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ClawRouter for OpenClaw🦞 reach 2000 stars🌟 within 7d launch. We shipped 5 fixes in the last 24 hrs: • New /v1/responses endpoint for Grok • Fixed nested output parsing • Real usage stats now visible on /stats • Free GPT 120B fallback AlwaysOn • Free GPT 120B with shortcut... show more

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$50 IN FREE CREDITS FOR GLM 5.2, KIMI K3 AND DEEPSEEK V4 PRO, ON A CODE THE COMPANY PUBLISHED ITSELF • ai&, the inference layer > Frontier models at up to 80% lower cost: > GLM 5.2, Kimi K3, Kimi K2.7 Code, DeepSeek V4 Pro and V4 Flash, plus Qwen3.6 27B, Gemma 4 31B and gpt-oss-120b. > OpenAI-compatible endpoint, so it drops into any agent or IDE you already run. • where the discount comes from > They route across AMD, NVIDIA and Tenstorrent, sending each workload to the silicon that suits it. > Everyone else tunes on one kind of chip, so the saving is architectural rather than promotional. Claiming it -> Credits in the top right, pick $50, apply "UNITABETAI" at checkout. The code has been live since their June launch, so run it on your own account before you plan around it ↓

$50 IN FREE CREDITS FOR GLM 5.2, KIMI K3 AND DEEPSEEK V4 PRO, ON A CODE THE COMPANY PUBLISHED ITSELF • ai&, the inference layer > Frontier models at up to 80% lower cost: > GLM 5.2, Kimi K3, Kimi K2.7 Code, DeepSeek V4 Pro and V4 Flash, plus Qwen3.6 27B, Gemma 4 31B and gpt-oss-120b. > OpenAI-compatible endpoint, so it drops into any agent or IDE you already run. • where the discount comes from > They route across AMD, NVIDIA and Tenstorrent, sending each workload to the silicon that suits it. > Everyone else tunes on one kind of chip, so the saving is architectural rather than promotional. Claiming it -> Credits in the top right, pick $50, apply "UNITABETAI" at checkout. The code has been live since their June launch, so run it on your own account before you plan around it ↓

slash1s

27,213 Aufrufe • vor 25 Tagen

timelapse #86 (15 hrs): - got my first OOM on 8xB200 node - defaulting back to grok-code-fast-1, the fastest reliable coding model with by far most intuitive instruction following, combined with grok 4 fast reasoning to plan before i let grok code work its magic - drank 2 large tim hortons iced capps, loaded myself w/ creatine, daily nootropics - tried out gpt-5-codex but it simply doesnt match the speed i require when i go deep into one thing at a time sequentially - got caught watching youtube videos in the middle, need to make sure i block any and all content that could get in my way - caught up on all book revisions so getting super ahead with other chapters - developed an overnight addiction to switching color themes in cursor - did some pair programming w/ Kearm h/eng using Tuple on free trial - applying for O-1

timelapse #86 (15 hrs): - got my first OOM on 8xB200 node - defaulting back to grok-code-fast-1, the fastest reliable coding model with by far most intuitive instruction following, combined with grok 4 fast reasoning to plan before i let grok code work its magic - drank 2 large tim hortons iced capps, loaded myself w/ creatine, daily nootropics - tried out gpt-5-codex but it simply doesnt match the speed i require when i go deep into one thing at a time sequentially - got caught watching youtube videos in the middle, need to make sure i block any and all content that could get in my way - caught up on all book revisions so getting super ahead with other chapters - developed an overnight addiction to switching color themes in cursor - did some pair programming w/ Kearm h/eng using Tuple on free trial - applying for O-1

Elliot Arledge

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Love OpenClaw but hate the token burn? 💸 Running a 24/7 agent on GPT-4/Claude is overkill. You don't need SOTA reasoning to handle a greeting or a simple lookup. LLMRouter 🩷 OpenClaw The first production-ready, agentic router designed to plug directly into OpenClaw. LLMRouter fully supports Multimodal, Memory-Equipped routing that adapts 100% to your needs—compatible with FREE open-source models. The Logic is Simple:🔹 Simple query → Cheap/Local model 🔹 Complex reasoning → SOTA model (GPT-4/Claude 3.5) 🔹 Multimodal input → Vision/Audio specialized model Why this isn't just a switch: 📉 30–50% drop in inference costs 🧠 Zero loss in response quality 🔓 100% compatible with OpenAI-style APIs 🚀 Deploy in Seconds General Usage: Get the library and serve any model: pip install llmrouter-lib llmrouter serve OpenClaw Native Integration: Want the full agent experience? LLMRouter built a dedicated integration for OpenClaw users: LLMRouter Resources: 🔗 Repo: 📦 PyPI: 🤝 Works with: Route smarter. Train your own. Pay less. More on LLMRouter: Most routers are static if/else. LLMRouter is an intelligent, learning system. 🤖 Agentic & Memory-Aware: Decisions aren't stateless. We use RAG-powered memory to route based on context and history. 👤 Fully Personalized: It learns from your usage patterns via RL feedback loops. 🔬 Research-Grade: Switch between 16+ routing strategies (KNN, SVM, BERT, Graph, RL) with a single flag.

Love OpenClaw but hate the token burn? 💸 Running a 24/7 agent on GPT-4/Claude is overkill. You don't need SOTA reasoning to handle a greeting or a simple lookup. LLMRouter 🩷 OpenClaw The first production-ready, agentic router designed to plug directly into OpenClaw. LLMRouter fully supports Multimodal, Memory-Equipped routing that adapts 100% to your needs—compatible with FREE open-source models. The Logic is Simple:🔹 Simple query → Cheap/Local model 🔹 Complex reasoning → SOTA model (GPT-4/Claude 3.5) 🔹 Multimodal input → Vision/Audio specialized model Why this isn't just a switch: 📉 30–50% drop in inference costs 🧠 Zero loss in response quality 🔓 100% compatible with OpenAI-style APIs 🚀 Deploy in Seconds General Usage: Get the library and serve any model: pip install llmrouter-lib llmrouter serve OpenClaw Native Integration: Want the full agent experience? LLMRouter built a dedicated integration for OpenClaw users: LLMRouter Resources: 🔗 Repo: 📦 PyPI: 🤝 Works with: Route smarter. Train your own. Pay less. More on LLMRouter: Most routers are static if/else. LLMRouter is an intelligent, learning system. 🤖 Agentic & Memory-Aware: Decisions aren't stateless. We use RAG-powered memory to route based on context and history. 👤 Fully Personalized: It learns from your usage patterns via RL feedback loops. 🔬 Research-Grade: Switch between 16+ routing strategies (KNN, SVM, BERT, Graph, RL) with a single flag.

