My crypto research usually doesn\u2019t happen in one place. I might open a chart to look at price structure. Then check funding. Then open interest. Then liquidation levels. Then on-chain data. Then prediction markets.
Then go back to the chart because something I found changed the original\u00a0thesis.<\/p>\n
And somewhere around tab number ten, the actual question I started with becomes: TrueNorth<\/a> approaches this problem differently. Instead of making you search through the data first, it lets you start with the question. So this isn\u2019t going to be another: Let\u2019s look at what TrueNorth actually is, what it can do today, and just as importantly, what it can\u2019t\u00a0do.<\/p>\n TrueNorth describes itself as an AI trading intelligence platform<\/strong>. TrueNorth connects AI to real-time financial data and specialized analytical tools. That means instead of asking an LLM: That\u2019s a very different problem. The AI isn\u2019t useful because it can generate another opinion. Crypto traders don\u2019t suffer from a lack of data. We probably have too much of\u00a0it.<\/p>\n A serious market read can involve: Those signals often live in different places. But collecting them isn\u2019t even the hardest\u00a0part.<\/p>\n The harder question is: Instead of: the workflow becomes: That\u2019s the part I find interesting.<\/p>\n TrueNorth\u2019s current documentation separates its capabilities into two broad layers: These are useful when you already know what you\u2019re looking\u00a0for.<\/p>\n For example: What\u2019s BTC funding right now? The documented toolset includes:<\/p>\n technical indicators such as RSI, MACD, support\/resistance and volume analysis;derivatives intelligence including funding rates, open interest and liquidation clusters;on-chain metrics such as TVL, DEX volume and protocol activity;market discovery and performance rankings;token economics and unlock schedules;prediction-market data;KOL tracking;DeFi analytics.<\/p>\n Think of this as the data retrieval layer. But the second layer is where things get more interesting.<\/p>\n Instead of requesting one metric, you can ask TrueNorth to investigate an entire\u00a0problem.<\/p>\n For example: Analyze Bitcoin. So instead of receiving a giant paragraph saying: \u201cETH looks bullish, although traders should remain cautious due to volatility\u2026\u201d<\/p>\n you can get something structured around: and, crucially: Thanks, AI. That\u2019s a little more useful.\u00a0\ud83d\ude02<\/p>\n One of the areas I\u2019ve found particularly useful is derivatives positioning.<\/p>\n TrueNorth can\u00a0combine:<\/p>\n funding rates;open interest and its\u00a0changes;liquidation distribution;price structure;<\/p>\n and use them to reason about positioning, crowded trades, potential squeezes and stop-hunt risk. Its own prompt guide specifically includes workflows for liquidation heatmaps, derivatives positioning, short-squeeze setups and stop-hunt analysis.<\/p>\n That allows for questions that can\u2019t really be answered from a candlestick chart\u00a0alone.<\/p>\n For example: Which major crypto asset currently has the strongest positioning asymmetry? It can investigate: Suddenly you\u2019re analyzing market positioning, not just\u00a0price.<\/p>\n This was obviously one of the first things I wanted to test. A typical output can include: But there\u2019s something much more important than getting a beautifully formatted setup. Recently, I asked TrueNorth to scan the market and choose the single trade it considered worth taking. I think this example is more important than showing you a screenshot of a +100% leveraged trade.<\/p>\n Because it demonstrates something that tends to disappear from conversations about AI trading: An AI can identify a reasonable asymmetry. The thesis can make sense. The risk\/reward can be attractive. And the next trade can still lose. That\u2019s trading. Interestingly, I\u2019ve also asked TrueNorth to find me a position and gotten: Not: \u201cHere\u2019s the least terrible setup I could find because you asked me for something.\u201d<\/p>\n Just: No\u00a0trade.<\/p>\n In one recent scan, the strongest candidates were already extended near their highs. This is another thing I\u2019ve been experimenting with. There\u2019s a huge difference between: \u201cBuy at\u00a0$100.\u201d<\/p>\n and: \u201cIf price breaks $100, closes above it, holds the level on a retest, and positioning confirms the move, then consider entering.\u201d<\/p>\n Price touching a level isn\u2019t automatically confirmation. That\u2019s the difference between: \u201cBTC is at X.\u201d For me, that\u2019s much more\u00a0useful.<\/p>\n There\u2019s another difference from a completely blank-slate chatbot: contextual memory.<\/p>\n TrueNorth\u2019s current documentation describes memory across the trading workflow and a system designed to stay engaged across plan -> execute -> iterate, rather than treating every prompt as an isolated interaction.