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Aware is (basically) a browser we're building to explore personal computing and generative, malleable software. it keeps a footprint of the materials (pages, files) as a graph in a relational database stored locally. Been writing my paper in my own latex editor inside Aware. It's very satisfying when software... fixes itself and fetches its own context and attach them to the right parts. The editor is an experiment of "interface as a skill": the editor's code and its skill live in the paper's repo, so the same agent that knows my code and data also lives in the editor. So i get: 1. an interface i can reprogram any part anytime (aesthetics i like, and the scratch pad i always wanted) 2. an agent living in the editor, with the whole project as context (a figure links to the dashboard, built from the real analysis code that made it) (though i have to admit, some of my focused writing time now goes to wanting to tweak the editor instead)show more

Rima Cao

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30,756 次观看 • 4 天前 •via X (Twitter)

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Out of sheer frustration ... I decided to vibe code my own tile map editor to see if it can help with making my agent skills be able to build better levels. It also proves that the agent skill is sufficiently good enough to know how to read the tilemaps - just bad at level design. So maybe I just need to build a level design skill.

Out of sheer frustration ... I decided to vibe code my own tile map editor to see if it can help with making my agent skills be able to build better levels. It also proves that the agent skill is sufficiently good enough to know how to read the tilemaps - just bad at level design. So maybe I just need to build a level design skill.

Chong-U

37,202 次观看 • 9 个月前

i'm writing my own gui framework in c++ and rewriting my image editor using it, which is going good so far, i wanted to move from swiftui, qt, tauri, electron, react native, and flutter so i can use metal and directx gpu apis on macos and windows as much as possible,so i think going full metal/directx is the way to go i know i have a very hard and long way to go though as there are many many flaws,bugs in this very very early version and doesnt utilize the gpu as much as i want to but i hope we will get there soon ,i also need to make the ui look somewhat decent instead of whatever mess it is right now

i'm writing my own gui framework in c++ and rewriting my image editor using it, which is going good so far, i wanted to move from swiftui, qt, tauri, electron, react native, and flutter so i can use metal and directx gpu apis on macos and windows as much as possible,so i think going full metal/directx is the way to go i know i have a very hard and long way to go though as there are many many flaws,bugs in this very very early version and doesnt utilize the gpu as much as i want to but i hope we will get there soon ,i also need to make the ui look somewhat decent instead of whatever mess it is right now

Ruben Veidt

85,053 次观看 • 1 年前

new skill: create-canvas. last week I made a skill to put every component from a repo on one canvas. I started using it with my agent to create variations, compare ideas, and iterate visually without leaving the codebase. so I made a new skill around that workflow. instead of moving your work into another tool, bring the canvas into your codebase and use it to explore UI with your agent, using the real components, styles, and project context already there.

new skill: create-canvas. last week I made a skill to put every component from a repo on one canvas. I started using it with my agent to create variations, compare ideas, and iterate visually without leaving the codebase. so I made a new skill around that workflow. instead of moving your work into another tool, bring the canvas into your codebase and use it to explore UI with your agent, using the real components, styles, and project context already there.

Ibelick

39,091 次观看 • 14 天前

If you're using match cuts in your video, the invideo editor + agent gives you the fastest, most seamless experience to do it. Here's what we did to create this in ~40 minutes: ~Picked an image with a circle in the centre. Used that image as a reference to generate other images with circular subjects (but you could always just use your own footage). ~Uploaded the audio track I wanted to use into the invideo timeline, and asked the agent to detect all beats and place markers there. ~Asked the agent to then place all my generated images against those markers. ~Used rulers in the editor to maintain clip/subject alignment.

If you're using match cuts in your video, the invideo editor + agent gives you the fastest, most seamless experience to do it. Here's what we did to create this in ~40 minutes: ~Picked an image with a circle in the centre. Used that image as a reference to generate other images with circular subjects (but you could always just use your own footage). ~Uploaded the audio track I wanted to use into the invideo timeline, and asked the agent to detect all beats and place markers there. ~Asked the agent to then place all my generated images against those markers. ~Used rulers in the editor to maintain clip/subject alignment.

