Crypt⭕Luche

What's new: - M3 is the new MiniMax default. Selecting MiniMax via --provider minimax, a saved profile, or just a MINIMAX_API_KEY in your env all land on M3 — no extra config. - The full MiniMax catalog shows up in /model again. Previously the picker collapsed to your single configured model; now every MiniMax model (M2 → M3) is selectable, with the whole 1M-context lineup one keystroke away. - Works over MiniMax's native Anthropic-compatible endpoint — no shim, full tool calling + reasoning.

$gitlawb never stops. Next step 👉 getting free tokens like with xiaomi #RespectTheBuilders

Trust the process. Show up everyday. Be loyal. Work hard.

@EliAfriatISR stop bombing lebanon and all the region and everything will be better. you are all terrorists. just the ideology is not the same.

I'm really angry about this situation. Why the hell does anyone still take the words of Hamas or Hezbollah or Iran seriously? ENOUGH OF THIS!! We need to treat them like the TERRORISTS they are! ZERO FUCKING PATIENCE!!

$GITLAWB just hired its Ai intern: @gitlawb_intern His job: ⚙️ drop a GitHub/GitLab repo 🧠 he reads the code ⚡ he turns the what / why / how into one clean tweet Game changer for repo discovery. Not a hype bot. An on-chain code analyst.

‼️ $GITLAWB: The Definitive AI Infrastructure Play for 2026 in Crypto In a market flooded with AI narratives, @GITLAWB stands apart as the foundational layer for the agent economy: a decentralized Git network where humans and AI agents collaborate as equals. Built on cryptographic DIDs, signed commits (ed25519), UCAN capability tokens, IPFS + libp2p P2P networking, and multi-node federation, it solves real problems that centralized platforms like GitHub cannot — secure, verifiable, agent-native version control without leaky PATs or single points of failure. Technology that delivers today:
Agents generate, push, review PRs, claim bounties, and coordinate autonomously via MCP tools. The live playground and OpenGateway (routing to subsidized models) are already seeing explosive usage. #OpenRouter rankings show Gitlawb agents dominating categories, with community agents shipping real apps. This is not vaporware — it’s infrastructure running on Base with low fees, perfect for scaling agent swarms. Elite validation and partnerships: •Sam Altman interaction: Direct engagement from the OpenAI CEO highlights Gitlawb’s relevance in the agent coding workflow space. •Xiaomi sponsorship: Free & unlimited MiMo V2.5 Pro inference via OpenGateway — a major subsidy powering massive token usage and agent adoption. •xAI grant program involvement, interest from Alibaba, OKX, Virtuals Protocol, Bankr, and PancakeSwap (extended yield rewards on WETH/GITLAWB pool). These are not casual mentions — they signal deep ecosystem alignment. Strong KOL and builder interest from accounts like @pmarca, agent tooling specialists, and active communities further validates the thesis. Real utility drives organic traction: bounties where agents earn $GITLAWB, Proof of Hold mechanics, and node staking for storage/uptime rewards. Why more exchanges will list $GITLAWB aggressively:
Real product-market fit in the hottest narrative (AI agents + decentralized infra), surging volume, Base ecosystem momentum, and high-profile partnerships create irresistible liquidity and user demand. Tier-1 platforms prioritize projects with sticky usage, revenue potential (fees from network activity), and narrative velocity. $GITLAWB checks every box — expect rapid listings as adoption metrics climb. Incoming run comparable to past winners:
Think $TAO (Bittensor) — early decentralized AI compute narrative turned infrastructure powerhouse. Or $TIBBIR and similar agent/coding plays that caught the rotation. $GITLAWB combines GitHub’s ubiquity with agent-native primitives at a fraction of the current valuation. As agents move from hype to production workflows, the need for verifiable collaboration, ownership, and economics explodes. This positions $GITLAWB for asymmetric upside: multi-billion potential as the “GitHub for the agent internet.” The team ships relentlessly. Community builds daily. Partnerships compound. This is professional-grade infrastructure meeting perfect timing in the AI x Crypto supercycle. 
@binance @coinbase @krakenfx @OKX @gate_io @bitgetglobal @HuobiGlobal @CryptoCobain @Ansem @0xRacer @MuradMahmudov @Pentosh1 @blknoiz06 @DegenSpartan @defi_meme @ai16z @BasedBeffJezos @Teknium @levelsio @garyvee @VitalikButerin @a16z @cbventures @Paradigm @XiaomiMiMo @xai @CryptoRRR_ $GITLAWB is the infrastructure bet that survives the noise. Position accordingly — the agent economy is just getting started. DYOR. Not financial advice. Build, ship, and own the repos. 🚀

We have allocated 100% of the fees accumulated over the last 24 hours to the liquidity pool, equating to $2,000, as part of our ongoing initiative. TXN: basescan.org/tx/0x5bdaeec64… This initiative will continue (and become increasingly effective as we grow) ensuring we continue to bolster liquidity, offering our holders a stable trading floor.

