
Jev Newsroom
Obviously, in this article I'm covering how to use Jev as a high-frequency trading bot, but don't be afraid to get creative and use it for these other use cases too.
Setting up the Technicals
Now that you understand the high-level architecture, here's how to set it up in practice.
The setup essentially runs off a single mega prompt that you can drop into Claude Code (or Codex if you want to use Astra).
The full setup prompt is too long to attach here on 𝕏, so I put it for free in my Skool community.
Just head over to Classroom → Free Asset Library → Scroll down to Opus 5.5 + Jev.
https://www.skool.com/milesdeutscherfinance
The prompt does three things:
- Installs Jev and walks you through deploying your bot on Vercel, so you don't have to work it out yourself
- Builds a strategy-tester harness dashboard
- Connects everything to your exchange for execution
Two routes for actual trade execution
Whichever route you pick, I recommend starting with paper trading.
Path 1: Alpaca (the quick start) Alpaca has both paper and live trading, plus crypto and stocks.
Alpaca
Just take your API key and put it in the .env file that Claude Code prompts you to create. Claude feeds the data to Jev, and Jev's signals go to your paper account.
Path 2: An always-on server (more complex)
Your second option is to deploy a VPS with a provider like Hostinger, so your bot can run 24/7 without you.
You can run this on older hardware, such as a Mac Mini.
You have the option here to use a tool like TriggerTrade, which essentially triggers trades in the cloud based on a predetermined Pine Script.
If you go this route, Opus 5.5 can guide you through the exact steps here.
Path 1 versus Path 2
Finding Profitable Strategies
Probably the most important part of this entire article. How to actually make money.
Your strategy is everything. Without a good strategy, you're just automating losses.
The way you should think about your strategy is that it's the "rulebook" Jev will use to generate buy/sell signals.
There are a few good places to find/backtest profitable trading strategies that you can feed AI, but the crux of it is this:
- Backtest hundreds or thousands of ideas - this is the volume game
- Filter the survivors
- Forward test them
- Paper trade test them
- Go live with small capital to test execution
In the article below, I go more in-depth as to how to find winning strategies:
https://x.com/milesdeutscher/status/2082095561176703135
Some places worth searching for strategies:
- TradingView public communities
- AI (use Claude to backtest real data)
- GitHub repos
How I personally find strategies (backtesting engine)
I use a backtesting engine I built myself. I can ask it to design a backtest across various assets, tell it the kind of strategy I'm after, and let it run multi-hour searches that return a shortlist.
I may release it at some point, but for now it's just for my own use.
The good news is, you don't need mine. You can open Claude Code, ask it to build a backtesting engine harness, and use the strongest model you have to backtest market data.
Once you have a strategy you want to test, inject it into your Claude chat where you're building your trading bot so it can ingest and adopt it.
News Trading with Jev (use case)
How a news trading engine works
Live news feed → Jev analyses → Scan your strategy → Trade based on set parameters
News Trading Engine
This is one of the coolest use cases I found for Jev in financial markets.
News trading is a probability game. A headline drops, and you have a very short window to work out what it means before the market prices it in.
I basically built a dashboard where I can watch headlines come in, see Jev label each one, and gain a real-time market edge with Jev's speed + execution.
News Trading Engine \live\
Final Tips
• Before any strategy goes live, set the rules that limit the damage when it's wrong. Build your risk management framework into your strategy. md file
• Things to include in your strategy. md: max position size, daily loss limit, kill switch, manual approval for certain trades
• Use API keys with trading permission only and withdrawals switched off.
• Set up alerts (via BotFather on TG)
• Keep a human in the loop on bigger trades
• I personally use Bybit for execution, but for this to work properly, you need any exchange that allows AI connectivity via an MCP + API.
I hope you've found this article helpful.
If you did, be sure to follow me here @milesdeutscher. . Every single day I post about how you can actually use AI to gain an edge in financial markets.
For deeper AI insights, follow me over on@aiedge_.
Reminder: You can download the full mega prompt to send to Claude now to set up your Opus 5.5 + Jev trading bot.
Posted for free in my Skool community.
👉https://www.skool.com/milesdeutscherfinance