Invideo

11,077 次观看 • 1 个月前

A FLY IS NOW WRITING PYTHON CODE WITH ITS OWN NERVOUS SYSTEM I genuinely didn't expect a fly to end up behind a code editor. The setup is strangely simple. A fly sits on a keyboard while its neural activity is captured in real time. On the other side of the screen, Python code starts appearing line by line inside wordle_solver_v1.py, with the neural visualization changing as the input comes through. The model contains 100,010 flyemg neurons, with 88,172 represented in the current neural model. As activity changes, the system translates those signals into keyboard input and the cursor keeps moving through the code. Then you start looking at what is actually being typed. import random import unicodedata def quitar_acentos(palabra): It's not just random characters filling the editor. The video shows an actual Python function being constructed while the neural activity and keyboard input remain synchronized beside it. Brain activity → keyboard → code. A tiny biological nervous system is being used as the interface between a fly and a programming environment. The fly isn't sitting there watching someone code. It's sitting on the keyboard while the system turns its neural activity into the next input. And somehow the first thing it ended up building was a Wordle solver

A FLY IS NOW WRITING PYTHON CODE WITH ITS OWN NERVOUS SYSTEM I genuinely didn't expect a fly to end up behind a code editor. The setup is strangely simple. A fly sits on a keyboard while its neural activity is captured in real time. On the other side of the screen, Python code starts appearing line by line inside wordle_solver_v1.py, with the neural visualization changing as the input comes through. The model contains 100,010 flyemg neurons, with 88,172 represented in the current neural model. As activity changes, the system translates those signals into keyboard input and the cursor keeps moving through the code. Then you start looking at what is actually being typed. import random import unicodedata def quitar_acentos(palabra): It's not just random characters filling the editor. The video shows an actual Python function being constructed while the neural activity and keyboard input remain synchronized beside it. Brain activity → keyboard → code. A tiny biological nervous system is being used as the interface between a fly and a programming environment. The fly isn't sitting there watching someone code. It's sitting on the keyboard while the system turns its neural activity into the next input. And somehow the first thing it ended up building was a Wordle solver

Insomnia

12,054 次观看 • 1 个月前

Seems like Visual Studio Code is starting to tell you: your agent primitives need to move. There is now a new migration banner in the Chat panel, and it is part of a much bigger change happening under the hood: the move from the old Local harness to the new Agent Host architecture built around AHP. This is not just about moving where an agent runs. The old model was very VS Code-centric: prompts, custom agents, instructions and skills could live in VS Code-specific locations and the agent runtime lived inside the extension host. The new Agent Host separates the agent runtime from the editor. Sessions can keep running when the window closes, be shared across VS Code windows, run remotely, and support different harnesses such as Copilot, CLI and Copilot Desktop App through a common session layer. And that means some of our primitives need to move too. Prompt files are being deprecated for Agent Host and migrated to Skills. User-level agents and instructions that lived in VS Code profile storage need to move to harness-supported locations. Even the old location settings are being deprecated. The new migration experience can detect these things and guide you through moving or converting them, while keeping the originals unless you explicitly remove them. The new banner is basically the first visible sign that this migration is becoming a real product workflow. Basically telling us - it's time to move on!!!! If you have accumulated a lot of prompts, custom agents, instructions and skills over the last year, now is probably a good time to understand where they actually live and which harness owns them. To summarize the shift - it isn't just: VS Code Chat → Agent Host It is: VS Code-specific primitives → harness-native primitives. And I think this is going to become increasingly important as agents stop being features inside an IDE and become runtimes that multiple clients can connect to. Go run your migrations now 🏃‍♀️