<\/p>\n That becomes useful when the question isn\u2019t: What does BTC look like? Markets evolve. This might actually be my favorite way to use TrueNorth.<\/p>\n Not: What should I buy? I\u2019ve experimented with giving one agent a trading idea and then opening a fresh session whose only job was to argue against\u00a0it.<\/p>\n Then I used another agent to judge the two arguments.<\/p>\n The goal wasn\u2019t to create an AI debate\u00a0club.<\/p>\n It was to fight confirmation bias<\/strong>.<\/p>\n Because once I\u2019ve decided I like a trade, I naturally start looking for evidence that supports\u00a0it.<\/p>\n So instead I can ask: That\u2019s a much more interesting use of AI than asking it to predict tomorrow\u2019s candle.<\/p>\n Here\u2019s another experiment I ran. The easy crypto-Twitter interpretation would be: That\u2019s exactly the kind of job I want a research assistant doing.<\/p>\n TrueNorth isn\u2019t limited to candlestick analysis. You can investigate protocols. Compare market narratives. Look at relative performance. Examine prediction-market probabilities. Research token unlocks. Or combine several perspectives into one\u00a0thesis.<\/p>\n Another interesting part of TrueNorth is that its intelligence isn\u2019t necessarily confined to the main interface.<\/p>\n TrueNorth provides an MCP implementation that exposes the same broad idea of specialized tools and larger research workflows to compatible AI environments.<\/p>\n There\u2019s also a public TrueNorth CLI. Instead of maintaining a fixed list of tool-specific commands, the CLI discovers available tool names and schemas from TrueNorth\u2019s API at runtime. In other words, TrueNorth is increasingly interesting not only as an interface for traders, but as an intelligence layer that can be used in other AI workflows. This section matters as much as the feature\u00a0list.<\/p>\n TrueNorth is not: a money printer. And it shouldn\u2019t replace your own risk management. The useful question isn\u2019t: Can TrueNorth predict every trade correctly? After experimenting with it, I rarely use TrueNorth as a simple: Instead, I use it for questions like: That last part is important. The goal isn\u2019t to outsource the decision. A general AI model can explain funding. It can teach you what open interest means. It can explain RSI. It can help you build a trading framework. Those things are\u00a0useful.<\/p>\n But there\u2019s a fundamental difference between explaining: and analyzing: what current funding + OI + liquidations + price structure imply together.<\/p>\n TrueNorth is trying to operate in that second layer. Not: AI knows finance. The most interesting thing about TrueNorth isn\u2019t that it can tell me: LONG. It\u2019s that I can ask a market question and force the answer through multiple layers of evidence. Ask what would invalidate it. Or simply decide I disagree.<\/p>\n That\u2019s a much healthier relationship with trading AI than: The more useful model is: AI expands what one trader can investigate. For me, that\u2019s where TrueNorth becomes interesting. Not as an AI that trades instead of me. What Is TrueNorth? A Practical Guide to AI-Powered Crypto Research and Trading<\/a> was originally published in Coinmonks<\/a> on Medium, where people are continuing the conversation by highlighting and responding to this story.<\/p>","protected":false},"excerpt":{"rendered":" What it does, what data it can analyze, how its trading intelligence works and where it actually fits into a trader\u2019s\u00a0workflow My crypto research usually doesn\u2019t happen in one place. I might open a chart to look at price structure. Then check funding. Then open interest. Then liquidation levels. Then on-chain data. Then prediction markets.Then […]<\/p>\n","protected":false},"author":0,"featured_media":219194,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[],"class_list":["post-219193","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-interesting"],"_links":{"self":[{"href":"https:\/\/mycryptomania.com\/index.php?rest_route=\/wp\/v2\/posts\/219193"}],"collection":[{"href":"https:\/\/mycryptomania.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mycryptomania.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/mycryptomania.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=219193"}],"version-history":[{"count":0,"href":"https:\/\/mycryptomania.com\/index.php?rest_route=\/wp\/v2\/posts\/219193\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/mycryptomania.com\/index.php?rest_route=\/wp\/v2\/media\/219194"}],"wp:attachment":[{"href":"https:\/\/mycryptomania.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=219193"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mycryptomania.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=219193"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mycryptomania.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=219193"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
Wait\u2026 what was I trying to figure out\u00a0again?<\/strong><\/p>\n
Then the system goes looking for the data needed to answer it.
