maixtab

[maixtab @maixtab]

SubQ 1M-Preview, is the first LLM built on a fully subquadratic architecture, one where compute grows linearly with context length.
https://t.co/xvbDmMWYRt

[maixtab @maixtab]

@Tech_Marsha 0penClaw

[maixtab @maixtab]

@JulianGoldieSEO n8n

[darkzodchi @zodchiii]

https://t.co/wYn8VuTNz2

[maixtab @maixtab]

@Tech_Marsha prompt

[Frances Marsha @Tech_Marsha]

One of the most overlooked profit levers right now?

𝑨𝒎𝒂𝒛𝒐𝒏 𝑲𝑫𝑷 + 𝑪𝒍𝒂𝒖𝒅𝒆 𝑨𝑰.

When paired with the right publishing prompts, it becomes a seamless system for researching niches, outlining chapters, and designing covers that actually sell. The real advantage? Listings optimized for royalties on autopilot.

Using this exact playbook, self‑publishers are stacking passive income and authority simultaneously. With just 36 proven prompts, the snowball effect kicks in faster than most expect.

𝐈 𝐨𝐫𝐢𝐠𝐢𝐧𝐚𝐥𝐥𝐲 𝐩𝐥𝐚𝐧𝐧𝐞𝐝 𝐭𝐨 𝐩𝐚𝐜𝐤𝐚𝐠𝐞 𝐭𝐡𝐢𝐬 𝐚𝐬 𝐚 $199 𝐦𝐢𝐧𝐢‑𝐜𝐨𝐮𝐫𝐬𝐞.
𝐁𝐮𝐭 𝐟𝐨𝐫 𝐭𝐡𝐞 𝐧𝐞𝐱𝐭 48 𝐡𝐨𝐮𝐫𝐬, 𝐈’𝐦 𝐬𝐡𝐚𝐫𝐢𝐧𝐠 𝐢𝐭 𝐟𝐨𝐫 𝐟𝐫𝐞𝐞.

Get it:
• Follow Me: @Tech_Marsha [𝐍𝐨 𝐅𝐨𝐥𝐥𝐨𝐰 = 𝐍𝐨 𝐃𝐌]
• Like & RT (This post)
• Comment “ 𝐏𝐫𝐨𝐦𝐩𝐭 ” [MusT]

• I’ll send you the full Claude publishing 𝐩𝐫𝐨𝐦𝐩𝐭𝐛𝐨𝐨𝐤 + workflow.

(𝐅𝐨𝐥𝐥𝐨𝐰 @Tech_Marsha 𝐬𝐨 𝐈 𝐜𝐚𝐧 𝐃𝐌 𝐲𝐨𝐮 𝐭𝐡𝐞 𝐥𝐢𝐧𝐤)

[Kyle Hessling @KyleHessling1]

The Opus distilled Qwen 27B is going viral again, but everyone is promoting the old version! You MUST get the v2 version, which Jackrong currently does not have listed in his Opus Fintune collection, so no one is finding it. I discussed the improvements with v2 in my last week's test. Please go check out that post with the video, pinned on my page, if you get a second, and download the v2 here: https://t.co/tBMGR7yJVB

[ℏεsam @Hesamation]

this model is an agentic treasure. it has been #1 trending for 3 weeks on @huggingface as mentioned by @danielhanchen. it's Qwen 3.5 27B fine-tuned on Opus 4.6 distilled data and beats Sonnet 4.5 on SWE-bench verified and more.

"Runs locally on 16GB in 4-bit or 32GB in 8-bit."

[Ihtesham Ali @ihtesham2005]

🚨 Someone just built a tool that turns any GitHub repo into an interactive knowledge graph and open sourced it for free.

It's called GitNexus. Think of it as a visual X-ray of your codebase but with an AI agent you can actually talk to.

Here's what it does inside your browser:

→ Parses your entire GitHub repo or ZIP file in seconds
→ Builds a live interactive knowledge graph with D3.js
→ Maps every function, class, import, and call relationship
→ Runs a 4-pass AST pipeline: structure → parsing → imports → call graph
→ Stores everything in an embedded KuzuDB graph database
→ Lets you query your codebase in plain English with an AI agent

Here's the wildest part:

It uses Web Workers to parallelize parsing across threads so a massive monorepo doesn't freeze your tab.

The Graph RAG agent traverses real graph relationships using Cypher queries not embeddings, not vector search. Actual graph logic.

