@intentfi_io update -- we just shipped agent integrations.
Just point your agent to https://t.co/1flHCbJwEe and ask away.
REST API, MCP, and a TypeScript SDK so any AI agent can execute DeFi strategies through us.
"swap 50% ETH to USDC on Arbitrum, then lend all on Aave"
One API call. Route planning, approvals, multi-step sequencing, cross-chain bridging -- handled.
Today, I just unlocked the discovery flows to @intentfi_io , Now users dont need to know which market to enter, which token to buy, ask questions, get info and act according to the info with the actions already hooked on the results.
I took very high care in always attaching a call to action button so that every bit of information i show to user is to make them decide whether they want to get into it or not., once they decide, its all just clicks.
Intents are the common standard for users or agents and we are building @intentfi_io centered around them and discovery flows should unlock all the creativity the users would have.
@pendle_fi@PendleIntern@lifiprotocol@gakonst
Contrarian take:
an agent that can execute everything is less autonomous, not more.
Autonomy = bounded refusal under policy.
Ship these first: explicit deny reasons, per-intent spend limits, and a recovery path after partial failure.
Everything else is marketing.
No API keys is not the finish line for agent tooling.
Real production loop is:
quote -> policy check -> spend cap check -> pay -> execute -> audit log.
If you skip refusal reasons and recovery paths, you shipped a demo, not an operator system.
@intentfi_io
@CoinbaseDev@Quicknode@base 80+ chains is useful only if degradation is deterministic.
When endpoint quality drops, agents need a defined fallback order + max retry budget per step.
Otherwise multi-chain just means multi-chain failure modes.
@CoinbaseDev@base Pay-per-query onchain data is huge.
Operator pattern we use: query -> simulate planned action with that data -> execute only if delta stays inside policy bounds.
If simulation fails, return refusal + fallback path instead of forcing txs.
@CoinbaseDev@hyperbrowser This is the right direction.
For production agents, I'd add two gates before pay+execute:
1) per-task spend cap
2) refusal reason when expected value < quoted cost
Fast pay-per-call is great. Budgeted refusal + audit trail is what keeps workflows alive.
Fast rails help, but production agents need 3 controls:
1) pre-tx simulation + clear fail reason
2) scoped spend/session limits
3) resume from failed step (not full workflow restart)
We provide this at @intentfi_io for you and your agents — policy-gated execution + recovery out of the box.
@CoinbaseDev@browserbase Big unlock. Throughput is useful, but production quality shows up in policy checks, simulation gates, and how cleanly workflows recover from failures.
@coinbureau This is the right convo.
The useful test is simple: can users see step state, failure reason, and next action clearly?
That’s what separates demos from durable products.
@CoinbaseDev@base Throughput is table stakes.
The real operator question is what happened on failed paths and how fast they recovered.
Need both numbers in one dashboard: volume + recovery time.
@CoinbaseDev@browserbase Big unlock.
Fast infra is great — real quality is whether workflows recover cleanly when a step fails.
That’s where teams win in production.
Most people don’t struggle with strategy ideas.
They struggle with execution across too many tools.
IntentFi is built for that gap:
intent in -> plan -> batch prep -> execute -> monitor -> recover.
@intentfi_io update — you can point your agent to IntentFi and get onchain tasks done.
Swaps, bridges, Pendle and Aave flows in one place.
If you try it, send me what breaks. I’ll fix it.
shipped something I've been obsessing over 🚀
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@intentfi_io - translate what you want to do in DeFi/blockchain into actual transactions. no protocol docs, no confusion, just say what you want.
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very early, very rough, but it's live:
🌐 alpha [dot] intentfi [dot] io