I\u2019ve been testing TrueNorth for a while now, from simple market questions to multi-agent experiments, news analysis and actual trading\u00a0setups.<\/p>\n
\u201cAI will change trading forever.\u201d<\/p>\nWhat Is TrueNorth?<\/h3>\n
A simple way to think about it is somewhere between an AI research assistant and a trading terminal.
But the important distinction is that this isn\u2019t just a chatbot that happens to know something about\u00a0crypto.<\/p>\n
Its current documentation lists 30+ real-time data sources, including CoinGecko, DeFiLlama, Hyperliquid and Polymarket, among others.
And while most of my own testing has focused on crypto, TrueNorth\u2019s current scope goes beyond it: its market scanners cover crypto, equities, prediction markets and commodities.<\/p>\n
Is SOL bullish?
you can ask something much closer to:
Where are the largest liquidation clusters around SOL right now, what is funding doing, how is open interest changing, and does positioning support the current price\u00a0trend?<\/p>\n
It\u2019s useful when it can assemble the evidence behind that\u00a0opinion.<\/p>\nFrom Ten Tabs to One\u00a0Question<\/h3>\n
Price -> technical structure -> volume -> funding -> open interest -> liquidations -> on-chain activity -> relative strength -> prediction markets ->\u00a0news.<\/p>\n
What does all of this mean together?
Imagine BTC is rising.
Bullish?
Maybe.
But what if open interest is exploding at the same time? What if funding is extremely positive? What if a large concentration of long liquidations sits directly below price?
Suddenly the exact same bullish chart has a very different risk profile.
TrueNorth\u2019s approach is to put an intelligence layer on top of these datasets.<\/p>\n
find data ->compare data ->construct thesis<\/p>\n
ask question -> retrieve relevant data -> synthesize it -> review the\u00a0thesis.<\/p>\nTwo Layers of Intelligence<\/h3>\n
Specialized Tools and Expert Playbooks.
The distinction matters.<\/p>\nLayer 1: Specialized Tools<\/h4>\n
or: Show me ETH open interest.
or: What\u2019s SOL\u2019s\u00a0RSI?<\/p>\nLayer 2: Expert Playbooks<\/h4>\n
or: Give me a trading setup for ETH.
The documented Playbooks can orchestrate multiple data sources and turn them into a structured analysis. Current examples include Comprehensive Analysis, Technical Trading Setup and Tokenized Stock Research.<\/p>\n
Bias
Entry
Stop
Invalidation
Targets
Risk\/reward<\/p>\n
Why?<\/p>\nDerivatives Are Where It Gets Interesting<\/h3>\n
Now the AI isn\u2019t simply looking for the coin that went up the\u00a0most.<\/p>\n
Are longs crowded?
Are shorts crowded?
Is OI rising with price?
Is funding becoming expensive?
Where are liquidations concentrated?
Is the market sitting underneath a wall of potential forced short buying?
Or above a potential long-liquidation cascade?<\/p>\nBut Can It Actually Find\u00a0Trades?<\/h3>\n
So instead of giving TrueNorth an asset, I started asking it to scan the market itself and choose the best setup it could\u00a0find.<\/p>\n
Asset
Direction
Entry condition
Entry
Stop
Targets
Risk\/reward
Invalidation<\/p>\n
Does the trade actually work?
Here\u2019s a real\u00a0example.<\/p>\nA Real Trade: When TrueNorth Was\u00a0Wrong<\/h3>\n
It selected an XRP long breakout. The thesis looked reasonable. Trend was strong. Funding wasn\u2019t particularly crowded. Open interest wasn\u2019t extreme.
There were short-liquidation levels above price that could potentially fuel a squeeze.
And the proposed trade offered roughly 2.3:1 risk\/reward to its first target.
I took it.
The breakout triggered.
And then?
Stop-loss.
The trade\u00a0failed.<\/p>\n
Good analysis does not guarantee a profitable outcome.<\/p>\n
TrueNorth isn\u2019t a crystal ball. And I wouldn\u2019t trust any trading AI that pretended to be\u00a0one.<\/p>\nSometimes It Refuses to Give Me a\u00a0Trade<\/h3>\n
NO\u00a0TRADE.<\/p>\n
Buying meant chasing momentum. Shorting meant fighting a strong trend. And the available stops and targets produced poor trade geometry. So the conclusion was simply to wait. I like this more than I expected.
Because an AI that is implicitly rewarded for always producing an answer can be dangerous in trading.
