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MAY THE 4TH BE WITH YOUR AGENTS... starting today, TinyFish's `Web Search` and `Fetch` are FREE 🤯 Hand-rolling Playwright scripts and watching messy DOMs explode your context limits used to feel like battling the Dark Side. Today, TinyFish brings balance to the Force. Their Search and Fetch layer is...

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Charly Wargnier

169,696 subscribers

12,844 次观看 • 4 个月前 •via X (Twitter)

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TinyFish just made web search + fetch FREE for every AI agent. No credit card. No hacks. Just plug and go. Works everywhere I actually build: • REST API • MCP (Claude, Cursor, Codex) • Python + TS SDKs • Claude Code + OpenClaw skills • LangChain / CrewAI And the best part? Full-browser fetch → clean markdown/JSON = no junk HTML = lower token costs = faster agents This is what agent stacks were missing. Try it:
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TinyFish just made web search + fetch FREE for every AI agent. No credit card. No hacks. Just plug and go. Works everywhere I actually build: • REST API • MCP (Claude, Cursor, Codex) • Python + TS SDKs • Claude Code + OpenClaw skills • LangChain / CrewAI And the best part? Full-browser fetch → clean markdown/JSON = no junk HTML = lower token costs = faster agents This is what agent stacks were missing. Try it:

Shruti Codes

19,860 次观看 • 4 个月前

Here is an open-source tool to generate a complete dataset. 1. Describe the data you want 2. An orchestrator agent searches the web 3. Sub-agents run in parallel to fetch the data 4. You get a structured dataset you can download For example, you can run Bigset with the query "all leica lenses being sold on amazon", or "leica stores in kyoto with their opening hours and ratings". Bigset uses TinyFish's free Search and Fetch APIs in the background. You can configure it to refresh the data on a schedule. You can self-host it with your own keys. Here is the GitHub repository: You can get free TinyFish API keys here: Thanks to the TinyFish team for partnering with me on this post.
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Here is an open-source tool to generate a complete dataset. 1. Describe the data you want 2. An orchestrator agent searches the web 3. Sub-agents run in parallel to fetch the data 4. You get a structured dataset you can download For example, you can run Bigset with the query "all leica lenses being sold on amazon", or "leica stores in kyoto with their opening hours and ratings". Bigset uses TinyFish's free Search and Fetch APIs in the background. You can configure it to refresh the data on a schedule. You can self-host it with your own keys. Here is the GitHub repository: You can get free TinyFish API keys here: Thanks to the TinyFish team for partnering with me on this post.

Santiago

20,877 次观看 • 3 个月前

OptimAI Search MCP brings live context to the agents people already use. Claude. Cursor. Copilot. Codex. One integration layer. Everywhere you build. Under the hood, OptimAI can process hundreds to thousands of real-time signals in parallel across the public web, social platforms, and onchain data - all powered by a decentralized network. That is the difference: not another search tool, but infrastructure for agent-native intelligence. Build with it. 💡 -- OptimAI: the #1 AI on BNB Chain DappBay.
1:27

OptimAI Search MCP brings live context to the agents people already use. Claude. Cursor. Copilot. Codex. One integration layer. Everywhere you build. Under the hood, OptimAI can process hundreds to thousands of real-time signals in parallel across the public web, social platforms, and onchain data - all powered by a decentralized network. That is the difference: not another search tool, but infrastructure for agent-native intelligence. Build with it. 💡 -- OptimAI: the #1 AI on BNB Chain DappBay.

OptimAI Network

58,440 次观看 • 2 个月前

How to use 50+ API keys (models) for FREE on OpenClaw API??? - go to - login or register your account - click on "more models" - click on "use case" and select what you need it for - choose the model and open it - click on "view code" → "Generate API key" many models don't allow direct deploy, so use the "view code" button to generate API access basically Nvidia NIM gives you the ability to test almost any model from their list for FREE some of them are not worse than GPT 5.2 or Claude Opus 4.6, some might even perform better depending on the task how to understand if a model is efficient and compare it with others??? - go to - type the model name in search - click on "benchmarks" - you’ll see performance tests and rankings this way you can easily compare free models with paid ones of course there are RPM limits, on many models it’s around ~40 requests per minute each model is different, after generating the API key, RPM limits are shown in the top-right corner nothing stops you from using them, many work perfectly fine, super solid option for first tests and for learning OpenClaw or any other system where you need an AI API model
1:54

