Claude Opus 5.5 came out yesterday, and I think this is one of those AI releases that is very easy to underestimate.
You can open Claude, ask it to write an email, summarize a PDF, fix some code or research a topic. It will do all of that very well.
But I would not spend much time testing it that way.
There is something more interesting happening here.
Anthropic has made its strongest Opus model cheaper, faster and much better at staying with difficult work for longer. Suddenly, things that felt too expensive, too slow or too annoying to hand over to an AI agent start looking much more reasonable.
That is why I would pay attention to this release.
Not because Claude can answer better.
Because you can now give it much more to do.
The numbers are actually a big deal
Opus 5.5 costs $4 per million input tokens and $20 per million output tokens. Anthropic says a normal workload costs around 40% less than Opus 5, while the model produces output more than 30% faster.
It also has a 1 million-token context window, can produce up to 128K tokens in one response, and cached input now costs only $0.20 per million tokens.
Those numbers matter because serious AI work is becoming long.
A useful AI system may need to read your files, search the web, call tools, check a spreadsheet, change something, test it, find a mistake and try again.
Anthropic says one early tester used Opus 5.5 for a 680,000-line code migration in less than a day. Another tester left it working across six software repositories for more than 18 hours. GitHub says it completed more terminal tasks than Opus 5 while using less than half the steps in its testing. These are early tester results, not guarantees, but they show what Anthropic has built this model around.
And this is the part I think matters for normal users:
Stop thinking about Claude as one really smart answer.
Start thinking about what happens when Claude can keep working after the first answer.
That is where Opus 5.5 becomes interesting.
The full guide below breaks down the Opus 5.5 setup that actually matters: effort, Claude Code, Skills, subagents, memory, loops, automations, cheaper context and the prompt pattern that helps Claude keep working until the job is truly done.
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