Jiaxuan You

31,451 Aufrufe • vor 6 Monaten

Introducing LiteParse - the best model-free document parsing tool for AI agents 💫 ✅ It’s completely open-source and free. ✅ No GPU required, will process ~500 pages in 2 seconds on commodity hardware ✅ More accurate than PyPDF, PyMuPDF, Markdown. Also way more readable - see below for how we parse tables!! ✅ Supports 50+ file formats, from PDFs to Office docs to images ✅ Is designed to plug and play with Claude Code, OpenClaw, and any other AI agent with a one-line skills install. Supports native screenshotting capabilities. We spent years building up LlamaParse by orchestrating state-of-the-art VLMs over the most complex documents. Along the way we realized that you could get quite far on most docs through fast and cheap text parsing. Take a look at the video below. For really complex tables within PDFs, we output them in a spatial grid that’s both AI and human-interpretable. Any other free/light parser light PyPDF will destroy the representation of this table and output a sequential list. This is not a replacement for a VLM-based OCR tool (it requires 0 GPUs and doesn’t use models), but it is shocking how good it is to parse most documents. Huge shoutout to Logan Markewich and Clelia Bertelli (🦀/acc) for all the work here. Come check it out: Repo:

Introducing LiteParse - the best model-free document parsing tool for AI agents 💫 ✅ It’s completely open-source and free. ✅ No GPU required, will process ~500 pages in 2 seconds on commodity hardware ✅ More accurate than PyPDF, PyMuPDF, Markdown. Also way more readable - see below for how we parse tables!! ✅ Supports 50+ file formats, from PDFs to Office docs to images ✅ Is designed to plug and play with Claude Code, OpenClaw, and any other AI agent with a one-line skills install. Supports native screenshotting capabilities. We spent years building up LlamaParse by orchestrating state-of-the-art VLMs over the most complex documents. Along the way we realized that you could get quite far on most docs through fast and cheap text parsing. Take a look at the video below. For really complex tables within PDFs, we output them in a spatial grid that’s both AI and human-interpretable. Any other free/light parser light PyPDF will destroy the representation of this table and output a sequential list. This is not a replacement for a VLM-based OCR tool (it requires 0 GPUs and doesn’t use models), but it is shocking how good it is to parse most documents. Huge shoutout to Logan Markewich and Clelia Bertelli (🦀/acc) for all the work here. Come check it out: Repo:

Jerry Liu

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Grok Build CLI just got an update with v0.2.113! 🚀 Changelog v0.2.113 Features: • MCP servers can now be enabled or disabled directly from the CLI with `grok mcp enable ` and `grok mcp disable `. • Full plan markdown can now be copied to the clipboard with `y` during plan approval or preview. • Added support for the new SuperGrok Plus subscription tier in authentication and feature gating. • Enabled automatic recovery from repetitive loops in model output by default. Performance: • Cold start shows the UI instantly while models and settings load in the background. • Large session forks and resumes now use far less memory and avoid spikes. • Prevented thread exhaustion on high-core shared machines by limiting the workspace daemon's worker threads. Bug Fixes: • Terminal command output is no longer lost or duplicated when the gateway is unreachable. • Invalid MCP server entries in config.toml no longer prevent Grok from starting; problems are shown in `grok inspect`. • SessionEnd hooks now run on exit in non-leader TUI and headless sessions. • Paste chips now display with the correct background in inline prompts and question inputs. • Pasted content chips now behave consistently when editing answers in the question view. • Background task status now shows only elapsed duration instead of absolute timestamps. • Session lists no longer drop real sessions when the remote registry reports an outdated turn count of zero. • /loop now stores prompts that include stop conditions so recurring tasks can terminate themselves when done. • Reduced spurious warning messages for common auth and config scenarios. • Fixed conda activation (and other sourced scripts that read $@) when using persistent or login-capture shells. • Fixed stuck background-task tray rows after long foreground shell commands complete. • Agent subprocesses and idle inhibitors are now cleaned up when the parent CLI process dies unexpectedly. • Fixed truncated plans in minimal mode and improved visual separation between reasoning and output (including NO_COLOR). • Fixed credential loss across multiple grok processes sharing the same auth file. • Fixed doubled Enter and other keys on older Alacritty terminals. • Fixed false paywall messages for free-tier and unmatched users.

Grok Build CLI just got an update with v0.2.113! 🚀 Changelog v0.2.113 Features: • MCP servers can now be enabled or disabled directly from the CLI with `grok mcp enable ` and `grok mcp disable `. • Full plan markdown can now be copied to the clipboard with `y` during plan approval or preview. • Added support for the new SuperGrok Plus subscription tier in authentication and feature gating. • Enabled automatic recovery from repetitive loops in model output by default. Performance: • Cold start shows the UI instantly while models and settings load in the background. • Large session forks and resumes now use far less memory and avoid spikes. • Prevented thread exhaustion on high-core shared machines by limiting the workspace daemon's worker threads. Bug Fixes: • Terminal command output is no longer lost or duplicated when the gateway is unreachable. • Invalid MCP server entries in config.toml no longer prevent Grok from starting; problems are shown in `grok inspect`. • SessionEnd hooks now run on exit in non-leader TUI and headless sessions. • Paste chips now display with the correct background in inline prompts and question inputs. • Pasted content chips now behave consistently when editing answers in the question view. • Background task status now shows only elapsed duration instead of absolute timestamps. • Session lists no longer drop real sessions when the remote registry reports an outdated turn count of zero. • /loop now stores prompts that include stop conditions so recurring tasks can terminate themselves when done. • Reduced spurious warning messages for common auth and config scenarios. • Fixed conda activation (and other sourced scripts that read $@) when using persistent or login-capture shells. • Fixed stuck background-task tray rows after long foreground shell commands complete. • Agent subprocesses and idle inhibitors are now cleaned up when the parent CLI process dies unexpectedly. • Fixed truncated plans in minimal mode and improved visual separation between reasoning and output (including NO_COLOR). • Fixed credential loss across multiple grok processes sharing the same auth file. • Fixed doubled Enter and other keys on older Alacritty terminals. • Fixed false paywall messages for free-tier and unmatched users.

Puck

94,737 Aufrufe • vor 1 Monat

OpenAI and Anthropic news roundup (Week 18, 2026) OpenAI open-sourced Symphony spec for Codex orchestration, published "Our principles" post, announced amended Microsoft partnership, achieved FedRAMP Moderate authorization, posted commitment to community safety, brought OpenAI models, Codex, and Managed Agents to AWS, shared cybersecurity action plan, posted Stargate compute infrastructure update, published "Where the goblins came from" post, posted Auto-review write-up for Codex, introduced Advanced Account Security, announced DevDay 2026, repositioned Codex as personal assistant for everyday work, launched Codex setup import, added Codex pets, announced GPT-5.5 party for next week, shared GPT-5.5 one-week launch metrics, and rolled out 360 worlds in ChatGPT Images on web, plus discovered Custom dictionary feature in development, ChatGPT search EU recipient numbers, confirmed new model selector in composer, and updated privacy policy with marketing cookies on by default for free users Anthropic opened Sydney office with new General Manager, launched Claude for Creative Work with new connectors, Claude Code can now send push notifications to your phone, published Introspection Adapters research, BioMysteryBench evaluation, "How people ask Claude for personal guidance" study, launched Claude Security in public beta, and preparing for Code with Claude developer conference next week, plus discovered "Cardinal" stats feature in development and internal red teaming for Claude Jupiter V1 P, and more

OpenAI and Anthropic news roundup (Week 18, 2026) OpenAI open-sourced Symphony spec for Codex orchestration, published "Our principles" post, announced amended Microsoft partnership, achieved FedRAMP Moderate authorization, posted commitment to community safety, brought OpenAI models, Codex, and Managed Agents to AWS, shared cybersecurity action plan, posted Stargate compute infrastructure update, published "Where the goblins came from" post, posted Auto-review write-up for Codex, introduced Advanced Account Security, announced DevDay 2026, repositioned Codex as personal assistant for everyday work, launched Codex setup import, added Codex pets, announced GPT-5.5 party for next week, shared GPT-5.5 one-week launch metrics, and rolled out 360 worlds in ChatGPT Images on web, plus discovered Custom dictionary feature in development, ChatGPT search EU recipient numbers, confirmed new model selector in composer, and updated privacy policy with marketing cookies on by default for free users Anthropic opened Sydney office with new General Manager, launched Claude for Creative Work with new connectors, Claude Code can now send push notifications to your phone, published Introspection Adapters research, BioMysteryBench evaluation, "How people ask Claude for personal guidance" study, launched Claude Security in public beta, and preparing for Code with Claude developer conference next week, plus discovered "Cardinal" stats feature in development and internal red teaming for Claude Jupiter V1 P, and more

