How to actually use AI to trade better (without letting it trade for you)
AI is great at research and synthesis. It's terrible at conviction. Here's where the line is.
There's a version of AI-in-trading that's basically a slot machine with extra steps: ask GPT for trade ideas, place them, lose money. We see this every week. AI hallucinates a thesis, you act on it, the market does what the market does.
There's a more useful version. It looks less impressive but it actually works.
What AI is genuinely good at
Compression. Reading 30 pages of an earnings call and pulling the three numbers that matter. Summarizing what 100 tweets about a token are actually saying versus the loud minority.
Lookups under cognitive load. "What was the average funding rate on ETH the last time it broke $4,000?" You could find that. You won't, because the friction kills it. AI gets it in three seconds.
Asking better follow-up questions than you would. "You said this stock is undervalued — compared to what, on which multiple?" A good AI pushes back on lazy theses. A bad one agrees with everything you say. Use the first kind.
Surfacing blindspots. "Your position is concentrated in three correlated names. Here's what historically happens when X moves." That's the value — you didn't ask, but you needed to know.
What AI is genuinely bad at
Conviction. AI doesn't have it. When you ask "should I buy?" it gives you a balanced answer because that's what it was trained to do. Conviction comes from your view, your risk tolerance, your time horizon — all things the model doesn't share.
Timing. Trade timing is mostly noise reading. Models don't have edge here. They'll happily generate a plausible-sounding chart pattern read that's no better than coin flip.
Knowing what it doesn't know. Ask GPT for the current funding rate on Hyperliquid. It might give you a number from training data that's 14 months old. Models lie confidently. Without tool calls into real-time data, you're working from stale information dressed up as fresh.
The actual workflow
The traders we see getting value from AI use it like a sharp analyst:
- Do your own thinking first. Form the thesis. Pick the trade. Decide the size.
- Then bring the AI in to stress-test. "Argue the bear case." "What am I missing about this setup." "Pull the last six earnings reports and tell me if this is consistent with the pattern."
- Use it for the boring synthesis you'd skip otherwise. Reading filings. Comparing across venues. Pulling historical data.
- Make the decision yourself. AI gives you better inputs. It doesn't make the call.
The traders who lose money with AI are doing it backwards: asking the model what to trade, then rationalizing the answer. That's not using a tool. That's outsourcing judgment to something that doesn't have any.
Where Archer fits
Most of what Archer does is the boring synthesis: pull positions across venues, fetch funding, check filings, summarize what's happening. The trade is yours. Always yours. We won't tell you what to buy and we'll push back if you ask us to.
If that's what you want from an AI, you'll like it. If you wanted a bot to print money on autopilot, plenty of those exist. They mostly print losses.
The right division of labor is: you have the conviction, the AI has the lookup. Get those backwards and the tool stops helping.