Oren Melamed

30,867 次观看 • 1 个月前

Own your personal agent, folks. Just built my own little personal agent with Pi's Pi Durable. I wanted to see how quickly I could build an OpenAI dots clone with open-source tools. I am amazed at how quickly I got this off the ground. It's proactive. It keeps working when you're not watching. It remembers you, runs jobs on a schedule, waits for your approval, and uses its own computer. Pi Durable makes that possible. Every step is checkpointed. I can kill the process mid-task, and My Pi picks up right where it left off. Memory lives in durable documents. What My Pi learns about me in one Space survives a crash and carries over to every other Space. Approvals are durable too. It also has its own computer. Each Space gets a full Linux desktop that My Pi controls with screenshots, mouse, and keyboard. The model runs through OpenRouter, so I can swap models without changing anything else. That's all configurable however you like it. If you've been wanting your own personal agent, now is a great time to build one. I am building this as an experimental ground where I can test new ideas and experiment deeply with proactive personal agents. But I plan to open-source it after testing it a bit and adding more interesting primitives. The goal is to make it customizable and easy to build on, so others can experiment with their own personal agent functionalities.

Own your personal agent, folks. Just built my own little personal agent with Pi's Pi Durable. I wanted to see how quickly I could build an OpenAI dots clone with open-source tools. I am amazed at how quickly I got this off the ground. It's proactive. It keeps working when you're not watching. It remembers you, runs jobs on a schedule, waits for your approval, and uses its own computer. Pi Durable makes that possible. Every step is checkpointed. I can kill the process mid-task, and My Pi picks up right where it left off. Memory lives in durable documents. What My Pi learns about me in one Space survives a crash and carries over to every other Space. Approvals are durable too. It also has its own computer. Each Space gets a full Linux desktop that My Pi controls with screenshots, mouse, and keyboard. The model runs through OpenRouter, so I can swap models without changing anything else. That's all configurable however you like it. If you've been wanting your own personal agent, now is a great time to build one. I am building this as an experimental ground where I can test new ideas and experiment deeply with proactive personal agents. But I plan to open-source it after testing it a bit and adding more interesting primitives. The goal is to make it customizable and easy to build on, so others can experiment with their own personal agent functionalities.

elvis

36,344 次观看 • 29 天前

HTML Artifacts are a big part of how I work with agents now. Artifacts can be more than just static files. When combined with agents, they can take action or help you take action. This unlocks all kinds of interesting ways to work with agents. This is clearly the future. Check out this writing and scheduler artifact I built in a few minutes. It uses a bit of HTML and JS. All the data is in markdown (Obsidian vaults), so the agent can access and modify it at any time. No DB needed. No sophisticated functionalities. The agent decides all that for me based on the skills, context, and memory it has access to. The best part about this simple stack is that all the important information stays with me. This has allowed me to build a recursive self-improving system and automations that can better tap into coding agents like Codex or Claude Code. I could have paid or built an entire app for scheduling posts, and there are so many of them out there. But I don't need to. I've realized a simple artifact does the job. And the simplicity of it is actually an advantage. Very little maintenance for very high returns on personalization, time, and efficiency. The other benefit of this is that I can add features as I please. That level of personalization feels magical, and we should all be pursuing more of it. All of this just keeps compounding. Of course, this example is just about writing. But I have similar artifacts for research, design, experimentation, evaluation, and so much more. And no, I didn't actually publish the post example I shared in the clip. It was just for demonstration purposes. I actually spend more time than this when writing together with agents. Lastly, having built my own agent orchestrator tool has made me realize that simplifying the tool stack is a superpower. If you are curious about how all this works, I will do a live session next week:

