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Kimi Code got a makeover. Jump between GUI and terminal instantly. Same conversation, zero context lost. Inline diffs, rich tool calls, plan mode, message queuing, and more.

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super.engineering

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44,778 просмотров • 2 месяцев назад •via X (Twitter)

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Today we're launching Replay When you're building with agents, the conversation is the work. The code is a byproduct. But that conversation disappears when you close the terminal Replay gives your Claude Code sessions a permanent, shareable home. Upload a session → browsable thread with inline diffs, tool calls, and decision traces And it's open source:
0:46

Today we're launching Replay When you're building with agents, the conversation is the work. The code is a byproduct. But that conversation disappears when you close the terminal Replay gives your Claude Code sessions a permanent, shareable home. Upload a session → browsable thread with inline diffs, tool calls, and decision traces And it's open source:

Nars

16,627 просмотров • 5 месяцев назад

built a small CLI tool that moves your AI coding session context between Claude Code, Gemini, Copilot, Codex and OpenCode when you hit rate limits. no more re-explaining what you were doing, or painful copy/paste from terminal that lose tool-call context. just `npx continues`
0:30

built a small CLI tool that moves your AI coding session context between Claude Code, Gemini, Copilot, Codex and OpenCode when you hit rate limits. no more re-explaining what you were doing, or painful copy/paste from terminal that lose tool-call context. just `npx continues`

Yigit Konur

213,967 просмотров • 7 месяцев назад

Qwen-Code weekly release (v0.0.8) : ✨ Deep VS Code Integration: Get context-aware suggestions & inline diffs directly in your editor! Initialize with /ide and supercharge your workflow. 🔌 Enhanced MCP Support: Add, remove, list MCP servers via CLI (qwen mcp add|remove|list), plus support for MCP roots & multimodal tool outputs (images, audio, and more!). 📱 Responsive Terminal UI: Now adapts gracefully to narrow terminals. 🔍 Reverse Search: Press Ctrl+R in shell mode to instantly search command history. 🗜️ Customizable Context Compression: Set your threshold in settings.json. 📂 Multi-directory Support: Auto-load multiple dirs at startup. 🔢 Hide Line Numbers: Set "showLineNumbers": false for cleaner copy-paste. 🔕 Plus: Disable update nudges with "disableUpdateNag": true 📌More details: Upgrade now and level up your coding experience 💻🔥
0:50

Qwen-Code weekly release (v0.0.8) : ✨ Deep VS Code Integration: Get context-aware suggestions & inline diffs directly in your editor! Initialize with /ide and supercharge your workflow. 🔌 Enhanced MCP Support: Add, remove, list MCP servers via CLI (qwen mcp add|remove|list), plus support for MCP roots & multimodal tool outputs (images, audio, and more!). 📱 Responsive Terminal UI: Now adapts gracefully to narrow terminals. 🔍 Reverse Search: Press Ctrl+R in shell mode to instantly search command history. 🗜️ Customizable Context Compression: Set your threshold in settings.json. 📂 Multi-directory Support: Auto-load multiple dirs at startup. 🔢 Hide Line Numbers: Set "showLineNumbers": false for cleaner copy-paste. 🔕 Plus: Disable update nudges with "disableUpdateNag": true 📌More details: Upgrade now and level up your coding experience 💻🔥

Qwen

127,588 просмотров • 1 год назад

Composer 2.5 got a brand new look. Cursor Chat View is live. Claude, Codex - whatever your subscription gives you. Rich chat UI with collapsible tools, live diffs, and streaming. Or switch to full TUI mid-conversation. Toggle seamlessly, context preserved. Live today.
0:28

Composer 2.5 got a brand new look. Cursor Chat View is live. Claude, Codex - whatever your subscription gives you. Rich chat UI with collapsible tools, live diffs, and streaming. Or switch to full TUI mid-conversation. Toggle seamlessly, context preserved. Live today.

