As someone who's spent a fair amount of time in Web3.
I can confidently tell you that the complexity of BLOCKCHAIN tasks, is a major obstacle for most.
Even for people who grasp the core concepts.
I mean, we've all had this experience of:
Staring at a liquidity pool, trying to figure out if a certain new token listing is worth the risk.
OR
Wanting to keep an eye on a wallet without having to manually check Etherscan every five minutes.
The struggle is very real.
You'll definitely wish you could just bypass such obstacles entirely...
Like simply talk to a dApp and tell it what you want to do.
Guess what,
I've had my eyes on
@graphlinq_proto and I got what you and I have been searching for.
Yes it's been a genuine change (for good) in how I'll approach on-chain tasks now and in the future.
——
GraphLinq’s vision is to make powerful blockchain tools accessible to everyone.
Think of GraphLinq as a platform that empowers both experienced developers & non experienced developers.
By providing systems to automate complex workflows
Using natural language prompts or no-code/drag-and-drop frameworks.
It eradicates the need to wrestle with scripts or complex syntax.
You just tell the system what you need, and it builds it for YOU!
——
Instead of building complex graphs with logical blocks
You can now achieve the same results with a single, conversational prompt.
For instance...
A couple friends of mine always wanted to track the movements of a known whale on the Aave protocol to see how they manage their health factor.
Aave's health factor is a critical metric for borrowers, indicating the safety of their loan.
If the health factor drops too low, their collateral gets liquidated.
——
Manually tracking this is a chore.
With GraphAI, one can simply type in:
“Monitor the health factor of wallet 0xabc... on Aave and send me a Telegram alert if it drops below 1.1.”
The AI assistant instantly generates a working automation.
That connects to the Aave subgraph, pulls the specific wallet's data, set a trigger condition, and integrate with the Telegram API.
What would take hours of learning the right blocks
and testing the connections can be done in seconds.
——
Another area of GraphAI is automated trading bots.
An article on the GraphLinq blog details this.
But experiencing it firsthand is something else entirely.
The prompts are remarkably straightforward.
For a simple DEX arbitrage bot, you could use a prompt like:
“Build a cross-chain arbitrage bot that monitors liquidity pools on Uniswap and PancakeSwap for ETH/USDT and alerts me on Telegram when an arbitrage opportunity of more than 0.5% appears, accounting for gas and slippage.”
The bot was created from this single instruction
And within a few minutes, it was already live.
The engine’s ability to process real-time data streams and make on-the-fly decisions.
Based on predefined conditions is what makes GraphLinq so powerful.
——
The fact that the GraphLinq ecosystem
is built on a custom blockchain called GraphLinq Chain which is
An AI-powered, EVM-compatible Proof-of-Authority (PoA) Layer 1.
Means automations will run with speed, security, low fees and high reliability.
Which is a key consideration for constant monitoring tasks.
——
Of course in every moving force, there's always a kind of fuel.
In GraphLinq's case it's the
$GLQ token, which acts as more than just a currency.
It's what powers every transaction
Every graph execution, and every prompt-powered AI interaction...
[
#GraphAI #DefAI #GraphLinqChain $GLQ]