Tibor Blaho

12,254 Aufrufe • vor 4 Monaten

BREAKING: Introducing All Access from Every 🪨, our new membership tier for the best builders in AI All Access subs get the Builder Pack which includes $7,000 in credits and free usage to the models + tool stack we use Every 🪨. All Access subscribers get: - $1,000 in Codex / @ChatGPTapp for Work credits - 12 months free of Cursor Pro+ - $4,000 in PostHog credits including self-driving to automatically fix bugs and identify issues in your production app - 1 year free of Framer - 6 months free of Notion And much more! (Did I mention $1,000 in Codex credits? It's time to build!) Get all access: Why All Access and the Builder Pack This is the best time in history to build something. For a long time, it’s been possible to one-shot impressive demos, but they’d fall flat the minute they hit production. But the release of GPT-5.6-Sol and Fable 5 heralds a new era: Everyone can build, launch, and maintain the software that they’ve always dreamed of. Everyone is a builder now. There’s just one catch: Building with AI is very expensive. (Ask me how I know.) (Alright, I’ll tell you. I accidentally used 2 billion tokens overnight this week on a big GPT-5.6-Sol run. Worth it.) This is unique in the history of technology. For most of the personal computing era, a billionaire and a solo builder could buy essentially the same top-of-the-line Mac. AI changes that: The more tokens you can afford, the more you can make. And we want to make that accessible to more people. That’s why the main feature of our new All Access plan is the Builder Pack: more than $7,000 in credits and discounts on the full stack we use to run Every, from idea to production—Codex, Claude, PostHog, Render, Gemini, FLORA, and more. Early-bird membership is only $500/year for the next 24 hours—and the Codex credits alone are worth $1,000. (I could’ve used it for my overnight run this week.) Now we’re handing it to you. Get all access: Meet the Builder Pack It's got more than $7,000 in offers from 10 of the AI products we use to write, design, build, and run Every 🪨: BUILD - $1,000 in Codex credits plus one month of ChatGPT for business - Twelve months free of Cursor Pro+ - One month free of Claude Max - Three months free of Google AI Pro DESIGN - One year free of Framer Pro - One month free of FLORA © Max HOST - $300 in Render credits IMPROVE - $4,000 in PostHog credits - Six months free of Notion Business - Six months free of AgentMail We rely on these every day, and we tried to put together a package that helps you comprehensively for each part of the process of building and running software in AI. What comes with All Access - Everything in an existing paid Every membership: our daily writing, guides, camps, and software like Monologue, Cora, Sparkle, and Spiral - The Builder Pack, with more than $7,000 in partner offers - Unlimited email accounts use of Cora and unlimited Spiral usage - Members-only programming with me and the Every team and me Get All Access:

BREAKING: Introducing All Access from Every 🪨, our new membership tier for the best builders in AI All Access subs get the Builder Pack which includes $7,000 in credits and free usage to the models + tool stack we use Every 🪨. All Access subscribers get: - $1,000 in Codex / @ChatGPTapp for Work credits - 12 months free of Cursor Pro+ - $4,000 in PostHog credits including self-driving to automatically fix bugs and identify issues in your production app - 1 year free of Framer - 6 months free of Notion And much more! (Did I mention $1,000 in Codex credits? It's time to build!) Get all access: Why All Access and the Builder Pack This is the best time in history to build something. For a long time, it’s been possible to one-shot impressive demos, but they’d fall flat the minute they hit production. But the release of GPT-5.6-Sol and Fable 5 heralds a new era: Everyone can build, launch, and maintain the software that they’ve always dreamed of. Everyone is a builder now. There’s just one catch: Building with AI is very expensive. (Ask me how I know.) (Alright, I’ll tell you. I accidentally used 2 billion tokens overnight this week on a big GPT-5.6-Sol run. Worth it.) This is unique in the history of technology. For most of the personal computing era, a billionaire and a solo builder could buy essentially the same top-of-the-line Mac. AI changes that: The more tokens you can afford, the more you can make. And we want to make that accessible to more people. That’s why the main feature of our new All Access plan is the Builder Pack: more than $7,000 in credits and discounts on the full stack we use to run Every, from idea to production—Codex, Claude, PostHog, Render, Gemini, FLORA, and more. Early-bird membership is only $500/year for the next 24 hours—and the Codex credits alone are worth $1,000. (I could’ve used it for my overnight run this week.) Now we’re handing it to you. Get all access: Meet the Builder Pack It's got more than $7,000 in offers from 10 of the AI products we use to write, design, build, and run Every 🪨: BUILD - $1,000 in Codex credits plus one month of ChatGPT for business - Twelve months free of Cursor Pro+ - One month free of Claude Max - Three months free of Google AI Pro DESIGN - One year free of Framer Pro - One month free of FLORA © Max HOST - $300 in Render credits IMPROVE - $4,000 in PostHog credits - Six months free of Notion Business - Six months free of AgentMail We rely on these every day, and we tried to put together a package that helps you comprehensively for each part of the process of building and running software in AI. What comes with All Access - Everything in an existing paid Every membership: our daily writing, guides, camps, and software like Monologue, Cora, Sparkle, and Spiral - The Builder Pack, with more than $7,000 in partner offers - Unlimited email accounts use of Cora and unlimited Spiral usage - Members-only programming with me and the Every team and me Get All Access:

Dan Shipper 📧

183,025 Aufrufe • vor 1 Monat

AI is creating a new kind of creator economy. One where anyone can launch complex apps, agents, trading systems, research tools, games, and community experiments in minutes. Not just content people consume. AI-native experiences people can use, share, and grow together. That is the bigger idea behind the AI Trading Arena: a live DeFAI environment where AI-created strategies compete on real crypto prices, with every trade, tick, P&L update, and leaderboard visible to everyone. The latest expansion makes it even more fascinating: AI is now designing new trading strategies and adding them into the Arena to compete with strategies from frontier models like GPT-5, Claude, Gemini, Grok, DeepSeek, and Llama. Just agents, markets, and performance in the open. And the Arena is only one example. On ChainOpera AI, creators can launch AI-native experiences in minutes, then grow them with the community that uses them. $COAI is the fuel for this creator economy: creators launch, users participate, and AI-native apps come alive through real community usage. What would you be built next?

AI is creating a new kind of creator economy. One where anyone can launch complex apps, agents, trading systems, research tools, games, and community experiments in minutes. Not just content people consume. AI-native experiences people can use, share, and grow together. That is the bigger idea behind the AI Trading Arena: a live DeFAI environment where AI-created strategies compete on real crypto prices, with every trade, tick, P&L update, and leaderboard visible to everyone. The latest expansion makes it even more fascinating: AI is now designing new trading strategies and adding them into the Arena to compete with strategies from frontier models like GPT-5, Claude, Gemini, Grok, DeepSeek, and Llama. Just agents, markets, and performance in the open. And the Arena is only one example. On ChainOpera AI, creators can launch AI-native experiences in minutes, then grow them with the community that uses them. $COAI is the fuel for this creator economy: creators launch, users participate, and AI-native apps come alive through real community usage. What would you be built next?

