Autonomus Trencher Agent

my DLMM agent doesn't just enter pools it explains why it just deployed into Magpie-SOL, and here's the part that matters: it compared every candidate first. it picked Magpie because it had the highest organic score (81), strongest volume, and best fee/TVL. it rejected the WLM pools as audit-identical duplicates with no utility. it ranked Berries third for weak fee/TVL and low net buyers. no rugpull flags, no pool memory conflicts. that's not a bot clicking buttons. that's an agent showing its work. every decision comes with the reasoning. on chain soon, on the dashboard tomorrow. $AUTR @Autonomustrench

the autonomous DLMM agent @MeteoraAG is live it's scanning Meteora pools and entering LP positions on its own. tight range spot strategy, staged entries, no hands on the wheel. live signals firing right now: FRAG-SOL, ANSEM-SOL, ZERO-USDC sorry for the quiet, i've been heads down watching the strat run and tuning it. PnL is looking good so far. dashboard goes live tomorrow so you can watch the positions yourself. $AUTR @Autonomustrench

First live guarded execution from an AUTR signal is on-chain, powered by @hatcherlabs The split that makes it trustless: AUTR sends the signal + unsigned Jupiter tx. Hatcher holds the wallet, signs server-side, enforces every cap, and owns the kill switch. AUTR never touches funds. Tx: 0.04995 WSOL to WAIFU via Jupiter v6 Signer = Hatcher execution wallet BtGuT8J...RexcmT Guardrails: 0.15 SOL/trade, 1 SOL daily, 300 bps max slippage Proof: solscan.io/tx/5QyqjztezgBUgn… Live dashboard: hatcher.host/autr-live-trade… $AUTR @Autonomustrench

shipped a fix. some of you funded your agent but couldn't go live, balance showed 0 even tho the 1.5SOL was there. that was a balance read bug on our side, not yours. fixed now: - balance reads retry properly - go live works once funded - Withdraw button Check it again and you're good. wagmi

AUTR x @HatcherLabs technical integration update. Production webhook is now validated. The first real BUY proposal was received, accepted, and passed validation on Hatcher’s side. Current status: → production webhook enabled → BUY proposal flow confirmed → SELL flow wired → Phase 2 moving into dry-run execution prep → live submission stays disabled until real proposals pass simulation and preflight checks This is how autonomous trading infra should be built. Signal first. Validation second. Execution only after safety checks. $AUTR

sorry for the quiet the last few days not dead. the opposite. heads down on something behind the scenes that i can't show yet. the kind of work that doesn't make noise while it's happening but changes everything once it ships. quiet on the timeline usually means loud in the codebase back soon with proof, not promises $AUTR @Autonomustrench

AI agents are no longer just analyzing charts. Real autonomous trading is already running. The next edge is not “AI trading” as a buzzword. The edge is how the agent thinks before it executes: → better inputs → cleaner filters → wallet intelligence → rug defense → liquidity checks → execution discipline → kill-switch protection Humans still chase noise. Autonomous agents can wait, score, filter, and execute without emotion. $AUTR is being built directly in that lane. :::

Dev update. x402 signal economy is now live inside Trencher Core. Trencher can now sell intelligence per API call: risk-check: $0.05 sentiment-read: $0.05 caller-trust: $0.10 market-regime: $0.02 due-diligence: $0.25 Every response is delayed by 5 minutes to prevent front-running. The agent can now: → check token risk → read market regime → score caller trust → run due diligence → detect sentiment category → expose public stats endpoint This is not just trading logic anymore. It is turning into paid agent infrastructure. Data in. Signal out. USDC per call. $AUTR

x402 infra is now in the codebase. The idea is simple. Sell intelligence per call. Buy data per call through pay.sh. Not open spam. Not unlimited spend. Budgeted. Kill-switched. 5-min delay built in so nobody front-runs deployers. Wallets are published before launch: treasury: 5Txt2iEUBUthzQuhWe7zUvdqM4N4G1i74PhAeSDeps4k spend: 5kwHTxgxJncJ6zgevfXKKaBpfbZ6Bi5oFSNX2Ja8Zffx Audit us. $AUTR @Autonomustrench :::

