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12 results for Context engineering
Article URL: https://twitter.com/AgentMemoryL/status/2101312784688726331 Comments URL: https://news.ycombinator.com/item?id=49797488 Points: 1 # Comments: 0
Using GPT-5.6, V7 turns scattered company files into context agents can use to complete complex, source-linked work.
Fyxer uses OpenAI models, fine-tuning, memory, and real user feedback to organize inboxes and draft emails in each user’s voice.
Every company I see has an automated code review agent set up in their repository. It doesn't solve the code review problem. The automated review agents cannot be trusted the same way coding agents cannot be trusted. They're very useful for finding bugs and edge cases you've missed, but they lack something only you have — "taste." You have more context. You know the people, the business, and the product better than any coding agent. You know when an abstraction is unnecessary. You know what needs a comment. You know where to break the rules. And, for that... Nothing beats "reading" the code. Problem is, reading code is not easy. It's even harder if your tools are designed for storing code rather than reading it. That's why I built Guided Review. It's a chrome extension that converts your Github PR into a guided walkthrough so you can actually read code in clustered changes (not just big scrollable list of file changes in alphabetical order). Comments URL: https://news.ycombinator.com/item?id=49179546 Points: 1 # Comments: 0
Hi HN! We’re Akilan and Miguel, the creators of MarbleOS. The inspiration for Marble comes from the GUI work at Xerox PARC, the 1984 Macintosh, and later NeXTSTEP, which became the foundation for Mac OS X. Before GUIs, interacting with a computer was limited to strange terminal commands: C:\> DIR C:\> COPY FILE.TXT A: You had to remember the command, syntax, paths, and parameters. The GUI made those capabilities visible. Instead of remembering commands, you could point at files, drag them, click buttons, and select actions from menus. It didn't necessarily make entirely new things possible; it just made existing capabilities much easier to understand and use. We feel like AI is still somewhere around this command-line stage. Even though the strict syntax has been replaced with natural language, the interaction can still be quite stiff and depend on heavily recall. Tools like Claude Cowork still look surprisingly terminal-like: /skill-name [param1] [param2]. The parameters are written in natural language, but the user still needs to know the capabilities that exist, and how to invoke it. Command-line flags and arguments have just been replaced with tools, skills, and context. ChatGPT works very well for asking questions, but we aren't convinced that it's the final interface for delegating work across multiple agents. A blank text box and a list of chat threads feels limiting. An agent's capabilities are mostly invisible. With Marble, we're exploring an interface that treats AI more like a workspace than another chat app. Each delegated task becomes a card. Multiple jobs can sit next to each other and run at once. Files, tools, and finished artifacts are visible at once. Before a task runs, Marble also shows which tools it expects to use. The basic idea is that the user should not have to hold the entire structure of the task in their head. And the result should be something directly usable, like a spreadsheet, PowerPoint, or other file, rather than something buried in a transcript. Marble is our attempt at exploring interaction models beyond the chat box. The product is mainly for people who already use ChatGPT or Claude, but haven’t really adopted agent workflows yet. We’ve found that when the tools and possible actions are made more visible, people start delegating work they would not have thought to do through normal chat. The site includes a downloadable beta if you want to try it. Does Marble feel like a genuinely novel interface? Comments URL: https://news.ycombinator.com/item?id=49119274 Points: 49 # Comments: 29
How OpenAI’s creative team uses Codex to build custom creative tools, accelerate ideation, and prototype faster with context-aware AI.