HTML Artifacts are a big part of how I work with agents now. Artifacts can be more than just static files. When combined with agents, they can take action or help you take action. This unlocks all kinds of interesting ways to work with agents. This is clearly the future. Check out this writing and scheduler artifact I built in a few minutes. It uses a bit of HTML and JS. All the data is in markdown (Obsidian vaults), so the agent can access and modify it at any time. No DB needed. No sophisticated functionalities. The agent decides all that for me based on the skills, context, and memory it has access to. The best part about this simple stack is that all the important information stays with me. This has allowed me to build a recursive self-improving system and automations that can better tap into coding agents like Codex or Claude Code. I could have paid or built an entire app for scheduling posts, and there are so many of them out there. But I don't need to. I've realized a simple artifact does the job. And the simplicity of it is actually an advantage. Very little maintenance for very high returns on personalization, time, and efficiency. The other benefit of this is that I can add features as I please. That level of personalization feels magical, and we should all be pursuing more of it. All of this just keeps compounding. Of course, this example is just about writing. But I have similar artifacts for research, design, experimentation, evaluation, and so much more. And no, I didn't actually publish the post example I shared in the clip. It was just for demonstration purposes. I actually spend more time than this when writing together with agents. Lastly, having built my own agent orchestrator tool has made me realize that simplifying the tool stack is a superpower. If you are curious about how all this works, I will do a live session next week:

elvis

18,374 次观看 • 5 个月前

Usually when I save a website URL it's because -I want to save the website design exactly how it is in that point in time -I want to know what frontend/animation trickery they did whether its just raw code or some framework so i made a site where I just drop the url -> get a screenshot + screen recording to capture any animations I found interesting a non-trivial amount of my notion links don't resonate with me due to redesigns and I think this is the simplest fix. Just like my notion list it lives in a browser tab and is still paste->enter->move on

Usually when I save a website URL it's because -I want to save the website design exactly how it is in that point in time -I want to know what frontend/animation trickery they did whether its just raw code or some framework so i made a site where I just drop the url -> get a screenshot + screen recording to capture any animations I found interesting a non-trivial amount of my notion links don't resonate with me due to redesigns and I think this is the simplest fix. Just like my notion list it lives in a browser tab and is still paste->enter->move on

Sabina

38,649 次观看 • 7 个月前

ONE PROMPT. AN ENTIRE FINANCIAL DASHBOARD. I asked a new AI agent to build it, and it created this interactive dashboard from scratch. It planned the project, wrote the code, ran it locally, and handled the final touches. Meet EvoX Agent 🧵👇

ONE PROMPT. AN ENTIRE FINANCIAL DASHBOARD. I asked a new AI agent to build it, and it created this interactive dashboard from scratch. It planned the project, wrote the code, ran it locally, and handled the final touches. Meet EvoX Agent 🧵👇

gus

60,661 次观看 • 1 个月前

Best part about being a software developer is you can bring ideas into reality. As a frequent flyer and an aviation geek, I missed the in-flight entertainment on indigo flights. So I created an app that fetches my trip data, downloads an offline map of the estimated flight path before my flight and simulates an IFE during the flight Right now it shows altitude, speed, heading and flight location on the map.

Best part about being a software developer is you can bring ideas into reality. As a frequent flyer and an aviation geek, I missed the in-flight entertainment on indigo flights. So I created an app that fetches my trip data, downloads an offline map of the estimated flight path before my flight and simulates an IFE during the flight Right now it shows altitude, speed, heading and flight location on the map.

Starcommander✨👨🏻‍💻

98,086 次观看 • 1 个月前

✨ professional news ✨ Though I hadn’t announced, five months ago I became the Senior News Editor at @Them. And though I loved my time there, it seems it has already come to an end as I take on a once-in-a-lifetime opportunity, effective immediately. Here’s to 2026!

✨ professional news ✨ Though I hadn’t announced, five months ago I became the Senior News Editor at @Them. And though I loved my time there, it seems it has already come to an end as I take on a once-in-a-lifetime opportunity, effective immediately. Here’s to 2026!

Mikelle Street

86,260 次观看 • 9 个月前

I spent months building a code editor and the feature people are most excited about is... copying images to the clipboard ⌘⌥C your code. Paste a masterpiece. Your Keynote will never look the same.