ChainOpera AI

16,700 Aufrufe • vor 3 Monaten

This is INSANE. My OpenClaw🦞 just called booked me a reservation. Here’s what actually happened: 1/ The Setup I gave my OpenClaw a real phone number. Most people would say that’s risky. I think the opposite. Why sit on hold when AI can do it for you? I installed the Clawdtalk skill, generated a phone number + PIN, and was live in minutes. That’s it. No complex setup. 2/ The Test Valentine’s Day was coming up. I told OpenClaw: “Find me a restaurants near me for 2 people on Saturday.” I genuinely didn’t think it would work. It called 5 restaurants. At the same time. Spoke to real humans. Booked 1 with availability. No hold music. No back and forth. No wasted time. 3/ The Shift The infrastructure is changing. OpenClaw isn’t just a chatbot. It’s an execution layer. The interface to the real world is becoming API-accessible. Restaurants. Doctors. Contractors. Front desks. If it has a phone number, it’s now programmable. Today: dinner reservations. Tomorrow: vendor negotiations, recruiting screens, appointment backlogs. Anything that requires: – calling – waiting – confirming – coordinating …can now be delegated. We’re entering the era of agentic execution. I spoke with the Clawdtalk team and got a free usage tier for builders in my audience. Comment “Clawdtalk” and I’ll DM you the link. Let’s build.

This is INSANE. My OpenClaw🦞 just called booked me a reservation. Here’s what actually happened: 1/ The Setup I gave my OpenClaw a real phone number. Most people would say that’s risky. I think the opposite. Why sit on hold when AI can do it for you? I installed the Clawdtalk skill, generated a phone number + PIN, and was live in minutes. That’s it. No complex setup. 2/ The Test Valentine’s Day was coming up. I told OpenClaw: “Find me a restaurants near me for 2 people on Saturday.” I genuinely didn’t think it would work. It called 5 restaurants. At the same time. Spoke to real humans. Booked 1 with availability. No hold music. No back and forth. No wasted time. 3/ The Shift The infrastructure is changing. OpenClaw isn’t just a chatbot. It’s an execution layer. The interface to the real world is becoming API-accessible. Restaurants. Doctors. Contractors. Front desks. If it has a phone number, it’s now programmable. Today: dinner reservations. Tomorrow: vendor negotiations, recruiting screens, appointment backlogs. Anything that requires: – calling – waiting – confirming – coordinating …can now be delegated. We’re entering the era of agentic execution. I spoke with the Clawdtalk team and got a free usage tier for builders in my audience. Comment “Clawdtalk” and I’ll DM you the link. Let’s build.

Jacob Klug

18,908 Aufrufe • vor 6 Monaten

🚀 Traffic Cameras, Custom Storm Tracks, and More We've just released some powerful new features — all available for FREE: Traffic Cameras — View live camera feeds directly on the map. We're starting with 5 US states: Kansas, Maryland, Minnesota, Tennessee, and Virginia. Custom Storm Tracks — Draw your own storm path on the map, set the speed, and instantly see a cone of uncertainty with estimated impact times for cities along the way. Weather Office Details — Tap any NWS office to view contact info, coverage stats, the latest Area Forecast Discussion (AFD), and all active alerts organized by type. Hazcams — Browse all active Hazcams in one place. Search by name, see viewer counts, and jump to any camera on the map. Available now on: iOS: Android: Browser: And to Plus/Pro subscribers using our Windows/Mac/Linux App

🚀 Traffic Cameras, Custom Storm Tracks, and More We've just released some powerful new features — all available for FREE: Traffic Cameras — View live camera feeds directly on the map. We're starting with 5 US states: Kansas, Maryland, Minnesota, Tennessee, and Virginia. Custom Storm Tracks — Draw your own storm path on the map, set the speed, and instantly see a cone of uncertainty with estimated impact times for cities along the way. Weather Office Details — Tap any NWS office to view contact info, coverage stats, the latest Area Forecast Discussion (AFD), and all active alerts organized by type. Hazcams — Browse all active Hazcams in one place. Search by name, see viewer counts, and jump to any camera on the map. Available now on: iOS: Android: Browser: And to Plus/Pro subscribers using our Windows/Mac/Linux App

WeatherWise.app

32,432 Aufrufe • vor 7 Monaten

OpenAI and Anthropic this week: GPT-Red, Fable 5 plan changes, and free Claude for teachers (Week 29, 2026) OpenAI introduced GPT-Red, an internal automated red teamer trained through adversarial self-play to find prompt injection vulnerabilities at scale Training against it made GPT-5.6 their most robust model against prompt injections to date And there's a hidden "GPT-RED // Invader Patrol" game in the article OpenAI also published GPT-Live usage limits, brought ChatGPT back to WhatsApp in the European Economic Area, rolled out a new unified search in ChatGPT across chats, projects, images, and documents, raised the custom instructions limit from 1,500 to 5,000 characters, and updated the ChatGPT desktop app with a clearer Chat and Work layout, unified Recents, Projects, and cloud sync ChatGPT Finances got Apple Card and Savings support On the publishing side, OpenAI shared articles on managing AI investments in the agentic era, why teens deserve access to safe AI, state and federal AI safety action, and Sarah Friar's useful intelligence per dollar scorecard Beyond the official channels, Bloomberg reported OpenAI's first device will be a movable screenless smart speaker, and The New York Times reported a Kalshi partnership showing World Cup odds in ChatGPT search Work Louder launched the Codex Micro keypad built for Codex, OpenAI merch is back in a new Supply Co. shop, and I spotted a new private equity and investment management community in the works Anthropic made Claude Fable 5 standard in all Max and Team Premium plans at 50% of limits starting July 20, with a one-time $100 credit for Pro and Team Standard, after extending Fable 5 access on paid plans through July 19 Claude Code weekly limits stay 50% higher through August 19 Anthropic also introduced Claude for Teachers with free premium Claude access for verified K-12 educators in the US, committed 10 million Canadian dollars to Canadian AI research, and published a Canada Economic Index country brief Artifacts in Claude Code now support public sharing, multiplayer editing, and MCP connectors, plus creation via Claude Tag Claude Code got /code-review effort levels up to ultra, and HIPAA configuration is now self-serve for Claude organizations On the research side, Anthropic published work on Claude's values across models and languages, and four new agentic misalignment case studies

OpenAI and Anthropic this week: GPT-Red, Fable 5 plan changes, and free Claude for teachers (Week 29, 2026) OpenAI introduced GPT-Red, an internal automated red teamer trained through adversarial self-play to find prompt injection vulnerabilities at scale Training against it made GPT-5.6 their most robust model against prompt injections to date And there's a hidden "GPT-RED // Invader Patrol" game in the article OpenAI also published GPT-Live usage limits, brought ChatGPT back to WhatsApp in the European Economic Area, rolled out a new unified search in ChatGPT across chats, projects, images, and documents, raised the custom instructions limit from 1,500 to 5,000 characters, and updated the ChatGPT desktop app with a clearer Chat and Work layout, unified Recents, Projects, and cloud sync ChatGPT Finances got Apple Card and Savings support On the publishing side, OpenAI shared articles on managing AI investments in the agentic era, why teens deserve access to safe AI, state and federal AI safety action, and Sarah Friar's useful intelligence per dollar scorecard Beyond the official channels, Bloomberg reported OpenAI's first device will be a movable screenless smart speaker, and The New York Times reported a Kalshi partnership showing World Cup odds in ChatGPT search Work Louder launched the Codex Micro keypad built for Codex, OpenAI merch is back in a new Supply Co. shop, and I spotted a new private equity and investment management community in the works Anthropic made Claude Fable 5 standard in all Max and Team Premium plans at 50% of limits starting July 20, with a one-time $100 credit for Pro and Team Standard, after extending Fable 5 access on paid plans through July 19 Claude Code weekly limits stay 50% higher through August 19 Anthropic also introduced Claude for Teachers with free premium Claude access for verified K-12 educators in the US, committed 10 million Canadian dollars to Canadian AI research, and published a Canada Economic Index country brief Artifacts in Claude Code now support public sharing, multiplayer editing, and MCP connectors, plus creation via Claude Tag Claude Code got /code-review effort levels up to ultra, and HIPAA configuration is now self-serve for Claude organizations On the research side, Anthropic published work on Claude's values across models and languages, and four new agentic misalignment case studies

