And we'll roll in those cameras. >> Great. Thank you.>> Yeah. >> Hey everyone, I'm Roma. We've been steadily improving Codex to make it feel like a more capable and reliable coding collaborator.And for us, it's very important for Codex to be everywhere you work. And that's why we launched an ID extension. You can now have codeex right in your code editor, whether it's like VS Code, Cursor, Windsor, or many others.And with me today, I have Gabriel, engineering lead on the extension to give us a quick tour. W ...

Product Updates & Features - Codex CLI has been improved with updates to GP5 and GP5 codecs, enhancing agentic coding capabilities [1] - Codex CLI can be easily installed with npm or brew and logged in with a Chat GPT account [2] - The new GPT5 Codex model is highly effective for various coding tasks [3] - The model switcher feature allows users to select different models for different tasks, optimizing reasoning level [5] - Codex offers sandboxing features with three modes: read-only, auto (default), and full access, controlling file access and modifications [6][7] - Codex resume allows users to continue from previous sessions [8] - Codex can be used for deploying applications and debugging by analyzing logs and disparate data sources [9][10] Deployment & Usage - Codex can deploy applications on platforms like Versal, utilizing code search to fetch the latest documentation [11] - The demonstration showcased Codex CLI modifying a game to implement a multiplayer feature in real-time [12][13] - Codex CLI supports a wide variety of languages, frameworks, and projects [14] Accessibility & Availability - Codex CLI is designed to be an AI teammate accessible wherever users work, directly in the terminal [15]

Responses API Overview - OpenAI introduced the Responses API to evolve beyond the Chat Completions API, addressing design limitations and enabling new functionalities for building agentic applications [1] - The Responses API combines the simplicity of chat completions with the ability to perform more agentic tasks, simplifying workflows like tool use, code execution, and state management [1] - The core of the Responses API is an agentic loop, allowing multiple actions within a single API request, unlike Chat Completions which only allows one model sample per request [2] - The Responses API uses "items" for everything, including messages, function calls, and MCP calls, making coding easier compared to Chat Completions where function calling was bolted onto messages [2] - The Responses API is purpose-built for reasoning models, preserving reasoning from request to request, boosting tool calling performance by 5% in primary tool calling eval tobench [2] - The Responses API facilitates multimodal workflows, making it easier to work with images and other multimodal content, including support for context stuffing with files like PDFs [2] - Streaming is rethought in the Responses API, emitting a finite number of strongly typed events, simplifying development compared to Chat Completions' object deltas [2] - Long multi-turn rollouts with the Responses API are 20% faster and less expensive due to the ability to rehydrate context from request to request, preserving the chain of thought [2] Agent Platform and Tools - OpenAI is changing deployment with its agent platform, centering on the Responses API and Agents SDK for building embeddable, customizable UIs [3] - Agent Builder and Chatkit, built on the Responses API, make it easy to build workflows into applications with minimal effort [3] - The Responses API is at the core of the improvement flywheel, enabling distillation and reinforcement fine-tuning using stateful data, along with tools like web search and file search [3]

Heat. Heat. Heat. Heat. Heat.Heat. Hey chat GPT, prep me for my meeting tomorrow. Heat. Heat. ...

No city embraces the future like San Francisco. Get inspired by local developers using AI to tackle real challenges: making SF services work, improving housing options, and strengthening community. ...

Great to have you here. Hi everyone. I'm Chad Nelson. I'm a creative director here at OpenAI.Stop. Stop. Stop.We'll keep it casual, but no, this is going to be a fun talk. Uh so in my career I've made a lot of content, films, video games, television shows and in all my experiences there's been one common kind of through line which is how am I going to make it. How am I going to make this stuff ultimately like what are my creative workflows that I need. What are the tools I'm going to use. And so what happen ...

Model Style Definition & Importance - Model style encompasses values (what models should/shouldn't do), traits (curiosity, warmth, conciseness), and flare (emojis, m-dashes), which together form demeanor [8] - Style matters because it shapes user experience, influencing how people perceive and trust the model, shifting usage from simple search to collaboration [9][10][11] Model Style Development - Model style is primarily set by pre-training (corpus defining knowledge and voice), refined by fine-tuning (adding tone, guardrails), and shaped by user prompts and app settings [12][13][16] - User prompts significantly influence model response style, with personalization features like memory further tailoring the style over time [14][15] Challenges & Considerations - Consistency in style is a major challenge because large language models approximate patterns rather than execute rules, making alignment difficult [27][28][31] - The company balances maximizing user autonomy and freedom with minimizing harm, setting default behaviors that users and developers can override within safety policies [23][24][25] - There is no single style that works for all users; the company aims to provide choice and flexibility for models to adapt to different contexts and needs [26][27] Future Directions - The company is focused on steerability, aiming to improve how well models follow customization requests for managing traits and flare [34][35] - The company aims to improve contextual awareness, enabling models to shift tone appropriately based on the user's context [36] - The company prioritizes AI literacy and accessibility, striving to make style management simple and intuitive for all users [37]

I'm >> here at OpenAI and I build Codex. With Codeex, we're building an AI software engineer. I personally like to think about it as a little bit like a human teammate.You can pair program with it on your computer. You can delegate to it or as you'll see, you can give it a job without explicit prompting. There's been recently a massive vibe shift.This has started from August where we had pretty decent usage and since then, thanks to all of you, we've grown tenfold. Today I want to start by sharing some of t ...

Earlier this year, a tweet went viral with a new term, vibe coding. Now, it got a lot of polarizing reactions, but I think one thing we can all agree on is it really changed the way we saw how AI was going to transform software engineering and how products are built. But we're not here today to talk about buzzwords or hype or what might be possible.Today, we are here to show you startups that our team has been working closely with and we have seen firsthand how their AI coding tools have helped tiny teams 1 ...

Internal AI Application Strategy - Focus on amplifying expertise with AI, not just driving efficiency, by capturing and distributing the knowledge of top performers across the organization [4][5][6] - Internal applications can significantly improve a company's agility and impact, potentially by 10x [4][7] - Building internal AI tools should be integrated into existing workflows and systems, ensuring ease of use and feedback [68] - Encourage a sprint-based approach: identify top operators, build within familiar tools, and leverage scalable platforms like Agent Kit [67][68][69] Go-to-Market Assistant (Sales) - The Go-to-Market Assistant enables sales representatives to deliver optimal customer engagement by providing quick customer research and technical answers [14][20] - By implementing the Go-to-Market Assistant, sales representatives reported saving one full day per week, which they can now dedicate to higher-value tasks [35] - The Go-to-Market Assistant exchanges approximately 20 messages per week with each sales representative [35] Openhouse (People/HR) - Openhouse helps employees quickly understand company operations by centralizing access to information on policies, announcements, and personnel [39][40] - Approximately 75% of employees use Openhouse every week, indicating high adoption and utility [53] Support System - The support system autonomously handles or deflects approximately 70% of support tickets [62] - The new support system outperforms the legacy system by approximately 30% [62] - Approximately 80% of tickets handled by the automated system are rated as highly positive by a QA team [63]