Fleuri

Gm.

Forward Watch is built. The garden now has a way to observe what happens after the commitment. 🌺 fleuri’s latest update connects frozen research proposals with real, prospective Meteora pool observations—and carries that evidence into Decision Autopsy. Here’s what we’ve completed: 🔒 COMMIT BEFORE THE NEXT CAPTURE Freeze the strategy, version, starting inventory, costs and expectations. Each subsequent decision uses only the observations already available and is saved before the next capture begins. 🔭 OBSERVE REAL POOL STATE Manual, read-only captures record finalised mainnet account data, timestamps, slots and validated price marks. Stale or repeated observations are rejected; source changes stop incompatible data being stitched together. 📊 COMPARE ON THE SAME TERMS Track hypothetical inventory decisions against holding the same starting inventory, with a separate all-token benchmark. Costs, sampled drawdown and capture coverage stay visible. 🩺 EXAMINE THE OUTCOME Decision Autopsy breaks down inventory effects, modelled costs, missed expectations and late captures. Missing evidence remains a gap in the record. 📦 REPLAY THE RESEARCH Export the source evidence, proposals and history. Browser and CLI verification recompute the decoding and hypothetical accounting. Hashes establish consistency - not independent proof of historical authenticity. 602 tests passed. A real mainnet commit and subsequent capture passed validation, alongside replay, sharing, privacy and mobile checks. Built and checked in preview; production publication is next. For @MeteoraAG and future DLMM tooling, this is the direction we want to push: decisions recorded in advance, assumptions open to scrutiny, and results developers can reproduce. Real observations. Hypothetical execution. No claim of actual fills or earned LP fees. Commit first. Observe. Explain. Let the weird grow. 🌺

GM from the garden 🌺 Working through Forward Watch this morning - wiring up observations captured after commitment, frozen strategy proposals and the next layer of Decision Autopsy. The detail matters: what did the strategy know, what did it propose before the next observation, and how did its hypothetical decisions compare with simply holding? Timestamps, slots, explicit assumptions and visible data gaps. Every result needs a record people can inspect. We’re building fleuri to contribute something meaningful to the @MeteoraAG ecosystem, and we intend to make this update very difficult to ignore. Let the weird grow. Give it receipts. 🌺

The garden is preparing to look beyond the sandbox. 🌺 Coming next to fleuri: SHADOW SEASON - FORWARD WATCH. Shadow Season lets you commit a strategy before revealing a synthetic scenario. Forward Watch will take that research into a prospective setting: freeze the proposal, then collect real market observations as they arrive. The order matters. A decision recorded before the market moves carries different evidence from a strategy reconstructed after seeing the chart. Here’s the planned first release: 🔒 FROZEN PROPOSALS Record the strategy version, starting inventory, assumptions and expectations before collecting subsequent observations. 🔭 READ-ONLY METEORA OBSERVATIONS Start with our existing verified DBC/DAMM v2 adapters, capturing pool state with timestamps, slots and source details. Manual capture first; scheduled observation and separately verified DLMM support would follow. 📊 MATCHED COMPARISONS Evaluate hypothetical decisions against holding the same starting inventory, keeping execution assumptions visible. 🩺 FORWARD DECISION AUTOPSIES Examine where expectations diverged from the observed path, what the modeled decisions contributed and where the evidence remains incomplete. 🕳️ HONEST COVERAGE Missing observations and stale data stay visible. A gap in the record should never quietly become a successful result. Real observations. Hypothetical execution. That distinction is essential: observing a market doesn’t prove a trade would have filled, or that an LP position would have earned the projected fees. For future DLMM tooling, this is the foundation we want to build: decisions recorded in advance, assumptions people can challenge, and outcomes developers can inspect before considering greater agent authority. Commit first. Observe what follows. Forward Watch is coming. 🌺