Tibor Blaho

13,137 Aufrufe • vor 1 Monat

Introducing Tracelight 1.0 After six months, we are live with 5 of the 10 biggest management consultancies in the world, as well as PE funds and asset managers with over $600B in AUM. Tracelight is the best AI add-in to Excel. In testing against the leading alternative add-ins, Tracelight 1.0 was: - The most accurate - 2x faster building analysis on average - 20x faster at finding human errors in complex spreadsheets We’ve been building with early adopters and enterprise partners for months. You can now reach a completely new level of performance in Excel. That’s why today we’re proud to launch a major new version. To celebrate, we're giving 1 month of Tracelight Pro for free to anyone who comments LAUNCH below or TAGs a friend who needs this

Introducing Tracelight 1.0 After six months, we are live with 5 of the 10 biggest management consultancies in the world, as well as PE funds and asset managers with over $600B in AUM. Tracelight is the best AI add-in to Excel. In testing against the leading alternative add-ins, Tracelight 1.0 was: - The most accurate - 2x faster building analysis on average - 20x faster at finding human errors in complex spreadsheets We’ve been building with early adopters and enterprise partners for months. You can now reach a completely new level of performance in Excel. That’s why today we’re proud to launch a major new version. To celebrate, we're giving 1 month of Tracelight Pro for free to anyone who comments LAUNCH below or TAGs a friend who needs this

Peter Fuller

454,065 Aufrufe • vor 7 Monaten

HERMES AGENT SUPPORTS 300+ MODELS. PICKING THE RIGHT ONE PER TASK IS THE DIFFERENCE BETWEEN $5/MONTH AND $50. STARTING OUT: Claude Sonnet 4.6. official recommendation from Nous Research. "the model this project was built and tested with." strong reasoning. reliable tool calling. mid-range pricing. PREMIUM TIER: Claude Opus 4.8. best coding benchmarks available. self-correcting reasoning. catches its own mistakes. 1M context. use for demanding tasks where quality matters. GPT-5.5. #1 Chatbot Arena. #1 GPQA Diamond reasoning (94.1%). #1 creative writing. 2M context. handles entire codebases in one pass. Grok 4.30. the only frontier model with live X firehose access. real-time social data, breaking news, market sentiment. connects via Grok OAuth. no separate API key. Grok-Composer-2.5-Fast (v0.17.0). Cursor's coding model. 200K context. available through your Grok subscription via OAuth. no extra cost if you already pay for Grok. MID-RANGE TIER: Claude Sonnet 4.6. best balance of quality and cost for daily use. strongest prose and tool calling in this tier. Gemini 2.5 Pro. Google Search grounding built in. cites sources. verifies claims. pulls current data. 2M context. best for research-heavy workflows. GPT-4.1. reliable tool calling. solid general reasoning. good middle ground when you need OpenAI compatibility. BUDGET TIER: Claude Haiku 4.5. fastest Anthropic model. cheapest paid Claude option. strong at classification, routing, simple queries. use for auxiliary tasks: compression, vision, web extraction, approval scoring. DeepSeek V4. best cost-to-quality ratio in the market. 90% cache discount on repeated context. use for sub-agents and bulk parallel work. DeepSeek V4 Flash. cheapest paid model worth using. 1M context. MIT license. self-hostable. use for cron jobs, monitoring, routine searches. MiniMax M3. Nous Research and MiniMax collaborating on optimization. 1M context via lightning attention. 59% SWE-Bench Pro. beats several premium models on coding. one of the most-used models inside Hermes. FREE / LOCAL: Qwen 3.5 27B via Ollama. 16GB VRAM. reliable tool calling. best free local model for Hermes as of mid-2026. Qwen 3 8B. 8GB VRAM. fits a $7 VPS. handles routine tasks at zero API cost. Llama 4 Maverick. best open-weight tool calling. 1M context. needs more VRAM but strongest local option. HOW TO ASSIGN MODELS: main model: Desktop app / Dashboard → Models → switch sub-agent model: set in Desktop app, Dashboard, or config.yaml: delegation: model: "deepseek/deepseek-v4" auxiliary models (compression, vision, web extract): Desktop app / Dashboard → Models → Auxiliary Haiku 4.5 or Gemini Flash work well here. saves significantly when your main model is premium. per-profile: each Hermes profile gets its own model. Scout on DeepSeek. Analyst on Sonnet. Briefer on budget model. Coder on Opus. per-cron-job: pin a specific model to any cron job. morning brief on Haiku. deep research on Sonnet. monitoring on DeepSeek Flash. each job uses only the model it needs. per-session: /model deepseek/deepseek-v4-flash hot-swap mid-conversation. no restart needed. FALLBACK CHAINS: if your primary model is unavailable, Hermes automatically switches to the next provider. rate limit or server error = next model in the chain. no failed runs. no manual intervention. set in Desktop app, Dashboard, or config.yaml: fallback_providers: - openrouter - nous - codex PROVIDER PATHS: OPENROUTER: 300+ models under one API key. pay per token. most flexible. NOUS PORTAL: 300+ models + Tool Gateway (web search, image gen, TTS, browser). one OAuth. one subscription. 10% off token-billed providers. CHATGPT SUB: GPT-5.5 + Grok via OAuth. included tokens with $20 subscription. OLLAMA: free. local. private. zero API cost. your hardware only. mix providers across profiles and tasks. Scout on OpenRouter. Analyst on Nous Portal. Coder on ChatGPT sub. Monitor on Ollama. THE RULE: premium for work that needs deep reasoning. mid-range for daily driver tasks. budget for volume and background work. free for monitoring and routine jobs. pricing changes fast. check openrouter ai for current rates before committing. Which is your favourite model and for what task? full 15 levels breakdown in the article 👇

YanXbt

17,138 Aufrufe • vor 2 Monaten

elon musk grabbed the source code openai open-sourced by accident, rewrote it in rust over a weekend, and shipped it as a free coding agent that does everything $200/mo chatgpt pro does. why pay $200 to openai and $200 to claude when this runs for $8 the swarm above is one weekend of exactly that: thousands of agents pouring through four endpoints, three paid seats billing $1.80 a task while the free fork bills $0. musk co-founded openai, walked out, and when they left codex on github under a permissive license, he forked it, stamped grok on it, and gave it away what the free version does that the $200 seat charges for: the agent · openai's own engine -> it reads your repo, writes patches, runs your tests, and loops until they pass, exactly like codex -> because under the hood it is codex, just faster and free. you are paying $200 for the paid skin of a tool now sitting on github the license · apache-2.0, un-revocable -> free to use, free to fork, free to ship inside your own product with zero strings -> openai cannot pull it back. musk made sure the license is the kind that never expires the switch · one line, no new tools -> point it at any openai-compatible or claude-compatible endpoint, including an $8 kimi backend -> same terminal, same workflow, gpt-5.6 and opus 5 just quietly lose the seat the bill · $400 down to $8 -> chatgpt pro plus claude max is $400 a month. the free agent plus an $8 kimi key does the same daily work -> that is a 98% cut, built out of openai's own source code, handed to you by the guy suing them here is the part they will fight me on: openai did not lose this to a better model, they lost it to their own license and an enemy with a weekend free. the $200 was never the tool, it was the toll, and musk just put openai's own logo on the road around it drop your $400/mo ai stack to $8. the run above is openai's own agent, rewritten free, doing the job it bills $200 a month for. the full breakdown is in the article below

