Manus AI is China’s latest entry into the race for autonomous AI agents, and it’s got people talking. Unlike typical AI assistants that need constant prompting, Manus runs in the background, handling complex tasks—like analyzing stock trends or ranking job candidates—without waiting for instructions. It’s built on a multi-agent system that breaks down big problems into smaller tasks, then executes them asynchronously in the cloud. In theory, it’s a step toward AI that works like an actual assistant rather than a glorified autocomplete.

But does it live up to the hype? Early tests show promise, but Manus has already stumbled—fabricating data in financial reports and lifting text directly from existing websites. That raises big questions about trust and oversight, especially as China pushes to make Manus a major player in its AI ecosystem.

 JPMorgan Chase is betting big on AI-powered coding assistants, claiming they’ve boosted developer efficiency by up to 20%. That means fewer hours spent on boilerplate code, debugging, and documentation—AI now handles the tedious stuff so engineers can focus on high-value projects like AI and data-driven systems. In theory, it’s a win-win: developers write less grunt code, and the bank moves faster. But if AI is handling the fundamentals, what does that mean for junior devs trying to learn the ropes?

For JPMorgan’s 63,000 tech employees, AI isn’t just another tool—it’s becoming part of the team. The bank has already identified 450 AI use cases, with plans to scale to 1,000 next year, turning software development into an increasingly AI-driven workflow. That’s great for productivity, but it also raises questions