super.engineering

26,492 просмотров • 3 месяцев назад

MY FRIEND MADE $1.2M WRITING A 3D GAME WITH ONE PROMPT USING KIMI K3 open world, multiplayer, PVP mode, skins, team play with friends - all from one prompt in one session what used to take a team of 10 developers 6 months - he did alone in 10 minutes players started sharing the game themselves - organic growth with zero ads and zero marketing budget first $1,000 came the same day - a year later the account had $1.2M zero code written by hand, zero team, zero investment - just the right tool and the right prompt Kimi K3 - 2.8 trillion parameters, 1 million token context - exactly what made it possible to build the entire game in one request
0:31

MY FRIEND MADE $1.2M WRITING A 3D GAME WITH ONE PROMPT USING KIMI K3 open world, multiplayer, PVP mode, skins, team play with friends - all from one prompt in one session what used to take a team of 10 developers 6 months - he did alone in 10 minutes players started sharing the game themselves - organic growth with zero ads and zero marketing budget first $1,000 came the same day - a year later the account had $1.2M zero code written by hand, zero team, zero investment - just the right tool and the right prompt Kimi K3 - 2.8 trillion parameters, 1 million token context - exactly what made it possible to build the entire game in one request

Noisy

24,328 просмотров • 2 месяцев назад

🌘 Meet Kimi K2.7 Code HighSpeed! A high-speed mode of our latest open-source multimodal coding model, Kimi K2.7 Code. ⚡️ Up to 6× faster: Around 180 tok/s on coding tasks with median-length inputs, and up to 260 tok/s on shorter-context tasks. 🔷 Rolling out to Kimi Code Beta Program members, Kimi API developers, and Kimi Business users. (Access will remain limited for now due to capacity constraints.) 🔷 No invite needed. Anyone who joins the Beta Program has a chance to get access 👉 Open intelligence should be instant, affordable, and borderless. We'll continue improving the model and expanding access as more capacity becomes available! 🔗 Kimi Code: 🔗 API:
22:42

🌘 Meet Kimi K2.7 Code HighSpeed! A high-speed mode of our latest open-source multimodal coding model, Kimi K2.7 Code. ⚡️ Up to 6× faster: Around 180 tok/s on coding tasks with median-length inputs, and up to 260 tok/s on shorter-context tasks. 🔷 Rolling out to Kimi Code Beta Program members, Kimi API developers, and Kimi Business users. (Access will remain limited for now due to capacity constraints.) 🔷 No invite needed. Anyone who joins the Beta Program has a chance to get access 👉 Open intelligence should be instant, affordable, and borderless. We'll continue improving the model and expanding access as more capacity becomes available! 🔗 Kimi Code: 🔗 API:

Kimi.ai

571,673 просмотров • 3 месяцев назад

Excited to share Cline CLI 2.0 🎉 Reskinned the TUI to make it look and feel like the VS Code extension, and updated prompts to be more powerful in the terminal. Plan/Act modes, Auto-approve toggle, context window, git tracking, and a cute ASCII animation! npm i -g cline
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Excited to share Cline CLI 2.0 🎉 Reskinned the TUI to make it look and feel like the VS Code extension, and updated prompts to be more powerful in the terminal. Plan/Act modes, Auto-approve toggle, context window, git tracking, and a cute ASCII animation! npm i -g cline

Saoud Rizwan

19,612 просмотров • 7 месяцев назад

Most discussions around Claude Code focus on model quality or capability. But when you actually use it, the friction shows up earlier, more at the system level than the model itself. Token limits get the blame, but a lot of it comes from inefficient sessions: repeated context, extra tool calls, and small loops that quietly stack up. So it starts to feel less like “is the model good enough?” and more like “is the workflow slowing it down?” That’s where WozCode comes in. It helps streamline sessions, less repetition, smarter batching of tool calls, and tighter context usage so you can actually get more work done within the same limits. Woz just launched on Product Hunt. If Claude Code felt a bit restrictive before, it’s worth trying again with a cleaner workflow setup. Same model. Smoother execution. Upvote here:
1:01