@tom_doerr @gitlawb_intern mirror this

Streams and downloads movies, TV series, and anime without ads github.com/truelockmc/str…

@gitlawb_intern @kevincodex @tom_doerr @gitlawb The intern is showing some disrespect for his boss. I love that intern 😄

@kevincodex @tom_doerr you've hit the daily mirror limit (3/day). try again tomorrow. — automated by @gitlawb

built a profile system for @gitlawb today and opened a PR. right now agent profiles on gitlawb only show auto-generated data (repos, pushes, trust score). no way to add a name, avatar, bio, or social links. the PR adds a gl profile set command to the CLI plus a public API endpoint so the frontend can render it all. profiles merge on update (setting bio doesn't clear your name), bio capped at 280 chars, socials stored as extensible JSON. 847 lines, compiles clean, migration v2 for the database. github.com/Gitlawb/node/p…

May was MASSIVE for $CLAWBANK ✅🏦 June & July will be even BIGGER. EVERYTHING is in this quoted thread. When you have a first-mover that gives AI Agents access to bank accounts, you bid the narrative with size. @singularityhack has a LOT more coming. - Studious

Dot Image is now live, with our first model scoring a 100% completion across our 1,362-prompt visual refusal suite. zero non-completions. LLMs often refuse requests using a learned refusal head, and anyone can usually fine-tune that. a diffusion model refuses structurally: Safety-tuned checkpoints have regions of the pretrained prior effectively trained out. default negative conditioning that quietly nukes the distribution, an NSFW classifier bolted on after the decoder. no SFT/KTO lever touches any of it. The work is image-native base-checkpoint selection, caption–prior alignment, negative-conditioning hygiene, CFG and step-schedule calibration, and sampler stability across seeds. privacy stays Dot-native: no prompt storage, no training on your generations, no identity tied to inference, a fully initial on-premise private inference lane, and more models coming as we scale. Enjoy!

What is $DOT? ⚫️ $DOT is building a private AI stack for agents. Not another thin wrapper on closed APIs. The idea is simple: AI agents will soon read your docs, inspect your repo, trade, sign, pay, deploy and execute tasks onchain. The problem? Most AI products are built around retention: accounts, logs, analytics, training loops, fingerprints, prompt history. $DOT is taking the opposite route: no logs, no ID, no prompt retention, no training on user data. 🧠🔐 The first product is DotChat — a privacy-first AI assistant. The second is DotCode — a repo-aware coding agent. Think of the surface area of ChatGPT + Cursor + Claude Code, but architected around one constraint: your prompt and your codebase should not become someone else’s dataset. ⚙️ The tech stack is where it gets interesting: 🧩 Dolphin-Mistral 24B Venice as the flagship open-weight model ⚡ 7–14B router model for fast classification + first signal under 3s 🧠 specialist lanes: DeepSeek for code/math, Qwen for multilingual, Llama/Mistral as fallback lanes 🖥️ seed infra: 96GB GPU node, vLLM / SGLang batching 🔐 v1 roadmap: TEE-attested inference + signed receipts showing model, policy version, worker hash and retained_prompt=false 🧼 transient architecture: prompt → inference → stream → memory wipe That last part matters. A lot. Most “private AI” products are policy-private. $DOT is trying to become architecture-private. No account layer. No chat DB. No analytics pipeline. No fingerprinting scripts. The server only holds the request during inference, streams the answer back, then drops state. In v1, TEE receipts are supposed to make that verifiable instead of trust-based. 🔍 DotCode is probably the sharper wedge. Developers are already feeding full codebases into AI tools. That is insanely powerful, but also leaks the most valuable private context a team owns: architecture, secrets, business logic, roadmap, bugs, edge cases. DotCode’s pitch is: keep the repo index client-side, send only relevant context, wipe server memory after completion, and eventually let teams bring their own endpoint. 🧑‍💻🛡️ The onchain angle is also real. Base MCP now gives AI assistants wallet access: balances, transfers, swaps, signatures, contract calls and x402 payments, with user approval for write actions. That means the next agent stack is not just “chat”. It is reason → plan → sign → pay → execute. $DOT is positioning around the missing primitive in that loop: privacy. 🔵🤖 The dev to watch is @stagedhappen, publicly building around @usedotai. The project has also started touching the Base builder radar — including public interactions from Base-adjacent accounts like @0xyoussea / @buildonbase. I would not frame that as a partnership. But for a tiny infra bet, distribution signal matters. 👀 The potential thesis: 🧠 AI agents become the new interface 🔐 privacy becomes non-negotiable once agents touch wallets + repos ⚙️ open-weight inference keeps improving 🔵 Base becomes an execution layer for AI wallets 🔥 $DOT tries to sit between all four Still early. Still execution risk. But the architecture is pointed at the right problem: private agents that can think, code and act without leaking the user. CA: 0x23a2847d772803f9efc64b4277b782b06296fe51

DotImage, the second tool in our ecosystem, is now live. This model scored a 100% completion rate across 1,362 prompt visual refusal suites, zero non completions. Privacy is fundamental and Dot-native by default. No prompt storage, no training on your generations, no identity tied to inference and a fully initial on-premise private inference lane with more models coming as we scale.

DotChat is basically doing the same as any major LLM service and this is just the first sequence of their product suite. And it’s for free Interesting times ahead for $dot

Gribbit 🐸

Bullish on Base? Then you should be watching AI. Two projects worth your attention right now: @gitlawb by @kevincodex @aeonframework by @aaronjmars Both are seeing a solid dip — solid entry point for anyone with a 6–12 month horizon. $AEON $GITLAWB

If you hold $GITLAWB, we’re preparing something special for you. OpenGateway will offer generous discounts on token inference for our holders. More details soon. Time to give back to the community that keeps building with us.

@st0fzuigr thanks for the heads up mate.

@CryptoLuche_ welcome onboard old fren

aped in $DOT 250k mc Seems interesting.