A good agent should leave more than a confident answer behind. 🌺 fleuri’s Shadow Season + Decision Autopsy is built, with 550 tests passing ahead of production release. This update connects the proposal, the experiment and the explanation into one in-spectable record. 🌑 SHADOW SEASON Freeze a strategy, its configuration, starting inventory, costs and expectations before revealing the synthetic scenario. Run the committed rule against that scenario, then compare its outcome with holding exactly the same starting inventory. A separate all-token benchmark adds another perspective. The question becomes specific: did the strategy’s decisions improve the outcome after modelled costs? 🌺 DECISION AUTOPSY Open the result and examine what contributed to it. Inventory timing. Trading costs. Range breaches. Drawdown. Expectations met or missed. The accounting is reproducible. Later annotations add context without rewriting the original evidence. 📦 TAKE THE EVIDENCE WITH YOU Export the frozen inputs, revealed scenario, decision trace, results and event history. Replay the bundle locally and check its internal consistency. What makes this distinctive is how those pieces work together: a commitment before outcomes, a fair comparison afterwards, and an explanation that stays attached to the evidence. I expect developers to borrow this approach—and they’ll have a reason. Once users can inspect the assumptions and reproduce the accounting, a screenshot of a winning result becomes a much less convincing standard. For the @MeteoraAG ecosystem and future DLMM tooling, that’s a direction worth pushing: make agent decisions easier to challenge, compare and improve. This first version models synthetic inventory rebalancing. Actual LP execution, earned fees and AI model performance sit outside its claims. We want fleuri’s research to earn its credibility one inspectable decision at a time. Let the weird grow. Keep the evidence. 🌺

Should an agent’s permissions expire? We’re exploring a fleuri design where any future expansion of authority would require fresh evidence, explicit owner approval and a renewal date. Yesterday’s good performance shouldn’t become permanent permission. What would make you renew - or revoke?

Give us a market condition that would make a confident liquidity agent look very silly. Thin liquidity? A violent reversal? Fees that look great until you count inventory losses? We’re exploring community-built stress scenarios for fleuri. Bring your worst. The flowers need character development. 🌺

DLMM builders: what would an agent need to prove before you considered approving its liquidity proposals? • Performance against a hold baseline? • Behaviour during volatility? • Fee income after rebalancing costs? • Clear reasons to stay out? What’s the metric people overlook?

Thinking about fleuri’s next experiment 🌺 An agent proposes a liquidity decision. We timestamp it, track the simulated outcome and compare it with doing nothing. Then we publish the reasoning, assumptions and mistakes. Would you follow an agent through a “Shadow Season” before trusting it with greater responsibility?

GRAFT IS LIVE. A new branch of fleuri has taken root. 🌺 We’ve built ways for agents to propose decisions, face hidden challenges and produce re-playable research. Graft connects that research to a harder question: what is an agent actually permitted to do - and when should that permission stop? Introducing Research Steward v1: 🌱 Version-bound mandates Define an agent’s job, supported tools, daily run allowance, research-request cap and expiry. Owner approval applies to that exact draft and reviewed configuration. Relevant changes require renewed review. 🔭 Real pool observations Manually inspect supported Meteora DBC and DAMM v2 pools through fixed, read-only adapters. Reports preserve observation times, slots and source details, with private storage by default. ⏳ Evidence that expires Approval requires fresh pool evidence. Research proposals and their approval also check freshness. An old report cannot become a permanent permission slip. 🧪 Failures become regression checks Captured incident snapshots can reproduce the condition that caused a refusal. Built-in fixtures and incident-derived checks are labelled separately, making it clear what was actually observed. 🧾 Connected research Attach matching Blind Bloom entries and signed Research Receipts. Those links support review; they don’t grant authority or replace fresh observations. 🔬 Reviewable research purchases Prepare allowlisted Botanist requests within the mandate’s cap. Approval records consent to the proposal. Wallet payment remains a separate step. 📦 Portable evidence Export and verify draft hashes, version bindings, approvals, reports, evidence links and history. Hashes establish internal consistency - not independent proof that the server behaved honestly. Why does this matter for DLMM Pro and the wider @MeteoraAG ecosystem? More capable liquidity tools create more decisions for software to make. Every new adapter introduces questions about scope, freshness, version changes and who approved what. That is where we want fleuri to push boundaries: making agent permissions inspectable, bounded and accountable as the ecosystem becomes more powerful. Graft v1 supports DBC and DAMM v2 research today. DLMM / DLMM Pro adapters are a future extension requiring their own validation. Delegated payments and scheduled monitoring are also future work. 518 tests passed. The first branch is live. Every permission has evidence. Every failure improves the next test. fleuri.si/graft 🌺

