Shadowing Practice: Introducing the Agents API - Learn English Speaking with Video

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Getting a long-running agent into production takes a lot of work, even with a capable model.
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You need to connect tools, track progress, manage context, and secure and maintain the infrastructure around it.
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Today, we're launching the Agents API to handle that infrastructure for you.
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The Agents API brings a hosted version of the Codex Harness to your applications.
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OpenAI handles orchestration, sessions, and context management so that you can stay focused on building.
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Let's look at an example.
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Suppose we want to build an agent that helps investigate incidents in our production stack.
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It would need access to observability data and recent code changes, along with our team's instructions for how to handle an outage.
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We can connect all of our necessary tools through MCPs and give the agent our investigation runbook via a skill.
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You control the agent's execution environment and the tools it has access to.
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That includes connecting a sandbox, whether it's through through OpenAI, a third party provider, or using your own infrastructure.
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In a situation like this, we'd also be working through a ton of logs, likely more than we could fit in the model's context window.
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With programmatic tool calling, the agent can process those logs and filter the results in code,
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meaning fewer tokens spent passing around raw data and more spent on the information the agent needs.
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For the largest tasks, independent work can be delegated via multi-agent orchestration.
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In this case, we might want one sub-agent to examine recent changes, another to check telemetry, and then have the lead agent unify their findings.
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But even in a single agent session, long-running context windows still work really well with compaction.
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It gives the model a summary of all prior work completed so the agent can continue its investigation.
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Once the work is complete, the findings should be served as a report that the on-call team can review, a likely root cause, the supporting evidence,
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and suggested next steps bundled into a single shareable file.
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And there we have it.
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With the agents API, we were able to drive an entire workflow without building or maintaining any of our own agent infrastructure.
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Infrastructure that will continue to get better alongside new models and new capabilities.
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We're excited to bring you an ever-improving harness behind one API.
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Happy building.

About This Lesson

You're practicing English with "Introducing the Agents API" using the Shadowing technique — a method originally developed for professional interpreter training.

Focus on sounding like the speaker — not just repeating words. With 15–30 minutes of daily practice, you'll build real-world speaking confidence.

What is the Shadowing Technique?

Shadowing is a science-backed language learning technique originally developed for professional interpreter training and popularized by polyglot Dr. Alexander Arguelles. The method is simple but powerful: you listen to native English audio and immediately repeat it out loud — like a shadow following the speaker with just a 1–2 second delay. Unlike passive listening or grammar drills, shadowing forces your brain and mouth muscles to simultaneously process and reproduce real speech patterns. Research shows it significantly improves pronunciation accuracy, intonation, rhythm, connected speech, listening comprehension, and speaking fluency — making it one of the most effective methods for IELTS Speaking preparation and real-world English communication.