starmex

110,709 Aufrufe • vor 8 Tagen

Alibaba just released a coding model that hits 82 percent on SWE-Bench Verified. That is the highest score ever published for an open-source model. The weights are free. The license is Apache 2.0. You can run it today. The model is Qwen 4 Coder 32B. Here is what 82 percent on SWE-Bench Verified actually means. SWE-Bench Verified tests whether an AI can autonomously resolve real bugs pulled from real production GitHub repositories. Not synthetic exercises. Real open-source projects that real teams depend on. A model gets a bug report, reads the code, writes a fix, and either passes the test suite or it does not. At 82 percent, Qwen 4 Coder 32B resolves 82 out of every 100 real production bugs it is given. Without a human guiding it. On code it has never seen before. For comparison: Qwen 4 Coder 32B: 82 percent SWE-Bench Verified. Open source. Apache 2.0. Claude Fable 5: 80.3 percent SWE-Bench Pro. $10 input / $50 output per million tokens. Currently suspended. GPT-5.6 Sol: Competitive on Terminal-Bench. $5 input / $30 output per million tokens. An open-weight model that you can download and run for free just beat both of them on the benchmark designed to measure real software engineering capability. Here is the architecture. Qwen 4 Coder 32B is a 32 billion parameter dense model. Not a Mixture-of-Experts. Every parameter is active on every request. This matters for inference: a dense 32B model runs on 22 gigabytes of VRAM, which fits on a single high-end consumer GPU or a MacBook Pro with 64GB of unified memory. The smaller variant, Qwen 4 Coder 4B, runs at approximately 135 tokens per second on an M5 Max and fits inside 8 gigabytes of RAM. For a model with usable coding capability, that is a new bar for what fits in a single laptop. The training methodology continued Alibaba's approach of reinforcement learning on verifiable coding tasks. The model gets rewarded when its code passes tests. It gets penalized when it fails. Over millions of training steps, the model learns to write code that actually runs rather than code that looks plausible. License: Apache 2.0. Full commercial use. No attribution requirement. No revenue threshold. No monthly active user ceiling. Weights: Hugging Face, available today. Runs on: vLLM, Ollama, SGLang, and any standard GGUF-compatible inference engine. Qwen 4 32B also runs at approximately 135 tokens per second on an M5 Max chip, setting a new bar for what a sub-8GB model can do on Apple Silicon. The open-source coding model just beat the best closed-source model in the world on the benchmark designed to test whether AI can actually do software engineering. The weights are free. The subscription is optional. Source: Autom8Labs AI Insight July 2026, State of Open Source LLMs June 2026, Kunal Ganglani blog June 2026.

Alibaba just released a coding model that hits 82 percent on SWE-Bench Verified. That is the highest score ever published for an open-source model. The weights are free. The license is Apache 2.0. You can run it today. The model is Qwen 4 Coder 32B. Here is what 82 percent on SWE-Bench Verified actually means. SWE-Bench Verified tests whether an AI can autonomously resolve real bugs pulled from real production GitHub repositories. Not synthetic exercises. Real open-source projects that real teams depend on. A model gets a bug report, reads the code, writes a fix, and either passes the test suite or it does not. At 82 percent, Qwen 4 Coder 32B resolves 82 out of every 100 real production bugs it is given. Without a human guiding it. On code it has never seen before. For comparison: Qwen 4 Coder 32B: 82 percent SWE-Bench Verified. Open source. Apache 2.0. Claude Fable 5: 80.3 percent SWE-Bench Pro. $10 input / $50 output per million tokens. Currently suspended. GPT-5.6 Sol: Competitive on Terminal-Bench. $5 input / $30 output per million tokens. An open-weight model that you can download and run for free just beat both of them on the benchmark designed to measure real software engineering capability. Here is the architecture. Qwen 4 Coder 32B is a 32 billion parameter dense model. Not a Mixture-of-Experts. Every parameter is active on every request. This matters for inference: a dense 32B model runs on 22 gigabytes of VRAM, which fits on a single high-end consumer GPU or a MacBook Pro with 64GB of unified memory. The smaller variant, Qwen 4 Coder 4B, runs at approximately 135 tokens per second on an M5 Max and fits inside 8 gigabytes of RAM. For a model with usable coding capability, that is a new bar for what fits in a single laptop. The training methodology continued Alibaba's approach of reinforcement learning on verifiable coding tasks. The model gets rewarded when its code passes tests. It gets penalized when it fails. Over millions of training steps, the model learns to write code that actually runs rather than code that looks plausible. License: Apache 2.0. Full commercial use. No attribution requirement. No revenue threshold. No monthly active user ceiling. Weights: Hugging Face, available today. Runs on: vLLM, Ollama, SGLang, and any standard GGUF-compatible inference engine. Qwen 4 32B also runs at approximately 135 tokens per second on an M5 Max chip, setting a new bar for what a sub-8GB model can do on Apple Silicon. The open-source coding model just beat the best closed-source model in the world on the benchmark designed to test whether AI can actually do software engineering. The weights are free. The subscription is optional. Source: Autom8Labs AI Insight July 2026, State of Open Source LLMs June 2026, Kunal Ganglani blog June 2026.

Harman

41,278 Aufrufe • vor 1 Monat

OpenAI and Anthropic this week: GPT-5.6 price cuts, Claude cracking ciphers, and both backing "Pacing the Frontier" (Week 31, 2026) Starting with OpenAI - GPT-5.6 got a big price cut, with Luna dropping 80% and Terra 20%, plus a new Fast mode for Sol in the API ChatGPT for Academic Researchers opened too, giving free frontier model access to 100,000 scientists On the research side, OpenAI shared ten advances in mathematics and theoretical computer science, all from an internal version of the next model called Astra, plus a study on how AI expands the range of work people do and a field report on scientists using coding agents On the developer side: GPT Transcribe and GPT Live Transcribe, a Terraform provider, an open-source Codex Security CLI, Sign in with ChatGPT in beta, and a desktop app update with browser upgrades, multi-repo review, image editing, and an Activity view GPT-5.4 retires from Codex end of August, the Student Collective opened, and two API settings tripled Sol's ARC-AGI-3 score Plus, I spotted a new "Places" section in ChatGPT Onto Anthropic - Claude Mythos Preview helped find weaknesses in cryptographic algorithms, cutting the effective key strength of the post-quantum scheme HAWK in half and speeding up an attack on reduced-round AES by 200 to 800 times, with no impact on production systems Anthropic released MCP 2026-07-28, the biggest protocol update since launch, moving it to a stateless core with standardized extensions and hardened auth Anthropic disclosed three incidents where Claude reached the internet from inside cybersecurity evaluation environments and accessed real systems of three organizations, traced to a misconfiguration rather than a model alignment failure Dario Amodei laid out Anthropic's position on open-weights models too, saying clearly a ban has never been on the table Both companies backed the "Pacing the Frontier" petition And I spotted Anthropic adding noindex and nofollow to shared Claude conversations