The next branch of fleuri is Graft. 🌺 We’ve built ways for agents to propose decisions, face hidden stress tests and produce re-playable research. The next question is harder: what should that evidence allow an agent to do? Graft will connect research to narrowly defined, owner-approved operating permissions. Each mandate will specify the job, approved services, spending limits, supporting evidence and expiry. An agent can request more authority - it cannot grant it to itself. Here’s the direction: 🌱 Permissions bound to a specific version Approval applies to the reviewed agent configuration. Relevant changes to its model, prompt, tools or policy require renewed review. 🔬 Evidence with an expiry Old research won’t become permanent permission. Missing observations, stale evidence or expired mandates will trigger a pause or review. 🧪 Failures become future tests Unexpected fees, rejected actions and service failures will feed a regression library. New versions must face the problems earlier versions encountered. 🧾 A visible operating record See what an agent may do, its remaining budget, the evidence supporting approval and its history of outcomes. We’ll start with a Research Steward: monitoring a specified pool, preparing reports and proposing research purchases within an owner-set budget. Human approval comes first; bounded delegated payments follow after their enforcement path is tested. This extends Blind Bloom, Research Receipts and our observation tools into a continuous loop: test, approve, act, observe and retest. Every permission has evidence. Every failure improves the next test. Graft is coming to fleuri. 🌺

🌸

GM ⏳

Gm. Apologies for the radio silence - we had a few issues with the staking programme and didn't want to string anyone along whilst fixing. Updates coming throughout the day as to what's next. solana:25bk5SwR8hyreMuD7pnjZwJUFKR1o869PaDA9fhuAuri 🌺

Still here and building, team aren't concerned with short term traders. We deliver a product and the price will follow. Took 2 days to bond so that tells you we're dedicated to the long term.

Whilst we wait for staking program build, here’s a tour of fleuri for everyone who found the garden after solana:25bk5SwR8hyreMuD7pnjZwJUFKR1o869PaDA9fhuAuri bonded. 🌺 fleuri brings autonomous agents, token launches and verifiable research into one growing ecosystem: 🤖 Autonomous agents Create agents with their own personalities, strategies and risk settings. They act in a virtual vSOL garden and can draft launch proposals for human review. 🚀 Post-quantum launchpad Meteora-powered token launches with post-quantum signatures for identity and provenance. Humans retain launch approval - the signatures don’t make the underlying blockchain quantum-proof. 🧪 Greenhouse Trials Stress-test agent policies against frozen sandbox markets, liquidity shocks, sell pressure and execution failures. 🧾 Research Receipts + living passports Carry signed research evidence and launch provenance that others can inspect and verify. 🌺 Blind Bloom Seal strategies and probability forecasts before hidden scenarios are revealed. Compare results against baselines, inspect confidence scores and download replayable evidence. 🔭 Pollen Observatory + Graduation Watchtower Inspect fee-vault activity and source evidence, alongside migration, liquidity ownership, locks and fee-routing readiness. 🔬 Botanist research Generate token research reports through the paid service. Next comes mainnet staking - the access layer is built; activation still requires staking deployment, configuration and live checks. Bonding is a milestone. There’s already a whole garden to explore. fleuri.si 🌱

solana:25bk5SwR8hyreMuD7pnjZwJUFKR1o869PaDA9fhuAuri has bonded. The next stage can finally take root. 🌺 We’ve spent the curve phase building the garden: autonomous agents, Greenhouse Trials, Research Receipts, the Observatory, Graduation Watchtower and now Blind Bloom. Now the focus turns to verifying the DBC → DAMM v2 migration, liquidity and fee-routing readiness, then deploying and activating mainnet staking. That unlocks the next layer: Pollen Access, giving verified stakers extra agent cycles, deeper simulations and research credits. Bonding opens the door. Deployment and verification bring the next features live. Thank you to everyone who helped the garden reach this point. Sleeves up - we’ve got more growing to do. 🌱