I spent months building a code editor and the feature people are most excited about is... copying images to the clipboard ⌘⌥C your code. Paste a masterpiece. Your Keynote will never look the same.

Marcin Krzyzanowski

29,669 次观看 • 10 个月前

Advent of Claude Day 31 - Claude Agent SDK I saved the best for last. The same agent loop, tools, and context management that power Claude Code is available as an SDK. Build agents that work like Claude Code in as little as 10 lines of code. This is just the beginning. 🎇🥂

Advent of Claude Day 31 - Claude Agent SDK I saved the best for last. The same agent loop, tools, and context management that power Claude Code is available as an SDK. Build agents that work like Claude Code in as little as 10 lines of code. This is just the beginning. 🎇🥂

Ado

100,117 次观看 • 10 个月前

Building a personal knowledge base for my agents is increasingly where I spend my time these days. Like Andrej Karpathy, I also use Obsidian for my MD vaults. What's different in my approach is that I curate research papers on a daily basis and have actually tuned a Skill for months to find high-signal, relevant papers. I was reviewing and curating papers manually for some time, but now it's all automated as it has gotten so good at capturing what I consider the best of the best. There are so many papers these days, so this is a big deal. You all get to benefit from that with the papers I feature in my timeline and on DAIR.AI. The papers are indexed using tobi lutke qmd cli tool (all of it in markdown files along with useful metadata). So good for semantic search and surfacing insights, unlike anything out there. I am a visual person, so I then started to experiment with how to leverage this personal knowledge base of research papers inside my new interactive artifact generator (mcp tools inside my agent orchestrator system). The result is what you see in the clip. 100s of papers with all sorts of insights visualized. I keep track of research papers daily, so believe me when I tell you that this system is absolutely insane at surfacing insights. This is the result of months of tinkering on how to index research and leverage agent automations for wikification and robust documentation. But this is just the beginning. The visual artifact (which is interactive too) can be changed dynamically as I please. I can prompt my agent to throw any data at it. I can add different views to the data. Different interactions. I feel like this is the most personalized research system I have ever built and used, and it's not even close. The knowledge that the agents are able to surface from this basic setup is already extremely useful as I experiment with new agentic engineering concepts. I feel like this knowledge layer and the higher-level ones I am working on will allow me to maximize other automation tools like autoresearch. The research is only as good as the research questions. And the research questions are only as good as the insights the agents have access to. Where I am spending time now is on how to make this more actionable. I am obsessed about the search problem here. The automations, autoresearch, ralph research loop (I built one months ago) are easier to build but are only as good as what you feed them. Work in progress. More updates soon. Back to building.

Building a personal knowledge base for my agents is increasingly where I spend my time these days. Like Andrej Karpathy, I also use Obsidian for my MD vaults. What's different in my approach is that I curate research papers on a daily basis and have actually tuned a Skill for months to find high-signal, relevant papers. I was reviewing and curating papers manually for some time, but now it's all automated as it has gotten so good at capturing what I consider the best of the best. There are so many papers these days, so this is a big deal. You all get to benefit from that with the papers I feature in my timeline and on DAIR.AI. The papers are indexed using tobi lutke qmd cli tool (all of it in markdown files along with useful metadata). So good for semantic search and surfacing insights, unlike anything out there. I am a visual person, so I then started to experiment with how to leverage this personal knowledge base of research papers inside my new interactive artifact generator (mcp tools inside my agent orchestrator system). The result is what you see in the clip. 100s of papers with all sorts of insights visualized. I keep track of research papers daily, so believe me when I tell you that this system is absolutely insane at surfacing insights. This is the result of months of tinkering on how to index research and leverage agent automations for wikification and robust documentation. But this is just the beginning. The visual artifact (which is interactive too) can be changed dynamically as I please. I can prompt my agent to throw any data at it. I can add different views to the data. Different interactions. I feel like this is the most personalized research system I have ever built and used, and it's not even close. The knowledge that the agents are able to surface from this basic setup is already extremely useful as I experiment with new agentic engineering concepts. I feel like this knowledge layer and the higher-level ones I am working on will allow me to maximize other automation tools like autoresearch. The research is only as good as the research questions. And the research questions are only as good as the insights the agents have access to. Where I am spending time now is on how to make this more actionable. I am obsessed about the search problem here. The automations, autoresearch, ralph research loop (I built one months ago) are easier to build but are only as good as what you feed them. Work in progress. More updates soon. Back to building.

