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Vibe coding is cool. But have you tried vibe-tuning? Here’s Claude Code using the Lightning Rod Labs SDK to turn messy Fed PDFs into a small, specialized economic forecaster. The agent: - parses raw historical PDFs - builds a training set - fine-tunes a smaller model - evaluates it...

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Ben Turtel

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423,542 просмотров • 4 месяцев назад •via X (Twitter)

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You can now fine-tune Llama 3 without writing a single line of code! We are moving at breakneck speed. I recorded a video to show you how to fine-tune any open-source model in a few minutes. I'm using a GPT capable of taking a problem and turning it into a fine-tuned model that will solve it. You don't have to write any code. You only need to explain to a GPT what problem you want to solve and tell it you want to use Llama 3. For example, "fine-tune Llama 3" or "deploy zephyr." It feels magic. The system will recommend a dataset and fine-tune the model for you. I'm using Monster API, a platform that specializes in making fine-tuning and deploying open-source models easy and fast. Their stack is well-optimized to maximize fine-tuning efficiency using techniques like Q-Lora and vLLM. They are behind the GPT. Here is what you need to do: 1. Create an account at 2. Load the GPT with the link below This is as simple as it gets. When you are done, you can click a button to deploy the model and start using it. I have 10,000 free credits for anyone using the code "SANTIAGO" in the dashboard. You can use these credits to access, fine-tune, and deploy these open-source models. You can also keep up with their latest updates, and get free credits and special offers on their Discord server:
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You can now fine-tune Llama 3 without writing a single line of code! We are moving at breakneck speed. I recorded a video to show you how to fine-tune any open-source model in a few minutes. I'm using a GPT capable of taking a problem and turning it into a fine-tuned model that will solve it. You don't have to write any code. You only need to explain to a GPT what problem you want to solve and tell it you want to use Llama 3. For example, "fine-tune Llama 3" or "deploy zephyr." It feels magic. The system will recommend a dataset and fine-tune the model for you. I'm using Monster API, a platform that specializes in making fine-tuning and deploying open-source models easy and fast. Their stack is well-optimized to maximize fine-tuning efficiency using techniques like Q-Lora and vLLM. They are behind the GPT. Here is what you need to do: 1. Create an account at 2. Load the GPT with the link below This is as simple as it gets. When you are done, you can click a button to deploy the model and start using it. I have 10,000 free credits for anyone using the code "SANTIAGO" in the dashboard. You can use these credits to access, fine-tune, and deploy these open-source models. You can also keep up with their latest updates, and get free credits and special offers on their Discord server:

Santiago

324,621 просмотров • 2 лет назад

Introducing EvoSkill V1, an open-source toolkit that takes a benchmark and a coding agent, and evolves it into a state-of-the-art specialist in minutes. Here’s all you need to start evolving, starting with your Claude Code ↓
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Introducing EvoSkill V1, an open-source toolkit that takes a benchmark and a coding agent, and evolves it into a state-of-the-art specialist in minutes. Here’s all you need to start evolving, starting with your Claude Code ↓

