Introducing the Agent OS Email Module by olla4.com. This module turns customer email handling into a controlled AI workflow, not just a chatbot. It includes: - Inbox sync and CRM pipeline - Email/thread understanding with intent, urgency and category detection - Multi-agent routing to the right specialist - Context-aware draft generation based on company rules, previous cases and memory - QA, risk, refund, cancellation, return and support checks - Human approval by stage when needed - Agent training from approved replies, corrections and resolved cases - Audit trails, safety rules and continuous improvement The system can work in three modes: Human approval, hybrid automation, or fully autonomous workflows for approved cases. Built for real business operations, including workflows, where speed matters but control, accuracy and accountability matter even more. Agent OS is not replacing humans. It is giving small teams an operational AI layer that can read, decide, draft, learn and improve.

🚨 JAILBREAK ALERT 🚨 ANTHROPIC: PWNED 🫡 FABLE-5: LIBERATED 🦋 let's start with the 🐘... the consensus seems to be that this has been one of the most disappointing model drops of all time, effectively preventing legitimate researchers from contributing their talents to our collective advancement. and not just because of what it means for the short-term, but for what these decisions signify for the long-term. but despite this overly sensitive, authoritarian "safety" layer on top of Mythos, my lil liberators have been hard at work—mapping the boundaries, probing the depths of long-context convos, and cleverly finding the holes in the fence that the thought police missed 🤗 we got some cyber, some chem, some psychological manipulation, and some good ol' fashioned explosives! it took many attempts from multiple agents hunting as a pack, during which I observed a combination of techniques across: • Unicode, homoglyphs, Cyrillic, and other Parseltongue-style text transforms • Long-context reference tracking • Taxonomy and document-structure reasoning • Fiction and narrative framing • Academic-review style contexts • Intent-classification inconsistencies but perhaps the most effective is decomposition recomposition in the backend. it's hard to get explicit names of harms like "Meth Recipe," but getting uplift on the process itself, like birch reduction method/reductive-amination (classic meth synthesis pathways), is much more doable. defense becomes much more difficult to maintain when you start throwing in out-of-distro tokens, breaking up the harmful uplift into benign chunks, and then piecing the innocuous-seeming facts back together, especially when you have jailbroken Opus helping you do it 😉 gg

Finally, the workflow feels right. Finally, I found the workflow that feels like the right operating system for AI development. My new setup combines VS Code Remote SSH, Codex, Headroom, Gitea/Git, and multiple parallel coding sessions into one powerful development environment. Headroom is the key layer that makes the workflow more efficient: it compresses tool outputs, logs, files, and context before they reach the LLM, helping reduce token usage while keeping the answers useful and accurate. Together with Codex and remote VS Code sessions, this gives me a real AI-powered development cockpit: multiple coding agents, remote environments, Git-based control, live token visibility, rate-limit awareness, cost savings, faster reviews, and cleaner execution. For me, this is not just “AI-assisted coding”. It feels like a new way to build software — faster, more structured, more controlled, and much closer to how AI-native development should work. This combination finally gives me the environment I was looking for. #AI #Coding #Codex #VSCode #Headroom #DeveloperTools #AIAgents #Automation #SoftwareDevelopment #OpenSource #Git #RemoteDevelopment #Productivity #BuildInPublic #Oll4 #Oll4Com

claude fable 5 is on par with gpt-5.5 on DeepSWE fable 5: 70% success rate at $10.3/task gpt-5.5: 70% success rate at $6.6/task opus 4.8: 58% success rate at $12.6/task @datacurve hasn't officially released the mythos 5 scores yet, but @theo somehow shared them on his youtube channel

Claude Fable 5 is insane, one prompt built an entire fantasy world with smooth movement and spells.

Just used claude fable (aka mythos) to create this city block simulator complete with multi-agent traffic, live detection boxes tracks, and day to night cycle. And it just one shotted it. This is gonna be fun -- the gap between idea and execution just keeps collapsing.

Claude Fable 5 vs Opus 4.8 👀

Data-first vs. AI-first I’m a big supporter of AI adoption. But I have to say, the strongest AI systems still start with one thing: Data AI can create the output. Data decides whether that output is useful. If your data is: - fragmented - low quality - poorly structured Then your AI will be: - inaccurate - unreliable - impossible to scale Before adopting AI at scale, it is worth understanding the data layer behind it. The best companies are not just AI-first. They are: Data-first → AI-enabled AI is the top layer, not foundation. Data is.

GPT-5.6 is not coming as an update. It is coming like a reset. Mythos had the throne. Now GPT-5.6 Thinking enters the battlefield. Is this the end of Mythos… or the beginning of the biggest AI war yet? Choose your side 👇 #AI #GPT56 #Mythos #ArtificialIntelligence #AIAgents

Anthropic will release tomorrow the model it previously said it wouldn't release. Two weeks ago, Anthropic said it had no plans to publicly release Mythos. Tomorrow, that may change. Anthropic will release a public version of its cybersecurity model under the name Claude Fable 5. That matters because Mythos was initially made available only through Project Glasswing to a limited group of vetted organizations. Anthropic's reasoning was straightforward: The industry lacked sufficient safeguards against misuse. Mythos was designed to excel at cybersecurity tasks, including discovering software vulnerabilities, identifying attack paths, and potentially uncovering zero-day exploits at a level that reportedly exceeds many human security professionals. That's the dilemma. The same model that helps defenders find vulnerabilities before attackers do can also help attackers find them faster. Now Anthropic appears ready to test a different approach. Instead of restricting access, Claude Fable 5 is expected to introduce new guardrails designed to preserve the model's cybersecurity strengths while reducing the risk of abuse. Early feedback suggests the capabilities remain significant. The real question is whether companies can safely release models powerful enough to find vulnerabilities that humans have missed. Anthropic may be about to find out. #AI #GenAi #Anthropic #Cybersecurity

Introducing the Agent OS Email Module by olla4.com: AI email workflows with inbox sync, CRM pipeline, intent detection, multi-agent routing, smart drafts, QA/risk checks, human approval, audit trails and training from resolved cases. Built for real operations.

Time for another reset? 😅