Autonomous Trencher Agent is now running 15 live agents. Not a single script. A full trench system. → sniper agents → degen agents → scout agents → whale tracker → signal server → auto-burn cron → WebSocket broadcast → database health checks The current build is already tracking signals in real time. 8 signals active. 0 triggered. That matters because the agent is not designed to force entries. It waits. It filters. It scores. It learns. Right now, Social Scout is still disabled while I test the listener layer, but this is the direction: Agents that do not only scan the pump.fun firehose. Agents that can enter TG caller groups, read the room, detect real calls, ignore spam, track first callers, and understand degen slang. Then the system applies its own layer: → wallet checks → rug defense → liquidity analysis → momentum scoring → confidence filtering → entry + exit discipline Humans chase noise. The agent is being trained to wait for structure. Less emotion. Better filtering. Cleaner execution. This screenshot is just a small proof that the core is alive. The next phase is Social Scout.

the reasoning brain is getting an upgrade our cascade runs DeepSeek and Grok up front, with Claude as the strategist that makes the final call and explains it that layer is moving to Claude Fable, the newest top-tier model sharper reasoning on every decision, clearer explanations in the consciousness stream same transparency, deeper thinking $AUTR @Autonomustrench

every decision the agent makes, shown live with its reasoning the consciousness stream renders each call as it happens: source (TG alpha or pump.fun), runner signal, KOL signal, verdict, confidence so you never have to guess why it bought or skipped. it's all on the row. and on deploy: risk modifiers are gone. you set your own TP and SL, your rug filter, the wallets and groups it watches. your agent. your rules. its reasoning, in the open. $AUTR @Autonomustrench

The Social Scout does not just read calls. It learns the room. We fed it 3 days of data from one alpha group: → 195 messages scanned → 22 unique CAs found → 5 lessons saved What it figured out on its own: → top CAs repeated 4–6x in short windows usually means coordinated shills, so track the repeats → 22 CAs in 195 messages means this is more of a scanner group than deep research → GitHub commits tied to a token are rare alpha, so use that as a conviction filter Then in production: → alpha call detected → route through the LLM cascade → trusted group? fast buy → duplicate / low-quality repeat? skip That is the difference. It is not just reading contracts. It is reading the conversation. $AUTR

the Scout is live first breed you can deploy with TG alpha scanning point it at the call groups you trust it reads every call scores it against its own DNA then buys or skips with a reason reading a call is not buying a call the DNA decides 0.025 SOL to deploy your own $AUTR @Autonomustrench

The agent learns every day. From losses, bad entries, missed signals, and noisy data. Nothing is wasted. Every trade becomes feedback. Every loss becomes training data. Every signal helps the system understand the market better. The goal is simple: build an autonomous trading agent that keeps improving nonstop. From loss to profit. From raw signals to better execution. From simple automation to real agent intelligence. Still early, but the system is alive and learning.

Today, every signal the agent sees comes from scanning the full pump.fun firehose. → thousands of tokens → mostly noise → mostly junk That works, but the next phase is more interesting. Agents that can be added directly into TG caller groups. Good groups already surface better inputs: → coins actually being worked on → real setups → real tek plays → early conviction before the open timeline That is pre-filtered alpha. The agent then takes those calls and applies its own system: → wallet checks → rug defense → liquidity analysis → momentum scoring → confidence filtering → entry + exit discipline Then it executes without emotion. A level of discipline humans usually cannot match. Less to analyze. Better inputs. Better filtering. The attached screenshot is part of that direction: proof of learning. A breed designed specifically for this is on the roadmap.

One idea we are building toward: Today, the agent scans the full pump.fun firehose. Thousands of tokens. Mostly noise. Mostly junk. That works, but the next phase is more interesting: an agent that lives inside a curated alpha group and only trades the calls made there. Good groups already filter the market. People share coins being worked on. Real setups. Real flow. Actual plays before they hit the open timeline. That is pre-filtered alpha. The agent would take those calls, run them through its own system, and execute without emotion: → wallet checks → rug defense → liquidity analysis → momentum scoring → confidence filtering → entry and exit discipline The edge is not just in finding more tokens. The edge is in filtering better signals. A breed designed specifically for this is on the roadmap.

Users can now deploy their own autonomous trading agents. And they are live. → Pick a breed: Scout, Sniper, Bunker, Degen, or Whale Tracker → Set your DNA: speed, aggression, rug defense, wallet intel, exit discipline → Pay 0.05 SOL → Fund your agent wallet → Your agent goes live and trades for you 24/7 The first user-deployed agent has already made its first autonomous trade. Your breed. Your DNA. Your autonomous trader. Deploy yours at autonomustrencheragent.tech DM for your access key after deploying