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GPT‑5.6 took on a complex coding task spanning nearly 1,000 lines for Ankit Aich at Snorkel AI, handling the work from start to finish without repeated prompting or hand-holding.

OpenAI Developers

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62,062 次观看 • 6 天前 •via X (Twitter)

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📣 OpenAI Developers's GPT-5.6 family is now generally available and rolling out in GitHub Copilot. GPT-5.6 comes in three variants: ☀️ GPT-5.6 Sol: the highest reasoning ceiling in the family. Best for complex reasoning over large codebases and demanding, long-running agentic work. 🌎 GPT-5.6 Terra: the balanced default. A strong all-round choice for everyday interactive and agentic coding. 🌕 GPT-5.6 Luna: a lightweight, cost-efficient variant for smaller, faster tasks and the lowest-cost option in the family. Try one, two, or them all in Visual Studio Code or the GitHub Copilot app.

📣 OpenAI Developers's GPT-5.6 family is now generally available and rolling out in GitHub Copilot. GPT-5.6 comes in three variants: ☀️ GPT-5.6 Sol: the highest reasoning ceiling in the family. Best for complex reasoning over large codebases and demanding, long-running agentic work. 🌎 GPT-5.6 Terra: the balanced default. A strong all-round choice for everyday interactive and agentic coding. 🌕 GPT-5.6 Luna: a lightweight, cost-efficient variant for smaller, faster tasks and the lowest-cost option in the family. Try one, two, or them all in Visual Studio Code or the GitHub Copilot app.

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⚡️OPENAI: GPT-5.6 SOL IS 54% MORE TOKEN EFFICIENT ON AGENTIC CODING Sam Altman says the new GPT-5.6 Sol model is 54% more token efficient on agentic coding tasks and is “as good or better” than competing models. He also said OpenAI aims to offer better value with “every enterprise now is thinking about spend and the value they’re getting in exchange for AI.”

⚡️OPENAI: GPT-5.6 SOL IS 54% MORE TOKEN EFFICIENT ON AGENTIC CODING Sam Altman says the new GPT-5.6 Sol model is 54% more token efficient on agentic coding tasks and is “as good or better” than competing models. He also said OpenAI aims to offer better value with “every enterprise now is thinking about spend and the value they’re getting in exchange for AI.”

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❝ We make the world, as workers. No lights go on, none of the wheels on the railways turn, nothing gets made, without a worker putting their hand or brain to that task… We make the world work but it doesn’t work for our people. Mick Lynch dropping truth bombs at #TressellFest

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Anthropic’s Boris Cherny argues that for certain modern, model-friendly codebases, especially TypeScript/React projects, coding is already effectively "solved". AI agents can write nearly 100% of the code, while humans shift from hand-coding to directing, reviewing, integrating, and scaling many small PRs at once.

Anthropic’s Boris Cherny argues that for certain modern, model-friendly codebases, especially TypeScript/React projects, coding is already effectively "solved". AI agents can write nearly 100% of the code, while humans shift from hand-coding to directing, reviewing, integrating, and scaling many small PRs at once.

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.The Information Reporter Stephanie Palazzolo on OpenAI's GPT-5—a major step up for coding and what it means for competitors. "GPT-5 is a step up on a lot of different domains...one area that really stood out to [sources] was with coding." "Not only is GPT-5 better on more academic...tasks, but it's also better on the more practical programming tasks...working with very large and complex code bases." "If GPT-5 is going to be significantly better at these more practical everyday programming tasks, that could prove to be bad news for Anthropic." Watch the full episode on

.The Information Reporter Stephanie Palazzolo on OpenAI's GPT-5—a major step up for coding and what it means for competitors. "GPT-5 is a step up on a lot of different domains...one area that really stood out to [sources] was with coding." "Not only is GPT-5 better on more academic...tasks, but it's also better on the more practical programming tasks...working with very large and complex code bases." "If GPT-5 is going to be significantly better at these more practical everyday programming tasks, that could prove to be bad news for Anthropic." Watch the full episode on

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Your Ai twin, that you can put on your work table or at the bed side. With a working touch screen, can connect / cast to a TV. Creates a fully dynamic UI for the task at hand. Works with All your docs, Email, Slack & 5000+ apps. What would you use it for ?

