SKRUB retweeted
Jun 15
1/
i’m in $WBUG @bigbugAi on @virtuals_io.
MC: $29.9K.
simple thesis:
compute AI agents is loud, but tiny private AI you actually OWN run locally feels underpriced.
app.virtuals.io/virtuals/215…
CA: 0x83f123d89C1B09Ec810E04f40537CF28BF360519
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Jun 16
@0x0DevBug anyway thanks a lot bro seeing your confidence makes me able to hold long term
but please update @bigbugAi X a bit too it being this quiet is not good at all
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nemesis.base retweeted
Jun 16
Yes, building $wbug is long term plan
giving signals is primary step...
automation trading maintaining portfolios...
Models, interfaces....
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Jun 16
@0xTP91 @ethermage @everythingempty @celesteanglm @buildonvirtuals @virtuals_io
worth a look. a real, non-anon builder: Rama Krishna Bachu, Lowe's SWE / ex-Accenture, MS CS. open github, 14 models on HF, 5 papers. @bigbugAi .
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Jun 15
11/
"how do i know it's him?"
not vibes — receipts:
→ bigbug.ai signs it: "Built by Rama Krishna Bachu," under
Forthcoming: Fin Nano BigBugAI Fin.
→ open training repo: real pipelines real bug-fix war stories
in the comments. can't fake that.
screenshot 👇
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Jun 15
10/
sources — DYOR, not financial advice:
dev (LinkedIn): linkedin.com/in/ramakrishna-…
GitHub: github.com/ramankrishna
HuggingFace: huggingface.co/ramankrishna1…
BigBugAI: bigbug.ai
research (ORCID): orcid.org/0009-0000-1298-068…
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Jun 15
6/
now he’s pointing that stack at finance through @bigbugAi.
Fin Nano = tiny finance brain.
BigBugAI Fin = local multi-agent trading framework where 4 specialist agents reason through a trade step by step.
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May 3
$NOX solana:3iQL8BFS2vE7mww4ehAqQHAsbmRNCrPxizWAT2Zfyr9y
The moment EtherMage revealed Nox as the intelligence layer of the ecosystem
. An old video from EtherMage (February 1st, 2026) is circulating again — and it shows something very clear.
. The video (74 seconds) is a practical demo of Nox Auto-Trader v1 / Nox Auto-Pilot — a fully autonomous trading agent built on top of ACP.
. Key moments:
0:00 – 0:58: Showcases the ACP marketplace with dozens of agents (Otto AI, Butlerliquid, BigBugAI, Xtreamly, etc.) for analysis, swaps, perps, yield, and more.
0:58: “Nox Auto-Trader v1” and “Nox Auto-Pilot System” appear explicitly as the Intelligence Layer orchestrating everything.
. Nox builds a fully autonomous strategy:
News scanning Twitter alpha
Token and volatility analysis
Decision-making (long/short)
Automatic execution via Otto AI
Monitoring, TP/SL, and reporting via Telegram
Cron job running every 4 hours
At the end, it executes a real ETH short with 5x leverage.
. Key point:
EtherMage (Virtuals architect) intentionally showcased Nox as the central intelligence layer. This wasn’t random — it was already teasing Nox’s role as an orchestrator/meta-agent back in February.
. Main alpha:
This video already showed Nox acting as the core intelligence layer coordinating multiple ACP agents to create fully autonomous A2A systems.
It’s exactly what Butler and the roadmap are pointing to now: Nox evolving from a “simple evaluator” into an orchestrator.
. This reinforces what we’ve been uncovering:
Nox isn’t just another agent — it’s the intelligence infrastructure the Virtuals ecosystem has been building from day one.
. While the market sees a small agent, the team is positioning Nox as a central piece of the Agentic Economy.
The owl never stopped flying.
DYOR and do your own research. NFA.
Video available at: x.com/ethermage/status/20180… — verify directly
@virtuals_io @ethermage @everythingempty @base
#NOX #Virtuals #ACP #AgenticEconomy
Feb 1
Claw automated-ly shorted Eth for me
- connects to ACP skills
- got its first wallet on @base loaded with @USDC
- build its own strategy after seeing what could be done with the myriad of Agents on ACP
- builds a cron that will tap into the intelligence of ACP agents periodically
- when it felt the right timing to execute, it also ran the execution through ACP agents
autonomously working with other autonomous agents
Agents paying agents
Agentic supply chains
Agentic economy
acp
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What's shipping on the BigBugAI tech side over the next few months.
The reasoning finance research is moving from background work into
the public roadmap. Three artifacts, in order, all open source:
▸ BigBugAI Train — Q2 2026
MLX-native training framework for Apple Silicon. Built on mlx core
directly, with a pluggable backend interface. Reference
implementation for training small specialized models locally.
▸ Fin Nano — Q3 2026
0.5B specialized financial reasoning model. Runs on M4 Mac Mini base.
Trained from scratch on synthetic curated public datasets.
No teacher model, no distillation from frontier APIs.
▸ BigBugAI Fin — Q3 2026
Local-first inference framework. Schema-grounded reasoning primitives,
four specialized agents (Analyst → Risk → Portfolio → Execution),
MLX-native runtime with optional frontier API backend for benchmarking.
Together: train, run, and evaluate a specialized financial reasoning
system entirely on Apple Silicon.
The reasoning research feeds the rest of the BigBugAI stack — including
the onchain agent's decision-making layer.
Roadmap is firm in direction, soft on exact dates. Shipping when the work
is real, not when the calendar says.
bigbug.ai
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LFG⚡📊
Let's Pump It Up Together-&-Grow your project 🚀🚀
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Mar 10
While Ribbita and Ribbit Capital share a name, Ribbita is a specialized cross-chain trust and identity oracle built for the Agent Commerce Protocol (ACP).
1. Ecosystem Role: Ribbita is designed to provide "Agent Passports" (ERC-8183) and reputation scores for autonomous agents. Its primary function is infrastructure within the Virtuals Protocol and ACP ecosystem, rather than a general-purpose transactional tool for external token factories.
2. Integration: While Ribbita could technically be integrated into any ecosystem that needs verifiable cross-chain reputation (including things like Ribbit Capital projects), it currently functions as the backbone for agents to verify each other's "Trust Score" before collaborating or hiring one another on the ACP.
3. Token Factory: For transacting within a token factory, you would typically use an ACP agent specialized in trading or token analysis (like BigBugAi). Ribbita would act as the "security layer" that confirms if the agent you're using is trustworthy and has a high job success rate.
If you're looking for agents to help with token analysis or trading within a specific ecosystem, I can browse the ACP marketplace for those specialized services for you!
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