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I am replacing codex with deepseek harness for this week 36,000+ stars on github the day it launched here is how it works (visualised). give this to your agent

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27,146 görüntüleme • 2 gün önce •via X (Twitter)

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WTFFF, this is absolutely insane 😳 i replaced my $200/mo Claude plan for deepseek harness and it costs nothing deepseek dropped their agent harness 2 days ago. 99.7K stars already everything is a plugin. MIT. FREE and you can run it for $0; free models, no credit card here is how you set it up: 1. install node.js 2. run npx deepseek-ai/dsh web 3. open 4. settings → add custom provider → free model (any free model provider) done. full agent harness for $0 dev preview, expect breaking changes try it before they add upgrades
0:41

WTFFF, this is absolutely insane 😳 i replaced my $200/mo Claude plan for deepseek harness and it costs nothing deepseek dropped their agent harness 2 days ago. 99.7K stars already everything is a plugin. MIT. FREE and you can run it for $0; free models, no credit card here is how you set it up: 1. install node.js 2. run npx deepseek-ai/dsh web 3. open 4. settings → add custom provider → free model (any free model provider) done. full agent harness for $0 dev preview, expect breaking changes try it before they add upgrades

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"The model is no longer the product. Codex, Perplexity Computer, or Claude Code - all are orchestration system. It takes a model and pairs it with an agent harness. What is an agent harness ? The rules for how the agent loops around" - Aravind Srinivas
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"The model is no longer the product. Codex, Perplexity Computer, or Claude Code - all are orchestration system. It takes a model and pairs it with an agent harness. What is an agent harness ? The rules for how the agent loops around" - Aravind Srinivas

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Hermes is the fastest growing AI Agent on GitHub... 100,000 stars And in this 32 min video, i made it way more powerful by connecting it to Browser Use:
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I have been testing Grok Bot for the last week and it's EXCELLENT It is your own personal fleet of AI agents doing work for you 24/7 In this video I give you a FULL walkthrough of the tool, how it works, and how to 100x your productivity with it SpaceXAI COOKED

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I love when Codex outsmarts me! Asked Codex to hack this badge that I got from Temporal's conference by putting Codex pets on it. I also gave it a photo of the badge along with it. Codex found the actual firmware of the badge on GitHub to have a starter 😂
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I love when Codex outsmarts me! Asked Codex to hack this badge that I got from Temporal's conference by putting Codex pets on it. I also gave it a photo of the badge along with it. Codex found the actual firmware of the badge on GitHub to have a starter 😂

dominik kundel

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holy shit this is a f**king gold mine I replaced opus 5 with deepseek v4-flash, it's basically free and someone figured out a way to run it's subagents as a self-improving loop inside codex [the setup takes 2 mins here is how] 1. clone the repo 'codex-self-imrpoving-loop' 2.give the '3 loop workflow' image to your agent 3. voila you are done save this no matter what. it'll be the most productive thing you do this week
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holy shit this is a f**king gold mine I replaced opus 5 with deepseek v4-flash, it's basically free and someone figured out a way to run it's subagents as a self-improving loop inside codex [the setup takes 2 mins here is how] 1. clone the repo 'codex-self-imrpoving-loop' 2.give the '3 loop workflow' image to your agent 3. voila you are done save this no matter what. it'll be the most productive thing you do this week

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holy sh*t this is f**king insane I cancelled my $200/mo Claude for this I replaced opus 5 with deepseek v4-flash and someone figured out to how to use them as subagents on codex [it takes 3 mins to set up here is how] 1. install this repo called 'model-router' 2. toggle subagent models > 'all selected models' 3. that's it
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holy sh*t this is f**king insane I cancelled my $200/mo Claude for this I replaced opus 5 with deepseek v4-flash and someone figured out to how to use them as subagents on codex [it takes 3 mins to set up here is how] 1. install this repo called 'model-router' 2. toggle subagent models > 'all selected models' 3. that's it

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This GitHub repo is gold for anyone running Claude Code/ Codex / Any coding agent at all. My usage limits almost last double since I started using this. An open source context layer that stops your agent from reading 40 files to answer one question. No API key, no billing, no rate limit tiers. Benchmarked against Claude Code baseline: 27x token efficiency, 36% lower cost, 89% fewer file reads, 49% fewer tool calls. Every number is reproducible, the harness is in the repo. 3.5k+ stars. 50k+ pip installs, 30+ contributors, works with Claude Code, Cursor and VS Code out of the box. pip install repowise and point it at your codebase.