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🤖 Introducing Taskade’s Autonomous Task Agents, now in Beta! Imagine an AI Agent creating tasks, adjusting timelines, and auto-prioritizing—managing your project from start to finish. Reschedule, assign, and keep workflows on track—all at once! For beta, reply ‘AI Project`

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GPT-5.6 vs GPT-5.5 on my custom spaceship prompt. I gave both models the exact same custom prompt. This is also the same prompt I previously gave to Fable 5. For context, GPT-5.6 Pro worked for 87 minutes, while GPT-5.5 Extra High worked for 34 minutes and 42 seconds. As I’ve said before, based on great authority GPT-5.6 will be an incremental/soldi improvement over GPT-5.5, not a “Fable killer.” My rough expectation has been that it would trade blows with Fable 5 on some benchmarks, maybe win around half depending on the category, but not clearly surpass it overall. And again fable five will have bigger model smell, but this was expected. After testing this coding output, that view feels pretty accurate. GPT-5.6 is clearly better than GPT-5.5 in several visual areas. The lighting, shading, chairs, object details, and exterior of the spaceship looked noticeably stronger. The scene was also easier to test. I do want to give GPT-5.5 credit though. It built out the rooms much much better and the planets looked better than GPT-5.6’s. It was also interesting that both GPT-5.5 and GPT-5.6 produced better-looking planets than Fable 5 in this specific test. The downside with GPT-5.5 was stability. The game was much glitchier and harder to test compared to GPT-5.6. But when it comes to the core of the demo, which is the spaceship itself, Fable 5 still beat both models pretty comfortably. GPT-5.6 is impressive, but from this test, it looks exactly like what I expected which was a meaningful incremental improvement over GPT-5.5, at least for indie game demos, but not something that replaces Fable 5. In collaboration with Chetaslua

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I Made a Game for my daughter based off of her favorite Teddy Bear and her as the main character. Took me about 30 minutes using Codex from OpenAI along with GPT Images 2.0. The Music is AI, the graphics AI and the entire code is AI. I have 0 coding experience other than HTML. The character looks just like her and the teddy bear is nearly exact to the picture I provided.

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Scale alone is not enough for AI data. Quality and complexity are equally critical. Excited to support all of these for LLM developers with Snorkel AI Data-as-a-Service, and to share our new leaderboard! — Our decade-plus of research and work in AI data has a simple point: scale alone is not enough. AI success is all about the quality, complexity, and distribution of data—in addition to volume. We’re excited to be powering leading LLM developers with Snorkel AI Expert Data-as-a-Service, our white glove service for custom, expert-level AI datasets—and to now preview some of what we’re building via our new Expert Data Leaderboard (🔗 in 🧵) + upcoming OSS dataset releases! Snorkel Expert Data-as-a-Service is built to meet the rapidly evolving data needs of the agentic AI world—where success is built on the quality, complexity, and distribution of datasets, in addition to size and scale. This kind of high-quality, frontier AI data can only come from a union of technology and human expertise. With Snorkel Expert Data-as-a-Service, we’re powering frontier LLM developers across agentic, expert knowledge, reasoning, coding, multi-modal, and other task types via the combination of these two key components: - (1) The Snorkel Expert Network: A global team of subject matter experts focused wholly on specialized knowledge–spanning thousands of topics in STEM/academic, vertical/professional, and consumer/lifestyle domains. - (2) Snorkel AI Data Development Platform: Our unique programmatic data curation and quality control platform, accelerating and improving expert authoring and review through principled techniques developed over the last decade of R&D. Now: we’re incredibly excited to showcase some of the power of Snorkel Expert Data-as-a-Service via the new Snorkel Leaderboard—putting frontier models to the test in complex, agentic, and reasoning settings inspired by real industry scenarios (not esoteric puzzles)! We’ll be releasing new leaderboards and accompanying expert-verified open source datasets (coming soon!) regularly. To start, we’re sharing three initial ones in preview: - SnorkelFinance: Q&A over financial documents requiring agentic tool-calling and reasoning - SnorkelUnderwrite: Agentic insurance tasks requiring industry-specific reasoning and tool use - SnorkelSequences: Mathematical tasks requiring compositional multi-step reasoning

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