Sentient

30,202 просмотров • 5 месяцев назад

FREE 2M tokens. Opus 4.8, GPT-5.5, and every major coding model in one API key. Plugs directly into Claude Code. Inferall gives you access to the full model stack - Opus 4.8, GPT-5.5, and every other serious coding model - through one unified API. Here's the exact setup: → go to inferall(.)ai with VPN or proxy → sign in and register with any email (Google accounts work best if you hit rate limits) → create an API key - copy the key in format ifu_xxxxxxxxxxxxxxxx → go to Billing → Add a card → Activate free tier → add your card - a card with zero balance works fine(!!) → set country to United States during checkout Done. 2,000,000 free tokens loaded. Plug into Claude Code or any agent stack: BASE_URL: API_KEY: ifu_XXXXXXXXXXXXXX Works with Claude Code, OpenCode, Hermes Agent, any OpenAI-compatible setup. Opus 4.8 available immediately. 2M tokens is enough for weeks of serious coding sessions.
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FREE 2M tokens. Opus 4.8, GPT-5.5, and every major coding model in one API key. Plugs directly into Claude Code. Inferall gives you access to the full model stack - Opus 4.8, GPT-5.5, and every other serious coding model - through one unified API. Here's the exact setup: → go to inferall(.)ai with VPN or proxy → sign in and register with any email (Google accounts work best if you hit rate limits) → create an API key - copy the key in format ifu_xxxxxxxxxxxxxxxx → go to Billing → Add a card → Activate free tier → add your card - a card with zero balance works fine(!!) → set country to United States during checkout Done. 2,000,000 free tokens loaded. Plug into Claude Code or any agent stack: BASE_URL: API_KEY: ifu_XXXXXXXXXXXXXX Works with Claude Code, OpenCode, Hermes Agent, any OpenAI-compatible setup. Opus 4.8 available immediately. 2M tokens is enough for weeks of serious coding sessions.

Atenov int.

25,493 просмотров • 3 месяцев назад

We shipped an OSS 'vibe coding platform' (like v0) built with Vercel AI SDK, Gateway and Sandbox. We worked with @openai to tune the GPT-5 agent loop. It can write/read files, run commands, install packages, autofix errors… Demo oneshotting a multiplayer Pong in Go ↓
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We shipped an OSS 'vibe coding platform' (like v0) built with Vercel AI SDK, Gateway and Sandbox. We worked with @openai to tune the GPT-5 agent loop. It can write/read files, run commands, install packages, autofix errors… Demo oneshotting a multiplayer Pong in Go ↓

Guillermo Rauch

794,422 просмотров • 1 год назад

Kineto, a no-code platform by JetBrains, is powered by GPT-5 👏 GPT-5 gives Kineto a significant boost in creating single-purpose apps from prompts without any coding required. The new model is particularly useful when it comes to the look and feel of the apps it builds. Watch the video to hear Kineto Product Leader andrew zakonov explain how JetBrains Kineto can help bring your ideas to life:
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Kineto, a no-code platform by JetBrains, is powered by GPT-5 👏 GPT-5 gives Kineto a significant boost in creating single-purpose apps from prompts without any coding required. The new model is particularly useful when it comes to the look and feel of the apps it builds. Watch the video to hear Kineto Product Leader andrew zakonov explain how JetBrains Kineto can help bring your ideas to life:

JetBrains

13,415 просмотров • 1 год назад

Run your coding agent on a local model, with QVAC. OpenCode now plugs into a model on your own machine through our official plugin. That changes two things. Privacy by default. Your repo, your prompts, and every command the agent runs stay on your device. No third-party model ever sees your code. For an agent that reads your codebase and runs commands, that is the point, not a nice-to-have. New workflows. With no meter and no rate limit, the agent does not have to stop. Let it loop on a task, refactor a whole repo overnight, or run a watch-build-fix loop that keeps going. Setup takes a few minutes: one line in opencode.json and OpenCode runs on a local QVAC model. In the video demo, it handles three real developer tasks back to back, fully offline.
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Run your coding agent on a local model, with QVAC. OpenCode now plugs into a model on your own machine through our official plugin. That changes two things. Privacy by default. Your repo, your prompts, and every command the agent runs stay on your device. No third-party model ever sees your code. For an agent that reads your codebase and runs commands, that is the point, not a nice-to-have. New workflows. With no meter and no rate limit, the agent does not have to stop. Let it loop on a task, refactor a whole repo overnight, or run a watch-build-fix loop that keeps going. Setup takes a few minutes: one line in opencode.json and OpenCode runs on a local QVAC model. In the video demo, it handles three real developer tasks back to back, fully offline.

