Yesterday was a reminder that we’re still in the early days of AI-as-infrastructure.

What happened (quick recap)

Anthropic’s Claude experienced a prolonged outage that lasted most of the day. For a lot of us, that meant workflows stalled, automations failed, and “just ask Claude” suddenly wasn’t an option.

In my case, it was worse than just downtime: my Claude Max plan got maxed out during the outage window, and support couldn’t resolve it. So even when service appeared to be coming back, I was still blocked.

I’m not writing this as a hit piece. Outages happen. But it did expose a real operational risk: single‑vendor dependence.

My impact

• Claude Max usage got maxed out during the outage
• Support couldn’t help in a useful timeframe
• A big chunk of my day evaporated waiting on a tool I treat as critical

The lesson: AI needs redundancy

If AI is part of your daily workflow (coding, writing, research, ops), you need at least two options that you can switch between quickly. Treat it like any other piece of infrastructure: no single points of failure.

That means:

• Have a backup model you can use immediately (OpenAI, Gemini, local models, etc.)
• Keep prompts/flows portable so you’re not locked to one tool’s UI
• Know your escape hatches before you need them

The lesson is boring but real: resilience beats convenience.

Closing thought

This outage didn’t change my belief in AI. It changed how I plan around it. We’re building on shifting ground. Until the foundations stabilize, redundancy isn’t a nice‑to‑have — it’s table stakes.