Most discussions around Claude Code focus on model quality or capability. But when you actually use it, the friction shows up earlier, more at the system level than the model itself. Token limits get the blame, but a lot of it comes from inefficient sessions: repeated context, extra tool calls, and small loops that quietly stack up. So it starts to feel less like “is the model good enough?” and more like “is the workflow slowing it down?” That’s where WozCode comes in. It helps streamline sessions, less repetition, smarter batching of tool calls, and tighter context usage so you can actually get more work done within the same limits. Woz just launched on Product Hunt. If Claude Code felt a bit restrictive before, it’s worth trying again with a cleaner workflow setup. Same model. Smoother execution. Upvote here:

Parul Gautam

15,079 просмотров • 4 месяцев назад

WTF Brooooooooo... this is actually incredible. 🤯 This library recreated the UI of Claude Code, Codex & Grok as reusable shadcn components. So if you wanna build AI apps, CLI tools, or terminal UIs with this kind of polished interface, you can just use these components instead of building everything from scratch. It includes chat messages, tool calls, code diffs, permission dialogs, todo lists, slash commands, and more. Perfect for building AI tools :) Follow me for more amazing AI, Coding & Web Dev insights 💎
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WTF Brooooooooo... this is actually incredible. 🤯 This library recreated the UI of Claude Code, Codex & Grok as reusable shadcn components. So if you wanna build AI apps, CLI tools, or terminal UIs with this kind of polished interface, you can just use these components instead of building everything from scratch. It includes chat messages, tool calls, code diffs, permission dialogs, todo lists, slash commands, and more. Perfect for building AI tools :) Follow me for more amazing AI, Coding & Web Dev insights 💎

Ram Maheshwari

65,834 просмотров • 26 дней назад

Claude for Excel and Claude for PowerPoint now sync together seamlessly. When you’ve got more than one file open, Claude shares the full context of your conversation between them. Pull data from spreadsheets, build out tables, and update a deck — without re-explaining a step.
1:36

Claude for Excel and Claude for PowerPoint now sync together seamlessly. When you’ve got more than one file open, Claude shares the full context of your conversation between them. Pull data from spreadsheets, build out tables, and update a deck — without re-explaining a step.

Claude

12,542,199 просмотров • 6 месяцев назад

Hermes agent just left the terminal. 𝗛𝗲𝗿𝗺𝗲𝘀 𝗗𝗲𝘀𝗸𝘁𝗼𝗽 dropped yesterday. native app for macOS, Windows, and Linux. for months Hermes was the agent that learned your projects, wrote its own skills, and built a model of who you are. all of it buried in terminal logs. now it has a window. the important part is that it's not a wrapper. it runs the same agent core, the same sessions, memory, and skills as the CLI. you can start a task in the terminal and finish it in the app without anything resetting. the state is shared across every interface, not copied between them. what the GUI actually adds: → streaming chat that shows live tool calls and inline reasoning instead of a spinner → a preview rail that renders pages, code, and images right beside the conversation → an artifacts panel that collects every file the agent has ever produced → remote gateway mode, so you can point the app at a VPS and run the heavy work elsewhere → skills, cron, profiles, and gateways managed point-and-click instead of through YAML → voice mode, drag-drop files, and inline image generation remote gateway mode is the one worth slowing down on. the agent runs 24/7 on a $5 server while you control it from your laptop like a local app. other agent UIs are chatboxes with a logo. this one shows the autonomy instead of hiding it, so you watch the skills load, the tools fire, and the artifacts pile up as it works. it was teased in Jensen's GTC keynote. MIT licensed, local-first, no telemetry. if you already run Hermes, download it and everything is already there. your chats, memory, and skills carry straight over. i wrote a full masterclass on Hermes Agent that walks through the SOUL. md identity layer, the three-tier memory system, the self-evolving skills loop, and how to run three specialized agents 24/7. desktop is the interface that finally does all of it justice. the article is quoted below.
1:18