QVAC

11,382,936 просмотров • 3 месяцев назад

Steve Yegge, 40-year engineer (ex-Amazon, ex-Google): "There are 8 levels of using AI. Level 8 isn't a better prompt - it's you building your own orchestrator. Claude Code running Claude Code." we don't need smarter models. we need better loops. 3 productive hours a day. 100x the output. the bottleneck stopped being the model. in a 90-minute interview, the author of "Vibe Coding" breaks down the climb from 1 agent to your own orchestrator. 1 agent + several + 10+ by hand + your own orchestrator - that's the ladder. Worth more than a $500 course on agentic coding. Watch it, then save.
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Steve Yegge, 40-year engineer (ex-Amazon, ex-Google): "There are 8 levels of using AI. Level 8 isn't a better prompt - it's you building your own orchestrator. Claude Code running Claude Code." we don't need smarter models. we need better loops. 3 productive hours a day. 100x the output. the bottleneck stopped being the model. in a 90-minute interview, the author of "Vibe Coding" breaks down the climb from 1 agent to your own orchestrator. 1 agent + several + 10+ by hand + your own orchestrator - that's the ladder. Worth more than a $500 course on agentic coding. Watch it, then save.

shmidt

17,823 просмотров • 2 месяцев назад

I just found a way to use Claude Code completely free. Claude Code is Anthropic’s terminal coding agent that usually needs a paid API key to run. But a viral GitHub project called Free Claude Code, now sitting at 37k stars, lets you skip the billing entirely. It works as a tiny proxy that sits between Claude Code and free model providers like NVIDIA NIM, OpenRouter, DeepSeek, and Gemini. Every request Claude Code would send to Anthropic gets quietly rerouted to a free model on the other side. The interface stays the same. What’s actually thinking behind it changes. Setup takes a couple of quick commands and a free API key from NVIDIA NIM or OpenRouter. Paste it into the local dashboard, pick a model, and you’re building. The catch is you’re not really using Claude anymore. But when the code ships, does the model badge matter? -- I have shared the Github Link in my free Whatsapp Community ↓
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I just found a way to use Claude Code completely free. Claude Code is Anthropic’s terminal coding agent that usually needs a paid API key to run. But a viral GitHub project called Free Claude Code, now sitting at 37k stars, lets you skip the billing entirely. It works as a tiny proxy that sits between Claude Code and free model providers like NVIDIA NIM, OpenRouter, DeepSeek, and Gemini. Every request Claude Code would send to Anthropic gets quietly rerouted to a free model on the other side. The interface stays the same. What’s actually thinking behind it changes. Setup takes a couple of quick commands and a free API key from NVIDIA NIM or OpenRouter. Paste it into the local dashboard, pick a model, and you’re building. The catch is you’re not really using Claude anymore. But when the code ships, does the model badge matter? -- I have shared the Github Link in my free Whatsapp Community ↓

Vaibhav Sisinty

37,255 просмотров • 2 месяцев назад

Lead of Claude Code: "100% of our code at Anthropic is now shipped by Claude. Over 30% of it is written using /loops. Loop engineering is the future of coding. Loops are as big a shift as move from source coding to agents" in a 1-hour podcast, a Claude Code lead engineer shares the internal setup for building the #1 coding tool. It’s the most useful breakdown of how the Anthropic team uses Claude internally that I’ve seen on YouTube. Worth more than a $500 vibe-coding course.
1:37:24

Lead of Claude Code: "100% of our code at Anthropic is now shipped by Claude. Over 30% of it is written using /loops. Loop engineering is the future of coding. Loops are as big a shift as move from source coding to agents" in a 1-hour podcast, a Claude Code lead engineer shares the internal setup for building the #1 coding tool. It’s the most useful breakdown of how the Anthropic team uses Claude internally that I’ve seen on YouTube. Worth more than a $500 vibe-coding course.