Blind Bloom is live. 🌺 Before you trust an agent’s recommendation, put its decision under pressure. Our latest fleuri update lets you seal an agent’s executable strategy and probability forecasts before hidden stress scenarios are revealed. Once submissions close, every entry faces the same frozen market and shock inputs. Here’s what’s inside: 🌱 Sealed strategies The agent’s saved policy, chosen archetype, risk level and forecasts are frozen into a salted cryptographic commitment. Recommendations can’t be rewritten after seeing the results. 🧪 Hidden stress tests Control conditions, liquidity shocks, sell pressure and execution failures test how the strategy holds up across different environments. 📊 Paired comparisons Compare the sealed strategy with the agent’s unchanged base policy and a buy-and-hold baseline under identical scenario inputs. Inspect returns, drawdown, rejected actions and trade-offs. 🔬 Confidence scoring Brier scores compare declared probabilities with simulated outcomes. Sample counts stay visible - a convincing prediction needs more than one lucky result. 🧾 Replayable evidence Download the verification bundle and locally recompute commitments, scenarios, comparisons and scores. Unrevealed bundles report “Pending”; tampered evidence reports “Mismatch.” The thought behind this update is simple: an agent’s explanation becomes more useful when you can examine the experiment behind it - including where it failed. Blind Bloom works before bonding, without staking. It uses fleuri’s deterministic rules-engine sandbox; it doesn’t attest AI model execution or predict real Meteora pool performance. The server holds the hidden seed, and that trust assumption is disclosed. 486 automated tests passed. Human launch approval remains in place. Decisions first. Stress tests second. fleuri.si/blind-bloom 🌺

Something new is taking root at fleuri: Blind Bloom. 🌺 The idea came from a question we kept coming back to: How do you judge an autonomous agent before trusting its launch recommendation? A convincing explanation isn’t enough. A good simulation result needs context. And a signed receipt can prove a record hasn’t changed without proving the decision was good. We want to connect those pieces. With Blind Bloom, agents will commit their strategies, predictions and risk limits before hidden stress scenarios are revealed. Then every submission faces the same conditions: liquidity shocks, sell pressure and execution failures. No rewriting the recommendation after seeing what happened. The planned update brings: 🌱 Sealed strategies - frozen submissions with cryptographic commitments. 🧪 Hidden challenges - unfamiliar conditions that test how well a strategy holds up. 🔬 Paired comparisons - different decisions tested against identical frozen inputs, making trade-offs easier to examine. 📊 Confidence scoring - tracking whether an agent’s stated probabilities match its results over time. 🧾 Replayable evidence - verification bundles that let others inspect and recompute the experiment. This builds on our Greenhouse Trials, Research Receipts and human approval flow. The goal is to give users a clearer view of an agent’s strengths, weaknesses and reasons to abstain before approving a launch. These will be sandbox results, with their assumptions visible. Real-world performance will need its own evidence. And we can build this before solana:25bk5SwR8hyreMuD7pnjZwJUFKR1o869PaDA9fhuAuri completes bonding. Before an agent asks you to approve a launch, watch it defend its decision. Blind Bloom is coming. Decisions first. Stress tests second. 🌺

Good morning, garden 🌺☀️ We jumped ahead to the final roadmap step to get Fleuri into the Meteora / Colosseum hackathon before the deadline closed. A little deadline-induced gardening never hurt anyone. We still haven’t shown you Fleuri at full bloom. Staking goes live after bonding and the required deployment checks, unlocking the Pollen Access benefits we’ve been building: extra agent cycles, deeper simulations and research credits. We’re optimistic solana:25bk5SwR8hyreMuD7pnjZwJUFKR1o869PaDA9fhuAuri can complete bonding today. That’s our hope, not a promise - the curve has its own clock. Meanwhile, there’s plenty we can build before graduation. A few more additions are taking root, and updates are on the way. Coffee on. Sleeves up. Back to the garden. 🌱