Rituraj

GOODBYE MANUAL ADS REPORTING⚠️ CLAUDE CAN NOW CHAT WITH YOUR META ADS IN REAL TIME. BUT ONE WRONG MOVE GETS YOUR ACCOUNT PERMANENTLY BANNED. NO MORE EXPORTS. NO MORE DASHBOARDS. NO MORE "LET ME PULL THAT REPORT". Copy these 5 prompts — and the 5 rules that keep u safe:

Harvard just published a study in Science journal. AI diagnosed ER patients more accurately than real doctors. Not in theory. In an actual emergency room. With real patients. Here's what they found:

🚨BREAKING: Researchers just tested 13 frontier AI agents on real business workflows. The best one — Claude Opus 4.6 — passed 66.7% of tasks. No model broke 70%. Not a toy benchmark. Not a sandbox. Real business services. Real CRM systems. Real HR platforms. Real email. Real calendar tools. Real helpdesk software. Tasks that companies are actively trying to automate with AI agents right now. Here's the breakdown that should give every AI agent vendor pause. Local workspace tasks — fixing files, repairing code, editing documents — the agents handle reasonably well. Close to ceiling performance across the board. Business service workflows — the tasks that actually matter for enterprise automation — are a different story entirely. HR workflows: 6.8% average success rate across all 13 models. Not 68%. Not 6.8 out of 10. 6.8 out of 100. Management workflows: 0%. Every model. Every task. Complete failure. Multi-system coordination — tasks that require an agent to work across multiple connected business services simultaneously: consistently the hardest category. No model came close to reliable performance. Here's what makes this benchmark different from everything before it. Every existing agent benchmark freezes its tasks at release. The same 100 tasks. Forever. Agents get optimized against those specific tasks. The benchmark scores go up. The actual capability gap stays hidden. Claw-Eval-Live refreshes its task set based on real workflow demand signals — what businesses are actually trying to automate right now, pulled from ClawHub's top 500 most-requested skills. The benchmark evolves as real-world needs evolve. You can't game a benchmark that keeps changing. Here's the part most people will miss. Two models can have nearly identical pass rates and completely different actual utility. Models with similar 60-65% pass rates diverged substantially in overall task completion when you looked at which tasks they passed and failed. Leaderboard rank tells you almost nothing about which agent is actually useful for your specific business workflows. The only thing that matters is whether the agent completes the tasks your business needs. And on the tasks that run actual businesses — HR, management, multi-system coordination — no current AI agent is reliable. The gap between what AI agents are being sold as capable of and what they can actually do in a real business environment is documented, measured, and larger than anyone is admitting. HR automation. 6.8%. Management tasks. Zero. That's where we actually are.