Hermes agent just left the terminal. 𝗛𝗲𝗿𝗺𝗲𝘀 𝗗𝗲𝘀𝗸𝘁𝗼𝗽 dropped yesterday. native app for macOS, Windows, and Linux. for months Hermes was the agent that learned your projects, wrote its own skills, and built a model of who you are. all of it buried in terminal logs. now it has a window. the important part is that it's not a wrapper. it runs the same agent core, the same sessions, memory, and skills as the CLI. you can start a task in the terminal and finish it in the app without anything resetting. the state is shared across every interface, not copied between them. what the GUI actually adds: → streaming chat that shows live tool calls and inline reasoning instead of a spinner → a preview rail that renders pages, code, and images right beside the conversation → an artifacts panel that collects every file the agent has ever produced → remote gateway mode, so you can point the app at a VPS and run the heavy work elsewhere → skills, cron, profiles, and gateways managed point-and-click instead of through YAML → voice mode, drag-drop files, and inline image generation remote gateway mode is the one worth slowing down on. the agent runs 24/7 on a $5 server while you control it from your laptop like a local app. other agent UIs are chatboxes with a logo. this one shows the autonomy instead of hiding it, so you watch the skills load, the tools fire, and the artifacts pile up as it works. it was teased in Jensen's GTC keynote. MIT licensed, local-first, no telemetry. if you already run Hermes, download it and everything is already there. your chats, memory, and skills carry straight over. i wrote a full masterclass on Hermes Agent that walks through the SOUL. md identity layer, the three-tier memory system, the self-evolving skills loop, and how to run three specialized agents 24/7. desktop is the interface that finally does all of it justice. the article is quoted below.

Akshay 🚀

51,540 просмотров • 3 месяцев назад

With all the buzz around the Codex App, OpenAI Developers quietly snuck out a new CLI update (0.94.0) as well. And boy is it an important update! Codex Plan mode is now officially released to the general audience! I am very excited about this one as it has a really strong prompt that is unlike any other plan mode I've personally used. Codex Plan mode doesn't necessarily just ask you 3 questions up front. It goes, collects context, asks questions, collects more context, asks more questions (sometimes), and then writes an incredibly high quality plan. It is my favorite implementation of plan mode thus far. It also comes with Codex's own version of "AskUserQuestion!" Although, it only works in Plan mode for now. They really need to allow people to use it in Code mode as well, but one win at a time. npm i -g @openai/codex Below is a demo of how it works. Let me know what you think!
2:15

With all the buzz around the Codex App, OpenAI Developers quietly snuck out a new CLI update (0.94.0) as well. And boy is it an important update! Codex Plan mode is now officially released to the general audience! I am very excited about this one as it has a really strong prompt that is unlike any other plan mode I've personally used. Codex Plan mode doesn't necessarily just ask you 3 questions up front. It goes, collects context, asks questions, collects more context, asks more questions (sometimes), and then writes an incredibly high quality plan. It is my favorite implementation of plan mode thus far. It also comes with Codex's own version of "AskUserQuestion!" Although, it only works in Plan mode for now. They really need to allow people to use it in Code mode as well, but one win at a time. npm i -g @openai/codex Below is a demo of how it works. Let me know what you think!

am.will

57,121 просмотров • 7 месяцев назад

Bruh... someone recreated the UI of Claude Code, Codex & Grok as reusable ShadCN components. 🤯 This open-source library lets you drop beautifully recreated AI interface components straight into your own apps or CLI projects. You'll find components for: → prompts & chat messages → tool calls → code diffs → permission dialogs → todo lists → slash commands → and much more... Perfect if you're building AI apps, terminal UIs (TUIs), or CLI-based developer tools and don't want to build everything from scratch :) Source 🔗: github(DOT)com/theswerd/brainless Follow me for more amazing AI, Coding & Web Dev insights 💎
0:39