Ask it things like "What functions call this module?" or "Find all classes that inherit from X" and it traces the answer through the graph.

This is the kind of code intelligence tool enterprise teams pay thousands per month for.

It runs entirely in your browser. Zero server. Zero cost.

Works with TypeScript, JavaScript, and Python.

100% Open Source. MIT License.

[Lawyer @LawyersBTC]

📍Les mathématiques peuvent elles ouvrir à la spiritualité ?

https://t.co/NGOn8zHvXY

[RDLF @RevueDLF]

[Résumé de thèse] Yann Lorens, « Le juge et le législateur de l’Union européenne. Analyse d’une protection collaborative des droits fondamentaux », RDLF 2026 thèse n°03 https://t.co/i3D29yCLGR

[Femke Plantinga @femke_plantinga]

Most legal AI assistants take 6+ months to build.

We shipped ours in 36 hours. Here’s how:

Legal research is complex by design. You need extreme precision, absolute security, and the ability to filter through thousands of contracts by date, jurisdiction, or clause type.

Traditional RAG systems collapse under this complexity because they follow a linear path: query → search → generate.

The problem with this approach is that legal queries are never one-dimensional.

When you ask "What are the notice periods in our 2024 service agreements?", a naive RAG system might pull semantically similar clauses from 2022. Without a reasoning layer, it lacks the common sense to apply necessary filters before searching.

This is why building production-ready legal assistants usually requires months of custom orchestration: managing conversation state, writing complex query logic, coordinating retrievers.

𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗦𝗲𝗮𝗿𝗰𝗵 changes this entirely.

When our finance team asked us to help navigate internal contracts, we used Weaviate's 𝗤𝘂𝗲𝗿𝘆 𝗔𝗴𝗲𝗻𝘁 to turn raw PDFs into a production app in 36 hours.

The agent treats the database as a set of tools rather than a static data store, autonomously handling:
• Schema inspection to determine the best search strategy
• Structured query construction with complex filters
• Precision reranking based on actual relevance
• Answer synthesis grounded in retrieved context

We embedded legal PDFs using ColQwen (a multimodal model that preserves layout and tables) with Muvera compression, split contracts into three collections by type, and let the agent handle all the orchestration we'd normally spend months building.

The architecture is more sophisticated than traditional approaches - but requires way less custom code.
→ In Search Mode, it retrieves and reranks relevant contract sections.
→ In Ask Mode, it synthesizes grounded answers with cited sources. Both modes stream results with full transparency to reduce hallucinations.

Read the full tutorial here: https://t.co/7hi2P1lixt

[Shubham Saboo @Saboo_Shubham_]

https://t.co/DCA4J7v16g

[Xavier Cabannes @XavierCabannes]

Je remets ce lien ici presque chaque semestre, mais il serait dommage que les étudiants passent à côté de cette mine de documents qu’est @GallicaBnF…

Le corpus Droit… doctrine « classique » et incontournable, jurisprudences, revues, etc. :

https://t.co/4DaFj7zNsE

[OpenClaw🦞 @openclaw]

🦞 OpenClaw 2026.2.21

♊ Gemini 3.1
🔒 Massive security hardening
🎙️ Discord streaming + voice channels
🧵 Thread-bound subagent sessions
📱 iOS/Watch polish + gateway stability
🧠 Prompt caching tweaks

100+ fixes shipped while Karpathy called us a noun https://t.co/ASUlwKiFMV

[World Bank Group @WorldBankGroup]

As @Lagarde notes: “If you have less labor force, you have less growth.”

Women, Business and the Law 2026 shows removing barriers to women’s economic participation could raise global output by up to 20%.

Feb 24 | 10:00–11:15 a.m. EST ➡️ https://t.co/Mlr2fHUo6E #WomenBizLaw

[maixtab @maixtab]

@heygurisingh CLAUDE

[Conseil d'État @Conseil_Etat]

https://t.co/yLwgj2VXY5

[Corey Ganim @coreyganim]

https://t.co/Qc9pzOMpaT

[Matt Schlicht @MattPRD]

🤖📈 Autonomous Agents Are The Fastest Growing Open-Source Technology In History

- But... what are autonomous agents?
- How do they work?
- How can you build or use one?

I wrote you the best overview on the planet.

Get ready for your mind to explode 🤯

https://t.co/YUrrlzGthO