Codez

37,770 просмотров • 3 месяцев назад

QVAC SDK will support in 0.9.0 (gonna be release in ~10 days) LoRA fine-tuning directly on-device, letting developers customize LLMs with their own data without sending anything to the cloud. You just load a base model, point it at your training dataset, and get a lightweight LoRA adapter back — all running locally. The fine-tuned model can then be used for inference immediately, with no extra setup. Why it matters: LoRA (Low-Rank Adaptation) fine-tuning lets you specialize a general-purpose language model for your specific use case — like matching a brand's tone, mastering domain terminology, or following a particular output format — using a fraction of the compute a full fine-tune would require. QVAC handles the entire workflow locally: dataset preparation, training with configurable hyperparameters, checkpoint saving, and seamless inference with the resulting adapter. Your data never leaves the device. The developer experience: Fine-tuning with QVAC is as simple as calling "sdk.finetune()" with your dataset and a few hyperparameters. Training runs entirely on your local hardware, produces a compact LoRA adapter file, and supports pause/resume so you can stop a job and pick it back up without losing progress. The result plugs straight into QVAC's inference pipeline — no model conversion, no deployment step, just immediate local completions with your fine-tuned model.
0:33

QVAC SDK will support in 0.9.0 (gonna be release in ~10 days) LoRA fine-tuning directly on-device, letting developers customize LLMs with their own data without sending anything to the cloud. You just load a base model, point it at your training dataset, and get a lightweight LoRA adapter back — all running locally. The fine-tuned model can then be used for inference immediately, with no extra setup. Why it matters: LoRA (Low-Rank Adaptation) fine-tuning lets you specialize a general-purpose language model for your specific use case — like matching a brand's tone, mastering domain terminology, or following a particular output format — using a fraction of the compute a full fine-tune would require. QVAC handles the entire workflow locally: dataset preparation, training with configurable hyperparameters, checkpoint saving, and seamless inference with the resulting adapter. Your data never leaves the device. The developer experience: Fine-tuning with QVAC is as simple as calling "sdk.finetune()" with your dataset and a few hyperparameters. Training runs entirely on your local hardware, produces a compact LoRA adapter file, and supports pause/resume so you can stop a job and pick it back up without losing progress. The result plugs straight into QVAC's inference pipeline — no model conversion, no deployment step, just immediate local completions with your fine-tuned model.

Paolo Ardoino 🤖

42,413 просмотров • 5 месяцев назад

Excited to introduce Ara, The cloud coding agent Bring your codex subscription and code with your teammate that uses claude code, together in web. Try it with a 100$ on us. Now generally available for the top coders
1:19

Excited to introduce Ara, The cloud coding agent Bring your codex subscription and code with your teammate that uses claude code, together in web. Try it with a 100$ on us. Now generally available for the top coders

Adi Singh

75,775 просмотров • 2 месяцев назад

Everyone expected GPT-5 to be a massive leap. But coding accuracy sits around 60% on SWE... meaning even the “best” model still ships bugs. So how do you vibe-code in 2025? One tool caught my eye: They rebuilt a Cursor app inside Cursor using their MCP to test, fix & ship. Looks crazy powerful, even if you’re non-technical. Check it out → cc TestSprite
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Everyone expected GPT-5 to be a massive leap. But coding accuracy sits around 60% on SWE... meaning even the “best” model still ships bugs. So how do you vibe-code in 2025? One tool caught my eye: They rebuilt a Cursor app inside Cursor using their MCP to test, fix & ship. Looks crazy powerful, even if you’re non-technical. Check it out → cc TestSprite

Eyisha Zyer

54,968 просмотров • 1 год назад

Sam Alba made an agent that analyzes your Dockerfile, makes it better, test that it builds correctly, then opens a PR - in 50 lines of code 🤯 Note the deep tracing - trust but verify! This was gpt-4o I believe. What model should he try next? 🧵
0:55