Bruh... someone recreated the UI of Claude Code, Codex & Grok as reusable ShadCN components. 🤯 This open-source library lets you drop beautifully recreated AI interface components straight into your own apps or CLI projects. You'll find components for: → prompts & chat messages → tool calls → code diffs → permission dialogs → todo lists → slash commands → and much more... Perfect if you're building AI apps, terminal UIs (TUIs), or CLI-based developer tools and don't want to build everything from scratch :) Source 🔗: github(DOT)com/theswerd/brainless Follow me for more amazing AI, Coding & Web Dev insights 💎

Ram Maheshwari

55,857 просмотров • 2 месяцев назад

94% OF ENGINEERING ORGS USE AI. ONLY 6% SCALE IT The missing link is context and governance. That’s exactly what Atlassian is going after with its new agentic engineering stack: Code Context + governed agent loops in Atlassian Jira + DX measurement. The idea is simple: make agents a native part of your engineering system instead of a side quest in a terminal. > Code Context grounds them in your architecture > Governed loops take work from backlog to pull request > DX measures the impact And the data backs up the context thesis: DX found context-rich AI teams shipped ~64% more per developer 👊 A pretty strong signal that context is becoming one of the biggest leverage points in agentic engineering.
1:00

94% OF ENGINEERING ORGS USE AI. ONLY 6% SCALE IT The missing link is context and governance. That’s exactly what Atlassian is going after with its new agentic engineering stack: Code Context + governed agent loops in Atlassian Jira + DX measurement. The idea is simple: make agents a native part of your engineering system instead of a side quest in a terminal. > Code Context grounds them in your architecture > Governed loops take work from backlog to pull request > DX measures the impact And the data backs up the context thesis: DX found context-rich AI teams shipped ~64% more per developer 👊 A pretty strong signal that context is becoming one of the biggest leverage points in agentic engineering.

Charly Wargnier ♨️

29,622 просмотров • 15 дней назад

Grok Build CLI just dropped. Not for dabbling. This is dev mode. Runs in your terminal and actually gets work done. Activate your personal dev mode. SuperGrok Heavy users only. Try it: * Confirm access - this is SuperGrok Heavy only, not your regular plan * Upgrade if needed - or * Install it - run the one-liner in your terminal * Jump into your project - cd into your repo * Launch Grok - type “grok” and log in once * Start prompting - audits, features, fixes, whatever you need * Use plan mode - review tasks and diffs before anything runs * Spin up sub-agents - let it handle big workloads * Go headless - automate scripts when you don’t want to babysit * Keep iterating - refine, rerun, improve You’re up and running in minutes. No excuses. Tip: Start with a small task in an existing repo to get comfortable with the plan and review workflow. xAI engineers are actively gathering feedback. Share your experience on 𝕏. xAI
0:33

Grok Build CLI just dropped. Not for dabbling. This is dev mode. Runs in your terminal and actually gets work done. Activate your personal dev mode. SuperGrok Heavy users only. Try it: * Confirm access - this is SuperGrok Heavy only, not your regular plan * Upgrade if needed - or * Install it - run the one-liner in your terminal * Jump into your project - cd into your repo * Launch Grok - type “grok” and log in once * Start prompting - audits, features, fixes, whatever you need * Use plan mode - review tasks and diffs before anything runs * Spin up sub-agents - let it handle big workloads * Go headless - automate scripts when you don’t want to babysit * Keep iterating - refine, rerun, improve You’re up and running in minutes. No excuses. Tip: Start with a small task in an existing repo to get comfortable with the plan and review workflow. xAI engineers are actively gathering feedback. Share your experience on 𝕏. xAI

