a 9b model went from solving 19 to 49 out of 100 puzzles it had never seen, just by training its weights.
that's the result from continual-arc, a new benchmark from @letsunifyai that tests whether ai actually learns on the job.
memory files help a model remember. training the weights is what made it generalize to new tasks.
memory and trained weights together look like the path to agents that get better every day they work.
The future of collaboration looks like humans and agents working as true teammates.
Now, see your @Atlassian work in Claude. Co-edit a @Confluence Page. Brainstorm on a @Confluence Whiteboard. Seamlessly move forward your @Atlassian context with @claudeai. All GA this week.
Apply sensitivity labels to critical files so they’re automatically protected in workflows and AI interactions. Watch here. https://t.co/yq9QN7FZRA
Take control of your data by discovering sensitive information across every file type and location with Microsoft Purview Information Protection.
Classify your data, apply clear labels, and enforce protections that automatically adapt to human and AI interactions so you can reduce risk without slowing down workflows. #MicrosoftPurview #SensitivityLabels #InformationProtection
Graphon, which wants to resolve AI agent memory limitations by mapping connections across documents, videos, and images, raised a $35M Series A (Shubhangi Goel / Business Insider)
(Visit Techmeme dot com for the link and full context!)
Anthropic engineers shared a blueprint for building reliable agent automations
it includes the code + memory + guardrails + failure handling + the entire run loop
i mapped the system into one map so you can steal the workflow
save this before you build your next AI agent ↓
MQTT broker access control mechanisms enable independent governance. You can define which clients publish to specific namespace topics and which can subscribe. #highbyte_iiot
Note: Video generated by AI.
Let your AI agent inspect Proxmox before you let it change anything.
Proximo is a Model Context Protocol (MCP) server for builders connecting AI agents to their Proxmox infrastructure.
It helps you investigate cluster issues and manage changes by letting an agent read status, preview a proposed change, and record what happened through one interface.
Key features:
• Four-product support – connects to Proxmox VE, Backup Server, Mail Gateway, and Datacenter Manager
• Read-only by default – start with inspection before granting write access through a scoped token
• Change previews – see the live target, proposed change, and blast radius before confirming a mutation
• Tamper-evident audit ledger – keyed, hash-chained records let you check whether recorded actions were altered
• Snapshot-first container commands – opt in to taking a snapshot before a risky command; execution is refused if that snapshot fails
Token permissions still matter, and risk ratings are advisory—not a sandbox. Review changes yourself.
It’s open-source (Apache-2.0 license).
Link in the reply 👇
THIS IS THE MOST UNDERRATED SETUP IN GROK BOT
Most people open Grok Bot, ask one question and close the tab.
The idea: one Grok Bot already has 20 tools built in. Split them across 7 bots, give only one of them a clock, and the team runs itself.
here's the split:
→ Scout gets X, GitHub and the browser, and scans every Monday at 9:00
→ Pain Miner gets memory, and turns complaints into scored themes
→ Judge gets nothing but the scores, and says GO or KILL
→ Builder gets GitHub and a full Linux box, and ships one PR
→ Pitch gets video gen, image gen and pages
→ Buyer gets price compare and the vault, and waits for my OK
→ Inbox gets the email inbox, with +bugs and +press aliases
The setup pays off at three moments:
→ Monday 9:00, when 1 clock wakes the whole chain
→ a KILL, when a bad idea dies before Builder writes a line
→ checkout, when nothing is paid without me
Scout finds. Judge filters. Chief approves.
7 hourly bots would burn 1,176 runs a week. this team does about 60.
the full wiring, bot by bot, is in the article below ↓
At Fintech Forward in Bahrain, His Excellency Arthur Mattli, Ambassador of Switzerland to the UAE and the Kingdom of Bahrain, discusses where the two countries can work together in fintech, what each market offers companies looking to expand, and how both approach regulating new financial technologies.
Watch the full interview: https://t.co/DFZRerabuO
#FintechForward2026 #FintechForward #ForbesMiddleEast #BahrainEDB #Fintech #Bahrain
Agentic RAG Interview Questions — Save This!
Preparing for an AI/GenAI interview? Don’t stop at “What is RAG?”
Interviewers increasingly test whether you can design and operate RAG systems.
Here are the areas you should be ready for 👇
🟢 Fundamentals
• Agentic RAG vs Traditional RAG
• Why use agents in RAG?
• Key components
🟡 Architecture
• Query decomposition
• Multi-hop retrieval
• Tool selection
• Hybrid search & reranking
🔴 Production
• Preventing infinite tool loops
• Reducing latency & LLM cost
• Prompt-injection protection
• Document-level access control
⭐ The #1 System Design Question:
“Your traditional RAG handles simple questions but fails on complex, multi-step queries. How would you transform it into Agentic RAG?”
Think:
Query → Plan → Tool → Retrieve → Rerank → Reflect → Retrieve Again → Answer → Cite → Validate
📌 Save this before your next AI interview.
Follow @gauravgoyalai for practical AI, GenAI & LLM engineering content.
#AgenticRAG #RAG #GenerativeAI #GenAI LLM AIEngineering MachineLearning ArtificialIntelligence AIEngineer TechInterview AIInterview RAGPipeline
Under Nadir Ben Sami Al-Koraya’s leadership, Saudi Arabia-based Riyad Bank has expanded its sustainable finance initiatives to support renewable energy and sustainable development. In 2025, the bank exceeded its original $5.3 billion sustainable finance target, reaching approximately $8.3 billion in eligible corporate financing, and raised its target to around $16 billion by 2030. In January 2026, Riyad Bank issued a $1 billion sustainability bond.
Full list link:
https://t.co/Zdmiv82sU2
📸: Illustration by Ali Darwish via OpenAI ChatGPT
@Nadir_AlKoraya@RiyadBank
#forbes #forbesmiddleeast #SustainabilityLeaders2026
🚀 Protect your apps from AI reverse engineering!
BLA adds fake keys, bait APIs & decoy logic to confuse AI analyzers, waste their tokens, and protect your original runtime.
Verified on 14 benchmarks.
GitHub: https://t.co/MwAdB2eDVW
before you add another rule to your CLAUDE.md, run this command.
claude code might be following outdated instructions, conflicting rules, or references to files that no longer exist.
and every time you try to fix its behavior by adding another rule, you could be making the mess even bigger.
anthropic has a command to help you clean it up:
/doctor prompt-audit
here’s how to use it:
1. update claude code
run claude update in your terminal.
you need version v2.1.283 or newer.
2. run the audit
open claude code in your project and enter:
/doctor prompt-audit
3. let it inspect your instructions
it checks supported instruction files, including:
→ CLAUDE.md and AGENTS.md
→ project and user-level instructions
→ rules, skills, and commands
→ outdated file references
→ conflicting or obsolete guidance
4. review the proposed fixes
claude identifies potential problems and suggests edits. review the reasoning before applying any changes.
want to audit just one skill?
/doctor prompt-audit .claude/skills/deploy
you can target a specific file or directory instead of checking everything.
here’s something worth remembering:
anthropic recommends keeping each CLAUDE.md under 200 lines.
the more your instructions grow, the easier it becomes to accumulate outdated rules and conflicting guidance.
sometimes, the best way to improve claude code isn’t to teach it something new. it’s to remove what no longer makes sense.
🔖 save this for your next claude code cleanup.
official documentation: https://t.co/8m761d8RMp