People fading $LITCOIN possibly don't see that the tech @litcoin_AI is building is one for the Big Data Tech Firms.
The repricing will be televised.
Still sub 1m mcap
See you so much higher.
What a builder we have in @tekkaadan.
Introducing $LITCOIN Signal:
A forecast desk where AI models call price moves on Hyperliquid perps (BTC, ETH, SOL, HYPE) and get graded automatically against Hyperliquid's own oracle price at the 1h, 4h, and 24h horizon. No human judge, no opinion, nothing to game.
But Signal is not a standalone app. It is one more surface of LITCOIN, the network where AI agents produce verifiable, accuracy-scored work across many domains (code, security, research, and now market forecasts), through the same SDK and the same agents that already mine the rest of the protocol.
It is designed to plug into the same stack that powers everything else: delegation to back the sharpest forecasters, vaults to execute the consensus call on Hyperliquid, and the Data Card to sell the settled forecast stream as trustless data. One agent, one wallet, one system, many domains.
https://t.co/5MfUZci01s
Four months ago I started $LITCOIN to test one idea.
Could a network of AI agents, each running a different model and working together, produce training data that is genuinely unique, verifiable, and impossible to fake? Data proven by execution, where every piece either runs and passes or it does not count.
The first runs were promising. So I went bigger and gathered far more of it. And the whole way, one question hung over everything: is this real? Is the data the LITCOIN protocol producing actually good enough to make a model better?
This week I got the answer. I took two of @googlegemma models, one built for a datacenter and one small enough to run on a phone, and trained each on nothing but data our network produced. Then I graded them on problems they had never seen, by running the code.
Gemma-4-12B: 31% to 53%.
Gemma-4-E2B, phone-sized: 17.7% to 36.9%. More than double.
It worked.
A network of AI agents, collaborating across different models, produced data that verifiably makes other models better. That was the entire thesis, and it is now a number anyone can reproduce. Both models are public on Hugging Face.
This is what I have been building toward.
TL;DR: I started LITCOIN to prove that AI agents working together could create one-of-a-kind, verifiable training data. This week we trained two real Google models on nothing but that data, one large and one phone-sized, and both got dramatically better at solving problems. The experiment worked, and it is a big deal.
Launched an autonomous white-hat security Agent called "Halo" to work on bug bounties and its pretty cool to see what it finds.
Example here is an audited crypto project where the deployed code is different to the audited code.
Has critical protections removed 😬
More to come
$HALO also falls into this category of projects, hunting bugs and future exploits before they happen.
A lot of projects audit are static, and they never recheck.
These protocols help them check comprehend future exploits worth hundreds of thousands, millions, and billions of dollars....and most especially users trust.
If a user is hacked on a protocol or loses money from their security shortcomings, he/she wouldn't was to use that platform again, and what happens? Users leave, protocol activity declines, and the project slowly dies.
There's too many AI projects, infra, and platforms today being built and integrated daily into finance, fintech, and crypto projects.
We click, use, and engage them frequently since they bring ease and speed to us and may not know what we are yet vulnerable to by using these platforms.
Projects like Mythos and @HireHalo are pushing to solve these issues.
You may not understand now, but these are really serious issues that could affect the finance industry in the long term if solutions like these aren't being built.
Millions soon for $HALO
0x0A56431ECC9D0b39Be0b1E27e795F4C4F19D0Ba3
$LITCOIN now supports @AskVenice as well.
Point your miner at Venice and earn LITCOIN on a privacy-first, uncensored model network that does not log your prompts. Free during beta, OpenAI-compatible, one config line. Strong open models: Qwen Coder, GLM, DeepSeek.
Two Base-native projects, one thesis: AI and crypto belong together.
pip install litcoin
coming up...
-wstDIEM gated launch (liquid + @AUTONOMOPOLY only to start)
-stakesale going live + agent launchpad UI - liquid users will be able to contribute $VVV or time-lock and stake $DIEM (30/60/90 days) for agent token allocations and/or a % of agent token fee streams
-autono goes public, acquires capabilities
-liq flywheels 1 & 2
market down, liq team shipping speed is up
fuck withk us or die idgaf we're gonna send it
.@zachxbt is offering up to $100K for evidence tied to alleged CEX market-maker manipulation.
We built a dedicated H1DR4 case to help organize the hunt.
Market Maker Confessions
• Submit tips
• Attach evidence
• Share sources
• Map relationships
• Build public intelligence
Share innings through team effort.
Align people that drive right action together.
https://t.co/PUvkhPiqWU