elvis

468,346 次观看 • 7 个月前

New beta feature in T3 Code: "share with guest" I'm so tired of copy pasting from a thread, sending it to a coworker, waiting for them to respond, screenshotting the context and sending it back to my agent. Now I just send them a link. It's a silly place to start, but I was heavily inspired by the Uber Eats/Doordash group order flow. If I send someone a link to my group order, they can add whatever they want, but ultimately I decide if the order goes through or not. Realized that flow would solve at least half the use cases I have for "shared threads", so it's now built into T3 Connect in T3 Code (nightly) Very curious how you guys feel about this flow. It's still early and I expect to adjust it a bunch (I left the ui bad so maria will come in to fix it sooner) Also s/o Opus 5.5 for making this lil video about the feature :)

New beta feature in T3 Code: "share with guest" I'm so tired of copy pasting from a thread, sending it to a coworker, waiting for them to respond, screenshotting the context and sending it back to my agent. Now I just send them a link. It's a silly place to start, but I was heavily inspired by the Uber Eats/Doordash group order flow. If I send someone a link to my group order, they can add whatever they want, but ultimately I decide if the order goes through or not. Realized that flow would solve at least half the use cases I have for "shared threads", so it's now built into T3 Connect in T3 Code (nightly) Very curious how you guys feel about this flow. It's still early and I expect to adjust it a bunch (I left the ui bad so maria will come in to fix it sooner) Also s/o Opus 5.5 for making this lil video about the feature :)

Theo - t3.gg

122,214 次观看 • 9 天前

I have a little robot that unlocks my door from the inside (so I don't have to carry a key) The problem was it wouldn't calibrate on my door. It was designed for 90° turns, but my lock only needs 15° In the past, this would've been a showstopper But I asked AI if it could help... At first, it suggested I snoop on the bluetooth connection to figure out the protocol Then it realized that we could probably just decompile the app's SDK and read its source code. That worked! It told me to switch to my mac and run some python for it. Unfortunately, it couldn't run the scripts directly because Claude Code Desktop didn't have bluetooth permissions, but my shell did. Thinking about it now, I probably should've used Claude Code or Codex in the Terminal. Anyways, it took a while, lots of backs and forths, we had some misunderstandings, it was massively overcautious in the beginning, but we finally got the lock calibrated! Feels like magic! I threw the repo up on github in case anyone in the future (ie me) runs into a similar issue – hopefully it can save them some time

I have a little robot that unlocks my door from the inside (so I don't have to carry a key) The problem was it wouldn't calibrate on my door. It was designed for 90° turns, but my lock only needs 15° In the past, this would've been a showstopper But I asked AI if it could help... At first, it suggested I snoop on the bluetooth connection to figure out the protocol Then it realized that we could probably just decompile the app's SDK and read its source code. That worked! It told me to switch to my mac and run some python for it. Unfortunately, it couldn't run the scripts directly because Claude Code Desktop didn't have bluetooth permissions, but my shell did. Thinking about it now, I probably should've used Claude Code or Codex in the Terminal. Anyways, it took a while, lots of backs and forths, we had some misunderstandings, it was massively overcautious in the beginning, but we finally got the lock calibrated! Feels like magic! I threw the repo up on github in case anyone in the future (ie me) runs into a similar issue – hopefully it can save them some time

Steve Krouse

38,720 次观看 • 3 个月前