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AI / Core OpenAI Codex Application Fundamentals Interview Questions

What is OpenAI Codex and how has it evolved from its original form?

OpenAI Codex began as a language model specifically trained for code generation, first released in 2021 as the engine behind GitHub Copilot. Over time, "Codex" evolved into something broader: OpenAI's agentic software engineering platform - a cloud-based coding agent that performs end-to-end software tasks rather than just generating snippets in response to prompts.

Today Codex refers to a complete product suite:

Modern Codex components
ComponentDescription
Codex AppDesktop and web command center for agentic coding sessions
Codex CLIOpen-source command-line tool for terminal-native agentic coding
Codex IDE ExtensionIntegration into VS Code and other IDEs
Codex CloudCloud-hosted agentic environment accessible from web/mobile
Codex SDK/APIProgrammatic access via the Responses API

The models powering Codex have also advanced substantially. Early 2025 introduced codex-1 (a version of o3 optimised for software engineering). By mid-2026 the recommended models are from the GPT-5.x family - primarily gpt-5.5 and gpt-5.4 - which unify reasoning, coding specialisation, and general intelligence in a single model line.

The architectural shift is fundamental: Codex evolved from a passive completion model ("give me code") into an active agent that reads repositories, writes and runs code, fixes test failures, and opens pull requests - operating more like an autonomous colleague than a syntax autocomplete tool.

What is the primary purpose of OpenAI Codex as it exists in 2026?
What was codex-1, announced when Codex launched as an agent product?

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What is OpenAI Codex and how has it evolved from its original form? What are the current recommended models for OpenAI Codex and the API, and when do you choose each? What is the OpenAI Responses API and how does it differ from the Chat Completions API? What are the built-in tools available in the OpenAI Responses API? What is the OpenAI Agents SDK and what are its four core primitives? What is the Codex CLI and what are its key features? What is the Chat Completions API and when should you still use it? What is function calling (tool use) in the OpenAI API and how does it work? What are structured outputs in the OpenAI API and how do you use them? What is the OpenAI Assistants API and what is its deprecation timeline? What is prompt caching in the OpenAI API and how does it reduce costs? What are reasoning models in the OpenAI API and what is the 'effort' parameter? What are OpenAI's key API authentication and security concepts? What are rate limits in the OpenAI API and how do you handle them in production? What is the Batch API and when should you use it? What is streaming in the OpenAI API and how do you implement it? What is OpenAI's Codex Skills feature and what are Automations? What is Model Context Protocol (MCP) and how does it integrate with OpenAI tools? What is fine-tuning in the OpenAI API and when should you use it? What are embeddings in the OpenAI API and what are they used for? What is the OpenAI moderation API and why is it important for application safety? What are OpenAI's image generation models and how do you use them in applications? What is the OpenAI Realtime API and what use cases does it enable? What is retrieval-augmented generation (RAG) and how do you implement it with OpenAI? What is OpenAI's approach to responsible use and safety in the API? What is the OpenAI token system and how do you count and optimise token usage? What are guardrails in the context of OpenAI application development? What is the OpenAI Files API and how is it used for document management? How do you implement multi-agent systems using the OpenAI Agents SDK? What is the OpenAI Evals framework and why is evaluation critical for production applications? How do you implement error handling in OpenAI API applications? What is the OpenAI Codex App and what are its main features for software teams? What are the key differences between OpenAI's o-series reasoning models and the GPT series? How does the Codex IDE extension integrate with development environments? What are the key considerations for building production-grade OpenAI applications? What is the OpenAI Codex and API pricing model and how do you estimate costs? What is the OpenAI computer use capability and what does it enable? How do you use the OpenAI API for code generation, review, and debugging tasks? What is the role of system prompts (instructions) in OpenAI applications and how do you design them effectively? How do you handle context window management in long-running OpenAI applications?
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