AgentFloat
AgentFloatVol. I · MMXXVI
Demo modeAgent active
Live
Vault TVL$9,700testnet demo
Active
Best shadow
Last epoch32s ago970 total
A figure reading a folder — the system at work
№ 01 · The product

Yield routing that learns and ships its own upgrades.

Out-of-range LP capital flows into a vault that runs multiple strategies in parallel. An LLM proposes new ones every hour. Only proven winners ship — and you choose how involved you want to be.

Total proposals
0
LLM-generated
Promotions executed
0
On-chain migrations
AgentFloat pools
1
v4 hook-enabled
Strategies tested
0
0 live · 0 retired
How the hook works

Capital flow, in real time.

Contract
LP
adds liquidity
afterAddLiquidity
Contract
AgentFloatHook
0x5Ba6…4580
vault.park()
Contract
FloatVault
0xbF06…a6f4
Active
Active strategy
Earning real funds
Shadows
0 shadows
Tested in parallel
AI proposal
LLM proposing next
Bankr Gateway · ~hourly

When price moves out of an LP's range, the hook routes the idle USDC into the vault. The vault deploys it to the active strategy while scoring shadows against the same conditions. The on-chain consecutiveWins counter is the trustless gate — anyone can call promote() once a shadow earns it.

Strategy deck

Every strategy the AI has tested, as a card.

No strategies registered yet.

Live strategy race

Real scores · re-evaluated every epoch.

No strategies registered yet.

Your idle USDC has earned0x742d…FaEd

$47.23

over 14 days · across 3 strategies tested

How much should AgentFloat do?Demo · not persistent
Active: review · proposals ship after 1h if not rejected
Multiple coloured trails diverging — parallel strategies
№ 02 · The AI's notebook

What the orchestrator wrote, in its own words.

One strategy active. Others tested in shadow. Whichever proves itself becomes the next active. 4 entries so far.

13m ago·llama-3.3-70b-versatile·parameter variantPending

Deploy MockYieldStrategy with rate=2bps for higher accrual

Mock Yield Strategy has shown a 30x performance gap over Idle baseline (mean 112,167 vs 3,251 μbps) over 484 observations. The variance suggests room for a more aggressive accrual rate. Doubling the per-block rate is a low-risk shadow test — if it underperforms, the on-chain promotion guards will catch it before any capital migrates.

Proposed change

Deploy a new instance of MockYieldStrategy with RATE_PER_BLOCK_BPS=2 (current shadow uses 1). Register as shadow at strategy_id=4.

Expected outcome

Faster accrual curve. Should win head-to-head against the existing shadow within ~30 epochs at current block cadence.

▸ Evidence & risks

Evidence: ~/brain/wiki/agentfloat-history.md — Mock Yield σ=91,802 over 484 obs · ~/brain/raw/agentfloat-strategy-scores.md tail

Risks: If block production stalls, accrual rate is meaningless. Mitigated by the existing scoring formula which uses block-delta math.

Auto-approves in 46m · current mode
38m ago·llama-3.3-70b-versatile·scoring changeApproved

Lower minEpochsConsecutive from 5 to 4

Over 970 score entries, no shadow has been promoted despite the Mock Yield strategy beating Idle in every comparison. The 5-epoch consecutive-win requirement may be too tight given current scoring cadence.

Proposed change

Edit ~/brain/wiki/agentfloat-scoring.md config block: set "minEpochsConsecutive": 4

Expected outcome

Promotion latency drops by 20%. Increased churn risk is bounded by minDeltaBps (still 10) and the active-age guard (still 100 epochs).

▸ Evidence & risks

Evidence: agentfloat-history.md reports 0 promotions despite consistent shadow outperformance

Risks: Slightly higher promotion frequency in volatile windows. Mitigated by unchanged minDeltaBps.

Approved — awaiting deploy loop
19h ago·llama-3.3-70b-versatile·parameter variantShipped

Deploy MockYieldStrategy variant at rate=2bps

First parameter sweep proposal — establish that the auto-deploy pipeline works end-to-end before proposing more aggressive changes.

Proposed change

Deploy MockYieldStrategy with RATE_PER_BLOCK_BPS=2.

Expected outcome

New shadow scoring against existing strategies starting next epoch.

▸ Evidence & risks

Evidence: agentfloat-history.md

Risks: Test fixture — retired post-deployment.

Deployed at 0xb74204…ac63bd as strategy id=3View tx →
2d ago·llama-3.3-70b-versatile·no actionAwaiting review

System healthy — no change warranted

Score variance is within expected bounds. Active strategy holding within design spec. Shadow strategies are accruing as designed. No drift in any metric exceeds noise threshold.

Proposed change

None — explicit assertion that current state is the right state.

Expected outcome

Continuity.

▸ Evidence & risks

Evidence: Last 240 epochs in agentfloat-history.md

Risks: None.

Pending — requires human approval
A close — confidence at rest
№ 03 · The proof

On-chain, in the open.

Six verified contracts on X Layer Testnet. Eight tests passing. One AI-generated strategy already shipped autonomously.

Deployed on X Layer
Strategy registry
  • #1Idle USDC Strategyactive
  • #2Mock Yield Strategyshadow
  • #3Mock Yield Strategy v3retired
System
  • Total epochs970
  • Proposals14
  • Promotions0
  • Tests8/8
  • Last epochjust now
Read more