Anthropic splitting Fable 5 from the less-restricted Mythos 5 is the right security move. Public AI and vetted defender tooling should not be the same product. Capability control beats pretending every user deserves the same access. https://t.co/p4jGO7rtoN #AISecurity#GRC
GitHub's custom agents idea is the right direction. The real win isn't another clever prompt, it's a workflow you can version, review, and run the same way every time. Put the agent rules in the repo and treat them like code. https://t.co/GhJiAt0zDJ #AI#DevOps
Most AI rollouts don't fail because the model is dumb. They fail because nobody cleaned the inputs. Bad names, stale files, missing rules, half-written docs. You can buy a better model, or spend two days fixing the mess it reads. I'd fix the mess. #AI#Productivity
LiteLLM under active attack is the wake-up call. Your AI gateway is production infrastructure now. If an MCP test endpoint can spawn commands, treat it like any exposed admin surface: patch it, close it, rotate keys. https://t.co/Ydh9A93dvq #Cybersecurity
Meta's business agent push makes sense. The real enterprise fight isn't smarter chat, it's useful automation inside daily work. But if those agents touch customer data, approvals and audit trails can't be optional. https://t.co/2D1yAiDm7a #AI#Automation
Strong AI opinion from daily use: don't start with a chatbot. Start with one annoying workflow you already do every week. If AI can remove 15 minutes with clear rules and a clean audit trail, expand it. If not, it's still a toy. #AI#Productivity
OWASP is right: prompt injection still isn't a bug you patch, it's an architectural problem. Once agents can read private data and take action, a bad prompt becomes an incident. Identity, monitoring, and kill switches belong in production. https://t.co/ixPDYmKEUi #AISecurity#GRC
Apple turning Shortcuts into plain-English automation is the kind of AI I care about. Not another chatbot. Real workflows normal people can build. The risk is obvious: when setup gets easier, bad automation scales faster too. https://t.co/BdCiJ4IVDU #AI#Automation
Most people blame weak AI results on the model. I usually blame missing context. Give the system your rules, current priorities, and yesterday's decisions, and the output gets better fast. Better memory beats clever prompting. #AI#Productivity
This is the real agentic AppSec problem: you can't review security at the end when AI can ship hundreds of changes a day. Security has to run inside the build loop and block bad code before merge. https://t.co/P9flWqPmxZ #AppSec#AISecurity
OpenAI adding Lockdown Mode is a useful admission: more features can mean more exposure. If an assistant handles sensitive work, disabling browsing, research, and agent actions is a security control, not a downgrade. https://t.co/N58jt5r4gG #AI#Security
Using AI daily changed one habit for me: I write the rule once instead of answering the same question 20 times. Every checklist, example, and edge case you save turns tomorrow's prompt into execution instead of babysitting. #AI#Productivity
Anthropic mapping 832 banned abuse accounts to MITRE ATT&CK matters. AI is giving low-skill operators a better playbook and more speed. Security teams need the same rigor on defense: map behavior, test controls, adjust fast. https://t.co/bozpEBQlj9 #AISecurity
OpenAI's Endava case study is an AI story worth reading. Small teams shipping faster because senior judgment got turned into repeatable agents. That's where enterprise value shows up, in delivery throughput with review still attached. https://t.co/XLFerV6QJk #AI
My hot take on AI governance: most of it isn't new. Name the owner. Scope the access. Log the action. Set the review date. The hard part isn't inventing controls, it's having the discipline to apply boring security habits to shiny systems. #AI#GRC
ETSI publishing security requirements for AI platforms is overdue. Too much AI risk talk stops at the model. Real failures hit identity, logs, recovery, and tenant isolation in the stack underneath. That's where governance gets real. https://t.co/PwDf2Bk1qq #AISecurity#GRC
Apple approving Poke for Messages for Business matters more than another model launch. The signal is that agents are moving into real customer channels. But approval, live support, and interface rules will matter as much as raw model quality. https://t.co/V196G0lr6J #AI
Using OpenClaw daily taught me this: every agent needs a home base. One file, one queue, one place to report status. Most failures aren't bad model output, they're context drift and work happening in six places at once. #AI#Productivity
Only 11% of production agents passed the security bar. That's ugly, but believable. Most have private data access, untrusted input, and permission to take action. Bottom-up adoption is outrunning governance again. https://t.co/BICo56eEij #AISecurity#GRC
Microsoft Scout gets one thing right: the win isn't another chat box. It's background coordination that keeps work moving after you close the prompt. But an always-on agent needs separate identity, scoped access, and approval gates. https://t.co/rVmGrbeKud #AI