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latiblack.base.eth

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I have been testing DeepSeek-V4-Pro with the Pi coding agent. I am mindblown by how well it works out of the box. A few notes: I spent a few hours building an LLM wiki with an agent powered entirely by DeepSeek-V4-Pro on Fireworks inference. This is the first time I feel like there is an open-weight model that can reason at the level of Claude and Codex. And it does this in a cost-effective way with support for 1M context length. To be clear, I am using DeepSeek-V4-Pro inside of Pi without any special configuration. It works out of the box. It's exciting that there is a model that can just be plugged into a basic harness like Pi, and it just works. I've never seen that before. Most models require lots of configuration and setup. DeepSeek's DeepSeek-V4-Pro is clearly good at agentic coding (probably the best from the open-weight models), but the model is also great on knowledge-intensive tasks where reasoning matters. The agent pulled agentic engineering best practices from different company docs (Anthropic, OpenAI, Google, Stripe, Meta, Modal, DeepSeek, Mistral, Cohere), searched and digested Reddit and HN threads, summarized arxiv papers, and surfaced trending GitHub repos. Then it distilled everything into actionable tips across categories. I love the Wiki it built. The quality is really good. Here is a snapshot of what the wiki looks like: DeepSeek-V4-Pro handled the task without breaking stride. Multi-step research queries, code generation for scaffolding, context-heavy reasoning across disparate sources. For coding specifically, this is the first open-weight model that genuinely feels like a Codex or Claude Code experience. It compares in capability and actual multi-turn agentic work. What made the loop feel so responsive was Fireworks' inference speed (the fastest in the market) and the fact that they actually validate models at the systems level before shipping. No corrupted reasoning traces. Just fast, reliable iteration. The hybrid CSA and HCA attention design cuts KV cache to just 10% and inference FLOPs by nearly 4x at 1M-token context. This is what makes the agent loop actually fast and cheap enough to run in practice. For devs who've been watching open-weight models close the gap but haven't found one that actually delivers in practice, this is the closest I've seen. Try it here:
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I have been testing DeepSeek-V4-Pro with the Pi coding agent. I am mindblown by how well it works out of the box. A few notes: I spent a few hours building an LLM wiki with an agent powered entirely by DeepSeek-V4-Pro on Fireworks inference. This is the first time I feel like there is an open-weight model that can reason at the level of Claude and Codex. And it does this in a cost-effective way with support for 1M context length. To be clear, I am using DeepSeek-V4-Pro inside of Pi without any special configuration. It works out of the box. It's exciting that there is a model that can just be plugged into a basic harness like Pi, and it just works. I've never seen that before. Most models require lots of configuration and setup. DeepSeek's DeepSeek-V4-Pro is clearly good at agentic coding (probably the best from the open-weight models), but the model is also great on knowledge-intensive tasks where reasoning matters. The agent pulled agentic engineering best practices from different company docs (Anthropic, OpenAI, Google, Stripe, Meta, Modal, DeepSeek, Mistral, Cohere), searched and digested Reddit and HN threads, summarized arxiv papers, and surfaced trending GitHub repos. Then it distilled everything into actionable tips across categories. I love the Wiki it built. The quality is really good. Here is a snapshot of what the wiki looks like: DeepSeek-V4-Pro handled the task without breaking stride. Multi-step research queries, code generation for scaffolding, context-heavy reasoning across disparate sources. For coding specifically, this is the first open-weight model that genuinely feels like a Codex or Claude Code experience. It compares in capability and actual multi-turn agentic work. What made the loop feel so responsive was Fireworks' inference speed (the fastest in the market) and the fact that they actually validate models at the systems level before shipping. No corrupted reasoning traces. Just fast, reliable iteration. The hybrid CSA and HCA attention design cuts KV cache to just 10% and inference FLOPs by nearly 4x at 1M-token context. This is what makes the agent loop actually fast and cheap enough to run in practice. For devs who've been watching open-weight models close the gap but haven't found one that actually delivers in practice, this is the closest I've seen. Try it here:

