Learn how to use AI to find liquidity-pool opportunities, investigate the risks, and choose a range with a clear reason behind it. Set up your own research assistant and practice the process with me over two live evenings.
Two live evenings · October 7–8
7:00–8:15 PM Eastern
Both session recordings included. Funded wallet optional.
“I’ve taught hundreds of people liquidity providing. I’ll show you how to ask better questions, investigate a pool with AI, and understand the evidence behind your next move.”
After teaching hundreds of people liquidity providing, I kept hearing the same question: “Tyler, is this a good pool?”
People understood the mechanics. Some had already opened positions. But a new pool brought the same questions: Which numbers matter? What range makes sense? What would make me pass or proceed?
That's what we'll practice together: a repeatable way to find opportunities, check the risks, and make a decision you can explain.
I’m not teaching you to ask AI what to buy. I’m teaching you what questions to ask, what information matters, and how to use AI to compress the research work underneath your own judgment.
Illustrative example
Illustrative examples.
Example search scope: Ethereum, Base, Arbitrum, Optimism and Polygon.
I have USDC I’d like to earn yield on. Find some pools across these five networks.
I’ll compare pools containing USDC by recent fee activity, trading volume, and liquidity. Should I include pairs with other stablecoins only?
Yes. Show me three candidates.
Here’s a shortlist, with each pool’s network, paired token, recent fees, and available liquidity. Which would you like to investigate?
Sample shortlist, using fictional 7-day activity:
Pool A · Base · USDC/USDT: $2,400 in pool fees, $8M in volume and $3.2M in liquidity.
Pool B · Arbitrum · USDC/DAI: $1,800 in pool fees, $6M in volume and $2.8M in liquidity.
Pool C · Polygon · USDC/USDT: $1,200 in pool fees, $4M in volume and $1.9M in liquidity.
These pools and figures are fictional. Pool fees are not position profit.
Sample pools A–C · Questions, evidence and missing information.
Run the Go/ No-Go framework against these pools.
I’ll gather the information behind the framework: what drives the yield, token risks, liquidity, fee consistency, range choices, and management requirements.
Show me what we know—and what we still need to find out.
Here’s the research organized by question. I’ve highlighted missing information and areas that deserve a closer look.
What drives the yield? Sample finding: trading fees plus token incentives.
What are the token risks? Needs research: issuer, backing and bridge exposure.
How much liquidity is available? Sample finding: $1.9M–$3.2M across the three pools.
Are fees consistent? Needs research: the 30-day trend and unusual activity.
Which range choices fit the evidence? Needs research: compare ranges against price history.
What management would this require? Needs research: review frequency and adjustment costs.
This framework gathers information. It does not assign a score or investment verdict.
Sample ETH/USDC pool · Fictional 30-day price history.
Help me design a range for this ETH/USDC pool.
In this illustrative 30-day history, price moves between $1,800 and $2,200. Would you like to compare narrow, medium, and wide ranges against that history?
Yes. Compare estimated fees and time in range.
Here’s the sample comparison, including when price moves outside each range. Which tradeoff would you like to explore?
For a fictional $1,000 position over 30 days:
Narrow range ($1,850–$2,150): $120 in estimated fees, with price inside the range 70% of the time.
Medium range ($1,700–$2,300): $80 in estimated fees, with price inside the range 100% of the time.
Wide range ($1,500–$2,500): $45 in estimated fees, with price inside the range 100% of the time.
These figures are invented, not a measured backtest. Fees exclude costs and changes in asset value; they are not total profit.
Sample pool · Fictional annualized rates and activity.
This pool shows a really high yield. What’s driving it?
I’ll examine how much comes from trading fees, how much comes from incentives, and whether recent activity is unusual.
Compare the last seven days with the previous month.
Here’s the sample comparison. I’ve highlighted changes in volume, liquidity, and fee activity so you can see what’s behind the headline number.
The fictional headline rate is 28% annualized: 8 percentage points from fees and 20 from incentives.
Sample daily volume: $2.2M over the last 7 days, compared with $1.23M over the prior 30 days.
Sample liquidity: $3M over the last 7 days, compared with $4.5M over the prior 30 days.
Sample daily pool fees: $660 over the last 7 days, compared with $370 over the prior 30 days.
These are fictional annualized estimates, not profit. Incentives may expire, and recent activity may not persist.
Sample ETH/USDC position · USDC per ETH · Range $1,850–$2,150.
What happens if price moves outside this range?
Let’s examine both directions: which token the position would hold, when trading fees would stop, and what choices you’d have afterward.
Show me what I should consider before adjusting it.
We’ll look at your current holdings, adjustment costs, recent price behavior, and whether the original reason for choosing the range still holds.
Below the range: the position principal would be ETH, with no new trading fees.
Inside the range: the position would hold both tokens, earning trading fees as swaps occur.
Above the range: the position principal would be USDC, with no new trading fees.
Before adjusting, consider your holdings, transaction costs, recent price behavior and original reason for choosing the range. Previously earned fees remain separate.
We are not spending two nights re-teaching LP 101. We’ll get everyone aligned on the mechanics that affect decisions, then move into the research, range selection, judgment, and execution layer.
Every component exists because it removes a point where I see people get stuck.
Build the workflow with me, then use it on real examples.
Configure the tools that compress the manual research burden.
The copy-and-paste questions I use to investigate opportunities.
Turn information into a structured decision instead of a gut call.
See how to pressure-test range ideas against historical behavior.
Watch the research and decision process become an actual position setup.
Each recording is available by the end of that training session, so you can revisit the lessons as you put them into practice.
Get operationally ready if you choose to follow along with your own wallet.
A sneak peek into the world of tokenized Real World Assets (RWA). Where and how you can buy them.
Stay after the main session and work through your questions live.
Attend both live sessions. If the training isn’t worth $197 to you, request a full refund.
Email [email protected] from your purchase email by October 9, 2026 at 11:59 PM Eastern to request your refund.
Reserve My Seat →No. We will quickly refresh the LP mechanics that directly affect decisions, but the live workshop is centered on the layer after the basics: finding candidates, researching them, pressure-testing range ideas, making a GO / NO GO call, and putting the process into practice.
You can attend without having opened an LP position. We will refresh the mechanics used in the live examples, then focus on finding pools, checking the risks, and comparing ranges. You can watch without funding a wallet. Both session recordings are included, with each available by the end of that training session.
No. Following along with your own funded wallet is optional. You can watch the Uniswap walkthrough without putting money into a position.
No. The AI is a research layer. It helps retrieve, compare and organize information and pressure-test questions. The judgment stays with you. The workshop is specifically designed around making an explainable decision rather than blindly following an AI output.
We will set up an LP-specialized AI research workflow using free tools, then use it with the research prompts and decision framework taught in the workshop.
Yes. Your registration includes two recordings, one for each training session. Each recording will be available by the end of that session. The live workshop also includes optional Thursday Q&A.
Attend the two live sessions. If you do not think the training was worth the $197, email [email protected] from your purchase email by October 9, 2026 at 11:59 PM Eastern and request a full refund.
As with any investment vehicle, liquidity providing carries risks. These include market risk, token risk, smart-contract risk, loss relative to holding the underlying assets, range-related tradeoffs, and other risks. This training is educational and does not guarantee profits or remove investment risk.
Find the opportunity. Test the assumptions. Decide with a reason.
Registration closes in
Registration is closed.
Registration closes October 7 at 6:45 PM Eastern.
Ranged Pro