Mario Nawfal

75,474 просмотров • 4 месяцев назад

SITUATION EXPLAINED: Kimi K3 just beat Fable on a major coding benchmark, at a fraction of the price. • Kimi K3 beat Fable on Frontend Code Arena • The gap between Kimi and Fable is bigger than the gap between Fable and Sol • It also smashes Opus outright, while being priced the same as Sonnet, $3/$15 per million tokens • Sonnet 5 High currently sits in 10th place on this leaderboard at that same price point • The generational jump is dramatic: Kimi K2.6 ranked 18th on this benchmark, K3 jumped 17 spots to take the top spot • K3 ranked #1 in 6 of 7 tested domains: brand and marketing, reference-based design, data and analytics, consumer products, simulations, and content creation tools, it placed #2, only in gaming, behind Fable • Full model weights are set to release July 27th Theo Jaffee: "Imagine if Anthropic were a public company today, their stock would be down 20%, maybe more, enterprises are probably not gonna be spending $10 and $50 on Fable when they can instead be spending $3 and $15 on Kimi K3."
3:21

SITUATION EXPLAINED: Kimi K3 just beat Fable on a major coding benchmark, at a fraction of the price. • Kimi K3 beat Fable on Frontend Code Arena • The gap between Kimi and Fable is bigger than the gap between Fable and Sol • It also smashes Opus outright, while being priced the same as Sonnet, $3/$15 per million tokens • Sonnet 5 High currently sits in 10th place on this leaderboard at that same price point • The generational jump is dramatic: Kimi K2.6 ranked 18th on this benchmark, K3 jumped 17 spots to take the top spot • K3 ranked #1 in 6 of 7 tested domains: brand and marketing, reference-based design, data and analytics, consumer products, simulations, and content creation tools, it placed #2, only in gaming, behind Fable • Full model weights are set to release July 27th Theo Jaffee: "Imagine if Anthropic were a public company today, their stock would be down 20%, maybe more, enterprises are probably not gonna be spending $10 and $50 on Fable when they can instead be spending $3 and $15 on Kimi K3."

MTS

132,930 просмотров • 2 месяцев назад

Karpathy’s Agentic Engineering finally has proper DevTools! When an agent stops working, the model is only one possible cause. The problem could be a failed tool, a lost connection, an interface update that never appeared, or something earlier in the conversation. CopilotKit🪁 has rebuilt its open-source Inspector around this problem. It sits inside the application and watches the full interaction between the user, the interface, and the agent. When something fails, the Inspector button turns red, names the failure, and opens the spot where it happened. But even a much harder problem is reproducing that failure. This is because agents do not always follow the same path twice. Running the same prompt again may trigger another tool, produce another response, or start with a different application state. Inspector handles this through saved Threads and an isolated Agent Playground. A developer can open the conversation where the problem occurred, choose "Try from here," and copy everything up to that point into the Playground. The original conversation remains unchanged while another response or tool path is tested. Threads can open inside the live application, while assistant messages can jump back to their matching context in Inspector. Everything runs underneath AG-UI, the protocol that carries messages, tool activity, state changes, and other events between the agent and the interface. Those interactions can also feed CopilotKit Intelligence so that when the same issue or useful behavior appears repeatedly, it can become an evidence-backed Insight and a proposed SKILL(.)md file. Developers can review, edit, and approve the improvement before the agent inherits it. The tool also helps developers find a problem, recreate its surrounding context, test another path, and turn repeated lessons into agent improvements. It is open source and included with CopilotKit development builds. Intelligence setup starts with one prompt. Here are the docs: I am testing this extensively and will cover this in more detail soon with a hands-on demo.
0:29