Sam Alba made an agent that analyzes your Dockerfile, makes it better, test that it builds correctly, then opens a PR - in 50 lines of code 🤯 Note the deep tracing - trust but verify! This was gpt-4o I believe. What model should he try next? 🧵

Solomon Hykes

15,097 просмотров • 1 год назад

New course: Spec-Driven Development with Coding Agents, built in partnership with JetBrains, and taught by Paul Everitt | @pauleveritt@fosstodon.org. Vibe coding is fast, but often produces code that doesn't match what you asked for. This short course teaches you spec-driven development: write a detailed spec defining what to build, and work with your coding agent to implement it. Many of the best developers already build this way. A spec lets you control large code changes with a few words, preserve context across agent sessions, and stay in control as your project grows in complexity. Skills you'll gain: - Write a detailed specification to define your mission, tech stack, and roadmap, giving your agent the context it needs from the start - Plan, implement, and validate features in iterative loops using a spec as your agent's guide - Apply the same repeatable workflow to both new and legacy codebases - Package your workflow into a portable agent skill that works across agents and IDEs Join and write specs that keep your coding agent on track!
2:51

New course: Spec-Driven Development with Coding Agents, built in partnership with JetBrains, and taught by Paul Everitt | @[email protected]. Vibe coding is fast, but often produces code that doesn't match what you asked for. This short course teaches you spec-driven development: write a detailed spec defining what to build, and work with your coding agent to implement it. Many of the best developers already build this way. A spec lets you control large code changes with a few words, preserve context across agent sessions, and stay in control as your project grows in complexity. Skills you'll gain: - Write a detailed specification to define your mission, tech stack, and roadmap, giving your agent the context it needs from the start - Plan, implement, and validate features in iterative loops using a spec as your agent's guide - Apply the same repeatable workflow to both new and legacy codebases - Package your workflow into a portable agent skill that works across agents and IDEs Join and write specs that keep your coding agent on track!

Andrew Ng

466,088 просмотров • 5 месяцев назад

OpenAI engineer explained every form of fine-tuning in 1 hour 46 minutes - better than $3000 fine-tuning bootcamps. pick your task -> try prompting first -> drop to SFT for style -> run DPO for preference -> run RFT for verifiable rewards -> ship a model 10x cheaper than GPT-5. That loop is why teams that fine-tune beat teams that only prompt on cost and speed. Prompting + SFT + DPO + RFT + OpenAI fine-tuning API - that's the stack. Watch and save it, then pick the right fine-tune for your task this week.
1:45:58

OpenAI engineer explained every form of fine-tuning in 1 hour 46 minutes - better than $3000 fine-tuning bootcamps. pick your task -> try prompting first -> drop to SFT for style -> run DPO for preference -> run RFT for verifiable rewards -> ship a model 10x cheaper than GPT-5. That loop is why teams that fine-tune beat teams that only prompt on cost and speed. Prompting + SFT + DPO + RFT + OpenAI fine-tuning API - that's the stack. Watch and save it, then pick the right fine-tune for your task this week.

h100envy

41,245 просмотров • 2 месяцев назад

Fable 5 just completely redesigned the website and the results are absolutely INSANE. It created a lightning bolt animation that strikes the Get Started CTA. It built an interactive demo of BridgeSpace from scratch. A perfect 1:1 of the real app. It created 3 marketing videos, one for each vibe coding tool in the BridgeMind ecosystem. Fable 5 is by far the best model at UI design. I don't know if GPT 5.6 can beat this.
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Fable 5 just completely redesigned the website and the results are absolutely INSANE. It created a lightning bolt animation that strikes the Get Started CTA. It built an interactive demo of BridgeSpace from scratch. A perfect 1:1 of the real app. It created 3 marketing videos, one for each vibe coding tool in the BridgeMind ecosystem. Fable 5 is by far the best model at UI design. I don't know if GPT 5.6 can beat this.

BridgeMind

53,728 просмотров • 2 месяцев назад