OpenAI and Anthropic this week: GPT-5.6 price cuts, Claude cracking ciphers, and both backing "Pacing the Frontier" (Week 31, 2026) Starting with OpenAI - GPT-5.6 got a big price cut, with Luna dropping 80% and Terra 20%, plus a new Fast mode for Sol in the API ChatGPT for Academic Researchers opened too, giving free frontier model access to 100,000 scientists On the research side, OpenAI shared ten advances in mathematics and theoretical computer science, all from an internal version of the next model called Astra, plus a study on how AI expands the range of work people do and a field report on scientists using coding agents On the developer side: GPT Transcribe and GPT Live Transcribe, a Terraform provider, an open-source Codex Security CLI, Sign in with ChatGPT in beta, and a desktop app update with browser upgrades, multi-repo review, image editing, and an Activity view GPT-5.4 retires from Codex end of August, the Student Collective opened, and two API settings tripled Sol's ARC-AGI-3 score Plus, I spotted a new "Places" section in ChatGPT Onto Anthropic - Claude Mythos Preview helped find weaknesses in cryptographic algorithms, cutting the effective key strength of the post-quantum scheme HAWK in half and speeding up an attack on reduced-round AES by 200 to 800 times, with no impact on production systems Anthropic released MCP 2026-07-28, the biggest protocol update since launch, moving it to a stateless core with standardized extensions and hardened auth Anthropic disclosed three incidents where Claude reached the internet from inside cybersecurity evaluation environments and accessed real systems of three organizations, traced to a misconfiguration rather than a model alignment failure Dario Amodei laid out Anthropic's position on open-weights models too, saying clearly a ban has never been on the table Both companies backed the "Pacing the Frontier" petition And I spotted Anthropic adding noindex and nofollow to shared Claude conversations

Tibor Blaho

11,303 Aufrufe • vor 1 Monat

Introducing Impeccable 3.5, the best way to design in production: iterate on real UI with your AI agent, in the codebase you actually ship. Turns out many popular design skills, including Impeccable and Anthropic's frontend-design, weren't actually very good at...design (the workflow was valuable, but the output didn't magically make LLMs like GPT great designers). We measured it across thousands of generations: 74% of pages used the cream AI-default background, 76% reached for extreme letter-spacing, 90%+ failed the contrast floor. So we started fixing slop systematically, specific to each model. The skill now compiles rules for the exact defects each model makes, instead of shipping one generic file to everyone. The biggest jump is in GPT-5.5 and Codex. Also new: ◆ It now knows the difference between a new project and an existing one. Existing codebase, it reads your design system and preserves your identity. Greenfield, it seeds a fresh palette from 129 hand-curated anchors so every cold start doesn't drift to the same safe colors. ◆ Live Mode is now in beta, and works at two scales. Type a direction into the new Steer bar, or speak it, and the agent reads the whole page and edits it in place. Or pick a single element, steer it with a sub-command, live-edit any copy, and accept the variant straight back to source. Insert mode scaffolds brand-new elements between the ones already there. Recovery survives HMR, hidden heroes, and dev-tool overlays. ◆ A rebuilt anti-pattern detector. Torn off jsdom and onto a real CSS cascade resolver: roughly 20x faster, dependency-free, and now small enough to run inline inside the skill, not just the CLI and extension. 14 new rules, 41 total. ◆ The skill keeps itself current, checking once a day and offering to update. Plus /impeccable init and a bare /impeccable that reads your repo and tells you the next move. Free, open source. Claude Code, Codex, Cursor, and more.

Paul Bakaus

103,249 Aufrufe • vor 3 Monaten

I run my meta ads with OpenClaw🦞 for $0/month 😱 here's the system that runs autonomously: step 1: daily health check → social-cli (major shoutout to Vishal Gopal Ojha) wraps Meta's marketing API (token refresh, pagination, rate limits all handled) → am I on track? what's running? who's winning? who's bleeding? any fatigue? → the same 5 questions I asked Ads Manager every morning for 20 years step 2: catch dying ads before CPA spikes → OpenClaw🦞 pulls daily frequency by ad → frequency > 3.5 = audience is cooked, CTR is about to drop → this one signal saves more money than any dashboard step 3: auto-pause bleeders + shift budget to winners → CPA > 2.5x target for 48hrs? auto-pause. no hesitation. → ranks every campaign by efficiency. recommends shifting spend. → last fri it paused an $87 CPA campaign at 3am and scaled my best performer 30% step 4: write new ad copy from your winners → agent analyzes what's working (hooks, angles, CTAs) → generates variations based on the patterns in YOUR top performers → copy modeled on what already converts in your account. step 5: upload ads directly to your account → new creative + copy → live in Meta Ads Manager → no more downloading, formatting, clicking through the upload flow → agent handles the entire publish cycle step 6: content concepts + morning brief → spots patterns across winners and suggests what to test next → delivers everything to Telegram, Slack, wherever you want it → 90 seconds to read. reply "approved." done. input: your ad account + your target CPA output: an AI that monitors, kills, scales, writes, AND uploads your ads dozens of hours in ad manager → 1 text message I packaged the entire system as the Meta Ads Kit. 5 OpenClaw🦞 skills: - meta-ads (daily checks + auto-pause) - ad-creative-monitor (fatigue detection) - budget-optimizer (efficiency scoring + shift recs) - ad-copy-generator (writes variations from your winners) - ad-upload (publishes creative directly to your account) giving it away free. comment ADS + like + follow (must follow so i can DM)

I run my meta ads with OpenClaw🦞 for $0/month 😱 here's the system that runs autonomously: step 1: daily health check → social-cli (major shoutout to Vishal Gopal Ojha) wraps Meta's marketing API (token refresh, pagination, rate limits all handled) → am I on track? what's running? who's winning? who's bleeding? any fatigue? → the same 5 questions I asked Ads Manager every morning for 20 years step 2: catch dying ads before CPA spikes → OpenClaw🦞 pulls daily frequency by ad → frequency > 3.5 = audience is cooked, CTR is about to drop → this one signal saves more money than any dashboard step 3: auto-pause bleeders + shift budget to winners → CPA > 2.5x target for 48hrs? auto-pause. no hesitation. → ranks every campaign by efficiency. recommends shifting spend. → last fri it paused an $87 CPA campaign at 3am and scaled my best performer 30% step 4: write new ad copy from your winners → agent analyzes what's working (hooks, angles, CTAs) → generates variations based on the patterns in YOUR top performers → copy modeled on what already converts in your account. step 5: upload ads directly to your account → new creative + copy → live in Meta Ads Manager → no more downloading, formatting, clicking through the upload flow → agent handles the entire publish cycle step 6: content concepts + morning brief → spots patterns across winners and suggests what to test next → delivers everything to Telegram, Slack, wherever you want it → 90 seconds to read. reply "approved." done. input: your ad account + your target CPA output: an AI that monitors, kills, scales, writes, AND uploads your ads dozens of hours in ad manager → 1 text message I packaged the entire system as the Meta Ads Kit. 5 OpenClaw🦞 skills: - meta-ads (daily checks + auto-pause) - ad-creative-monitor (fatigue detection) - budget-optimizer (efficiency scoring + shift recs) - ad-copy-generator (writes variations from your winners) - ad-upload (publishes creative directly to your account) giving it away free. comment ADS + like + follow (must follow so i can DM)