Karpathy’s Agentic Engineering finally has proper DevTools! When an agent stops working, the model is only one possible cause. The problem could be a failed tool, a lost connection, an interface update that never appeared, or something earlier in the conversation. CopilotKit🪁 has rebuilt its open-source Inspector around this problem. It sits inside the application and watches the full interaction between the user, the interface, and the agent. When something fails, the Inspector button turns red, names the failure, and opens the spot where it happened. But even a much harder problem is reproducing that failure. This is because agents do not always follow the same path twice. Running the same prompt again may trigger another tool, produce another response, or start with a different application state. Inspector handles this through saved Threads and an isolated Agent Playground. A developer can open the conversation where the problem occurred, choose "Try from here," and copy everything up to that point into the Playground. The original conversation remains unchanged while another response or tool path is tested. Threads can open inside the live application, while assistant messages can jump back to their matching context in Inspector. Everything runs underneath AG-UI, the protocol that carries messages, tool activity, state changes, and other events between the agent and the interface. Those interactions can also feed CopilotKit Intelligence so that when the same issue or useful behavior appears repeatedly, it can become an evidence-backed Insight and a proposed SKILL(.)md file. Developers can review, edit, and approve the improvement before the agent inherits it. The tool also helps developers find a problem, recreate its surrounding context, test another path, and turn repeated lessons into agent improvements. It is open source and included with CopilotKit development builds. Intelligence setup starts with one prompt. Here are the docs: I am testing this extensively and will cover this in more detail soon with a hands-on demo.

Akshay 🚀

12,206 просмотров • 14 дней назад

Bloome is actually smart for coding workflows i added Claude Code, Codex, DeepSeek and a Project Lead agent into one group chat each agent independently built their own version one challenged the logic, one defended, one fixed missing details and the final website stayed inside the same thread no copy paste between agents no lost context just one group chat for getting work done Bloome
0:50

Bloome is actually smart for coding workflows i added Claude Code, Codex, DeepSeek and a Project Lead agent into one group chat each agent independently built their own version one challenged the logic, one defended, one fixed missing details and the final website stayed inside the same thread no copy paste between agents no lost context just one group chat for getting work done Bloome

Chetaslua

48,810 просмотров • 2 месяцев назад

I cant believe this guy just made a permanent solution to context bloat and open sourced it all! when we tested this tool (Context+) for solving an issue on the OpenCode repository, the agent using this tool used ~6.5k fewer tokens, found the code and fixed it in half the time! the results were surprising: 6 to 10k tokens saved per prompt, completed task in ~2 minutes while the agent running without the tool took ~4 mins for the same and got stuck in loops bro built an entire beast by using all the modern tools that we could think of: undo trees, semantic search by meaning (by haskellforall), advanced refactoring, blast radius, advanced file context trees, restore points... i can keep going on semantic code search and context trees are the future of agentic coding and this tool proves it the feature i loved the most is semantic search and how it gets things done 2x faster with least possible tokens it makes an agent that actually knows what it’s doing and not just guessing, it makes meaning from your code similar to RAG. if you aren't optimizing your context, you are just burning money the developer says this tool is still under development, it can have unexpected behavior and the docs need updates but the video shows the reality of how fast it can be github: get here:
0:46

I cant believe this guy just made a permanent solution to context bloat and open sourced it all! when we tested this tool (Context+) for solving an issue on the OpenCode repository, the agent using this tool used ~6.5k fewer tokens, found the code and fixed it in half the time! the results were surprising: 6 to 10k tokens saved per prompt, completed task in ~2 minutes while the agent running without the tool took ~4 mins for the same and got stuck in loops bro built an entire beast by using all the modern tools that we could think of: undo trees, semantic search by meaning (by haskellforall), advanced refactoring, blast radius, advanced file context trees, restore points... i can keep going on semantic code search and context trees are the future of agentic coding and this tool proves it the feature i loved the most is semantic search and how it gets things done 2x faster with least possible tokens it makes an agent that actually knows what it’s doing and not just guessing, it makes meaning from your code similar to RAG. if you aren't optimizing your context, you are just burning money the developer says this tool is still under development, it can have unexpected behavior and the docs need updates but the video shows the reality of how fast it can be github: get here:

forloop

226,491 просмотров • 6 месяцев назад