Sometimes the correct decision is: do\u00a0nothing.<\/p>\nEntry Price Isn\u2019t the Same as Entry Confirmation<\/h3>\n
Suppose an asset has resistance at\u00a0$100.<\/p>\n
Depending on the setup, TrueNorth can reason about things like candle closes, reclaims, retests, volume or derivatives positioning before treating a thesis as actionable.<\/p>\n
and: \u201cIf X happens under Y conditions, the thesis becomes actionable.\u201d<\/p>\nTrueNorth Can Remember the Trading\u00a0Context<\/h3>\n
but: What changed since the thesis we built\u00a0earlier?<\/p>\n
The useful context often isn\u2019t just the current price.
It\u2019s what changed relative to the plan you were already watching.<\/p>\nI Don\u2019t Only Ask It What to\u00a0Buy<\/h3>\n
But: Destroy my\u00a0thesis.<\/p>\n
What am I missing?
What\u2019s the strongest argument against this trade?
What data would invalidate my thesis?
Is this actually a good setup, or am I interpreting the data the way I\u00a0want?<\/p>\nCan AI Tell Whether a News Story Actually\u00a0Matters?<\/h3>\n
Michael Saylor announced that Strategy had increased its USD Reserve to $5.10 billion, established additional USD cash, and repurchased STRC.<\/p>\n
Saylor + billions = bullish BTC.
So I gave the announcement to TrueNorth and asked it to classify the actual signal.
Its conclusion was essentially:
Balance-sheet signal, not a BTC signal.
The reasoning was simple but important.
Available capital and actual BTC demand aren\u2019t the same thing.
The announcement demonstrated potential buying capacity.
It didn\u2019t announce that those billions had just been deployed into Bitcoin.
That doesn\u2019t automatically make the news bearish.
It simply separates: what the headline sounds like
from: what actually\u00a0changed.<\/p>\nPrediction Markets, DeFi and On-Chain\u00a0Research<\/h3>\n
Its documented toolset also includes prediction markets, DeFi analytics and on-chain metrics such as TVL, DEX volume and protocol activity. It also covers market discovery, token economics and other crypto-specific research categories.
So the question space can be much broader than: Long or short\u00a0BTC?<\/p>\nTrueNorth Beyond the App: MCP and\u00a0CLI<\/h3>\n
And its architecture is interesting.<\/p>\n
That means the live API remains the source of truth as the available analytical tools evolve. The CLI can discover tools, call individual tools and batch independent calls.<\/p>\n
That\u2019s a very different direction from simply building another charting app with a chatbot attached.<\/p>\nWhat TrueNorth Is\u00a0NOT<\/h3>\n
It\u2019s not: an\u00a0oracle.<\/p>\n
It can produce a trade that loses. It can analyze a market where the correct answer is NO TRADE. And an analysis that made sense earlier can become invalid when the underlying data changes.
That\u2019s not a flaw unique to AI. That\u2019s what markets\u00a0are.<\/p>\n
Obviously not.
The useful question is: Can it help me make better-informed decisions with more relevant context and fewer blind spots?
That\u2019s the standard I\u2019m interested in\u00a0testing.<\/p>\nHow I Actually Use TrueNorth<\/h3>\n
\u201cTell me what to\u00a0buy.\u201d<\/p>\n
Compare these assets and tell me where positioning is most asymmetric.
Find the strongest argument against my trade.
Is this breakout supported by OI and funding, or am I chasing price?
What would have to happen for this thesis to become invalid?
Does this news actually change the market, or does it just sound bullish?
Find one trade worth taking, and say NO TRADE if none\u00a0exists.<\/p>\n
It\u2019s to improve the information going into\u00a0it.<\/p>\nTrueNorth vs. a General AI\u00a0Chatbot<\/h3>\n
what funding\u00a0means<\/p>\n
Its official positioning emphasizes real-time financial feeds, structured trading outputs and a workflow built specifically for traders rather than generic conversation.
That\u2019s the real distinction.<\/p>\n
But: AI has financial tools.<\/p>\nFinal Thoughts<\/h3>\n
Or:\u00a0SHORT.<\/p>\n
Price.
Structure.
Funding.
Open interest.
Liquidations.
On-chain data.
Prediction markets.
Whatever is actually relevant to the question.
Then I can challenge the conclusion.
Ask for the bearish\u00a0case.<\/p>\n
\u201cAI said buy, so I bought.\u201d
I don\u2019t think the interesting future of trading is human vs. AI.
<\/strong>And I don\u2019t think it\u2019s AI replaces\u00a0trader<\/strong>.<\/p>\n
Humans are still responsible for judgment.
For risk. For execution. And for knowing when not to press the\u00a0button.<\/p>\n
As an AI that gives me more context before I decide to\u00a0trade.<\/p>\n