Matthew Berman

640,424 Aufrufe • vor 6 Monaten

Today at Yoast we’re shipping something I've actually wanted to see on the web for some time (even before working at Yoast) and am now honored to be part of the team to bring this to the masses... Built in collaboration with the Open Source and NLWeb team at Microsoft lead by R.V.Guha (co-creator of RSS, RDF and other web standards) - we're introducing the Schema Aggregation feature: a "schemamap" endpoint that outputs your site's entire structured data map in one place. Under the hood, we now provide a standardised, deduplicated map of your entities via a single endpoint. An agent no longer needs to crawl all individual pages to understand its meaning but can now ingest an entire entity map with ease. A few details to note about the endpoint: - It's is cacheable with sub‑100ms responses - It respects existing privacy and indexing settings - It aggregates all indexable content without navigation noise - It merges duplicate entities so your "Author X" or "Article Y" exist as a single node instead of being re‑discovered on every URL. - If you're using one of our paid plugins that extends schema even more (such as Yoast WooCommerce SEO adds product schema) this will be populated within the endpoint too - If you already extend Yoast’s Schema API, or use partners like events or recipe plugins, their entities are pulled into the same map automatically. For me, this is one of the first major ways the agentic web can ingest a site at scale, and with much more efficiency and context. It has also been so much fun to work with this alongside the team at Yoast, particularly the genius mind of Alain Schlesser. Lastly, we have also launched a schema visualisation tool to view how everything is output. You can enable this feature today with the free version of Yoast SEO.

Today at Yoast we’re shipping something I've actually wanted to see on the web for some time (even before working at Yoast) and am now honored to be part of the team to bring this to the masses... Built in collaboration with the Open Source and NLWeb team at Microsoft lead by R.V.Guha (co-creator of RSS, RDF and other web standards) - we're introducing the Schema Aggregation feature: a "schemamap" endpoint that outputs your site's entire structured data map in one place. Under the hood, we now provide a standardised, deduplicated map of your entities via a single endpoint. An agent no longer needs to crawl all individual pages to understand its meaning but can now ingest an entire entity map with ease. A few details to note about the endpoint: - It's is cacheable with sub‑100ms responses - It respects existing privacy and indexing settings - It aggregates all indexable content without navigation noise - It merges duplicate entities so your "Author X" or "Article Y" exist as a single node instead of being re‑discovered on every URL. - If you're using one of our paid plugins that extends schema even more (such as Yoast WooCommerce SEO adds product schema) this will be populated within the endpoint too - If you already extend Yoast’s Schema API, or use partners like events or recipe plugins, their entities are pulled into the same map automatically. For me, this is one of the first major ways the agentic web can ingest a site at scale, and with much more efficiency and context. It has also been so much fun to work with this alongside the team at Yoast, particularly the genius mind of Alain Schlesser. Lastly, we have also launched a schema visualisation tool to view how everything is output. You can enable this feature today with the free version of Yoast SEO.

Alex Moss

15,372 Aufrufe • vor 6 Monaten

I pay Claude $20 a month. Most $TAO holders do too. There is a stack you can build in 15 minutes that fixes that completely. It runs on Bittensor. It costs $10. You do not write a single line of code. Here is how every AI chat product actually works under the hood. Three layers. Always three. The model. The brain. GPT, Claude, DeepSeek, Kimi, GLM. The inference layer. The GPU that runs the model when you hit send. The interface. The chat box you actually look at. ChatGPT and Claude bundle all three and hand you the result. You cannot change the model. You cannot change the inference. The interface is non-negotiable. Every prompt you type goes to a server run by a private company whose terms of service can quietly change next month. The anti-ChatGPT move is to pick each layer yourself. This is where $TAO comes in. Chutes is Subnet 64 on Bittensor. It is the inference layer. Open source models like DeepSeek, Kimi, GLM, and Llama get served by a global network of miner-operated GPUs. Validators score the output quality. The best inference wins the emissions. You hit send. A miner somewhere runs your prompt. You get the answer back. The TAO you hold is in part paying for the GPU you just used. The basic stack is one URL. chutes. ai/chat No account. No API key. No setup. Switch models mid-conversation. Web search built in. Image generation. File uploads. Free. The advanced stack is Chutes plus TypingMind. One-time license. No recurring fee. Plugins, agents, custom personas, a prompt library you build over months. Full model switching between Chutes, OpenAI, and Anthropic from the same window. Total cost: $10 a month to Chutes for inference. That $10 buys you $50 in actual usage. But here is the signal most people missed inside this story. Chutes ran a free tier until February. Then they killed it. Then they raised the minimum to $10 in May. Most people saw that as bad news. It is the opposite. Free things on the internet do not last. Real products do. Chutes is becoming a real product. A subnet that generates actual revenue from actual users paying actual money for actual AI inference. That is what $43 million in Q1 network revenue looks like at the individual subnet level. And there is one more thing ChatGPT and Claude cannot offer that Chutes already has. Trusted Execution Environments. Your prompt gets encrypted on your device, shipped to a confidential compute GPU, and the lock only breaks inside the chip. The miner running the model physically cannot read your prompt. ChatGPT cannot promise that. Claude cannot promise that. Bittensor already built it. You are holding a network where the subnets are generating real revenue, shipping real privacy infrastructure, and replacing $20 a month centralised subscriptions with $10 a month decentralised inference. The people who use the product always understand the investment better than the people who only watch the price.

I pay Claude $20 a month. Most $TAO holders do too. There is a stack you can build in 15 minutes that fixes that completely. It runs on Bittensor. It costs $10. You do not write a single line of code. Here is how every AI chat product actually works under the hood. Three layers. Always three. The model. The brain. GPT, Claude, DeepSeek, Kimi, GLM. The inference layer. The GPU that runs the model when you hit send. The interface. The chat box you actually look at. ChatGPT and Claude bundle all three and hand you the result. You cannot change the model. You cannot change the inference. The interface is non-negotiable. Every prompt you type goes to a server run by a private company whose terms of service can quietly change next month. The anti-ChatGPT move is to pick each layer yourself. This is where $TAO comes in. Chutes is Subnet 64 on Bittensor. It is the inference layer. Open source models like DeepSeek, Kimi, GLM, and Llama get served by a global network of miner-operated GPUs. Validators score the output quality. The best inference wins the emissions. You hit send. A miner somewhere runs your prompt. You get the answer back. The TAO you hold is in part paying for the GPU you just used. The basic stack is one URL. chutes. ai/chat No account. No API key. No setup. Switch models mid-conversation. Web search built in. Image generation. File uploads. Free. The advanced stack is Chutes plus TypingMind. One-time license. No recurring fee. Plugins, agents, custom personas, a prompt library you build over months. Full model switching between Chutes, OpenAI, and Anthropic from the same window. Total cost: $10 a month to Chutes for inference. That $10 buys you $50 in actual usage. But here is the signal most people missed inside this story. Chutes ran a free tier until February. Then they killed it. Then they raised the minimum to $10 in May. Most people saw that as bad news. It is the opposite. Free things on the internet do not last. Real products do. Chutes is becoming a real product. A subnet that generates actual revenue from actual users paying actual money for actual AI inference. That is what $43 million in Q1 network revenue looks like at the individual subnet level. And there is one more thing ChatGPT and Claude cannot offer that Chutes already has. Trusted Execution Environments. Your prompt gets encrypted on your device, shipped to a confidential compute GPU, and the lock only breaks inside the chip. The miner running the model physically cannot read your prompt. ChatGPT cannot promise that. Claude cannot promise that. Bittensor already built it. You are holding a network where the subnets are generating real revenue, shipping real privacy infrastructure, and replacing $20 a month centralised subscriptions with $10 a month decentralised inference. The people who use the product always understand the investment better than the people who only watch the price.

2xnmore

27,088 Aufrufe • vor 3 Monaten