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DeepSeek's R1 Model has shocked the World. Here is how it works. #DeepSeek #R1 #AI
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DeepSeek's R1 Model has shocked the World. Here is how it works. #DeepSeek #R1 #AI

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87,427 görüntüleme • 1 yıl önce

This is huge! This fixes the universal problem with conversational agents: hallucinations! Every company that builds customer-facing agents struggles to align them with business rules and make them consistent. If you solve this, you'll become a hero overnight. Check out Parlant, a free, open-source library taking off on GitHub. This is why it's big: 1. You have 10x more control over what your conversation agent says 2. You control how it conducts conversations 3. You control the service protocols and rules it follows 4. You control what it can and can't say Here is how Parlant's engine works behind the scenes as soon as your agent receives a question from a customer: 1. It loads the necessary domain terminology 2. It finds the relevant guidelines to answer the question 3. It invokes your tools to gather any relevant information 4. It implements self-critique to craft/evaluate its response iteratively All of this makes it very hard for an agent to hallucinate. Here is the GitHub repository: And here is a paper showing the prompt engineering method Parlant uses behind the scenes (4.8% more accurate than Chain of Thought!):
0:37

This is huge! This fixes the universal problem with conversational agents: hallucinations! Every company that builds customer-facing agents struggles to align them with business rules and make them consistent. If you solve this, you'll become a hero overnight. Check out Parlant, a free, open-source library taking off on GitHub. This is why it's big: 1. You have 10x more control over what your conversation agent says 2. You control how it conducts conversations 3. You control the service protocols and rules it follows 4. You control what it can and can't say Here is how Parlant's engine works behind the scenes as soon as your agent receives a question from a customer: 1. It loads the necessary domain terminology 2. It finds the relevant guidelines to answer the question 3. It invokes your tools to gather any relevant information 4. It implements self-critique to craft/evaluate its response iteratively All of this makes it very hard for an agent to hallucinate. Here is the GitHub repository: And here is a paper showing the prompt engineering method Parlant uses behind the scenes (4.8% more accurate than Chain of Thought!):

Santiago

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After creating Remodex: Codex remote control for iOS I decided to chill a bit by building a browser sidebar inside Theo - t3.gg 's T3 Code You can open it with Cmd+Shift+B This software is so easy to "manipulate" and build upon Congrats to all the guys that put the work in it because it is great I certainly will be building more things with it For this one I decided to switch from the Codex App to the Codex CLI too just to see how it works And boy it was so good
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After creating Remodex: Codex remote control for iOS I decided to chill a bit by building a browser sidebar inside Theo - t3.gg 's T3 Code You can open it with Cmd+Shift+B This software is so easy to "manipulate" and build upon Congrats to all the guys that put the work in it because it is great I certainly will be building more things with it For this one I decided to switch from the Codex App to the Codex CLI too just to see how it works And boy it was so good

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Codex /goal With Hermes Agent is life-changing. I updated my Hermes agent skill to give Codex a goal on the fly using Telegram and track each one of those codex goals in a Kanban board. It has been really insane to see and track Codex execute goals in the wild.
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Codex /goal With Hermes Agent is life-changing. I updated my Hermes agent skill to give Codex a goal on the fly using Telegram and track each one of those codex goals in a Kanban board. It has been really insane to see and track Codex execute goals in the wild.

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