How to use 50+ API keys (models) for FREE on OpenClaw API??? - go to - login or register your account - click on "more models" - click on "use case" and select what you need it for - choose the model and open it - click on "view code" → "Generate API key" many models don't allow direct deploy, so use the "view code" button to generate API access basically Nvidia NIM gives you the ability to test almost any model from their list for FREE some of them are not worse than GPT 5.2 or Claude Opus 4.6, some might even perform better depending on the task how to understand if a model is efficient and compare it with others??? - go to - type the model name in search - click on "benchmarks" - you’ll see performance tests and rankings this way you can easily compare free models with paid ones of course there are RPM limits, on many models it’s around ~40 requests per minute each model is different, after generating the API key, RPM limits are shown in the top-right corner nothing stops you from using them, many work perfectly fine, super solid option for first tests and for learning OpenClaw or any other system where you need an AI API model

Ronin

58,974 次观看 • 6 个月前

FREE GPT 5.5 API from a Chinese provider. I already farmed $520 in credits. Plug it directly into Hermes Agent or OpenClaw. > This is a Chinese proxy for OpenAI's official API - same models, same token pricing, same caching. GPT 5.5, Codex, the full stack. I found a way to farm credits through a Telegram bot and it still works. Here's the exact flow: → Go to on Telegram → subscribe to the channel → Join and complete the captcha (use the app, tap the first button) → Go back to the bot, grab your referral link → Invite 1 friend → you get an invite code → Register at with the invite code → Farm points: daily spins (+1-10 pts), each referral (+1/4 pt) → Redeem points for credits: $10 API = 1pt, $100 API = 5pts, $1000 API = 50pts → Create API key → select Codex/another GPT model → plug into Hermes Agent or OpenClaw Ready-made configs for Claude Code and OpenCode are in the "Use Key" section under API Keys. > I have $520 balance. Prices match official OpenAI rates. Caching works. Everything tested. // You can also use these points to buy a ChatGPT account or a subscription for your account. But they get blocked pretty quickly. USE THE API. // Nobody knows how long this lasts. Coupons have been restocked twice already. Move now.
0:34

FREE GPT 5.5 API from a Chinese provider. I already farmed $520 in credits. Plug it directly into Hermes Agent or OpenClaw. > This is a Chinese proxy for OpenAI's official API - same models, same token pricing, same caching. GPT 5.5, Codex, the full stack. I found a way to farm credits through a Telegram bot and it still works. Here's the exact flow: → Go to on Telegram → subscribe to the channel → Join and complete the captcha (use the app, tap the first button) → Go back to the bot, grab your referral link → Invite 1 friend → you get an invite code → Register at with the invite code → Farm points: daily spins (+1-10 pts), each referral (+1/4 pt) → Redeem points for credits: $10 API = 1pt, $100 API = 5pts, $1000 API = 50pts → Create API key → select Codex/another GPT model → plug into Hermes Agent or OpenClaw Ready-made configs for Claude Code and OpenCode are in the "Use Key" section under API Keys. > I have $520 balance. Prices match official OpenAI rates. Caching works. Everything tested. // You can also use these points to buy a ChatGPT account or a subscription for your account. But they get blocked pretty quickly. USE THE API. // Nobody knows how long this lasts. Coupons have been restocked twice already. Move now.

Atenov int.

65,251 次观看 • 3 个月前

We're looking for founders building agentic apps. • This is the TinyFish Accelerator. • 9 weeks. • $2M seed pool. We want you to build agents that navigate real web interfaces and execute real transactions. We don't want wrappers. We want agents from the ground up. To apply, you need a working app + record a demo, and publish it on X. We have 15+ partner companies across the full stack: Google for Startups, v0 by Vercel, ElevenLabs, Fireworks, MongoDB, Composio, AgentOps, Dify, and more. They all will provide credits, API keys, and direct engineering support to every founder in the cohort. What you get: • Free TinyFish API keys • Engineering support and product feedback from the team • Free credits + direct engineering access from partner companies • Weekly business mentorship sessions with founders and leaders • Off-the-record community meetups • Pitch directly to Robin Vasan (Mango Capital) The applications are open starting today. Rolling admissions through March 29. Apply →
1:32

We're looking for founders building agentic apps. • This is the TinyFish Accelerator. • 9 weeks. • $2M seed pool. We want you to build agents that navigate real web interfaces and execute real transactions. We don't want wrappers. We want agents from the ground up. To apply, you need a working app + record a demo, and publish it on X. We have 15+ partner companies across the full stack: Google for Startups, v0 by Vercel, ElevenLabs, Fireworks, MongoDB, Composio, AgentOps, Dify, and more. They all will provide credits, API keys, and direct engineering support to every founder in the cohort. What you get: • Free TinyFish API keys • Engineering support and product feedback from the team • Free credits + direct engineering access from partner companies • Weekly business mentorship sessions with founders and leaders • Off-the-record community meetups • Pitch directly to Robin Vasan (Mango Capital) The applications are open starting today. Rolling admissions through March 29. Apply →

Santiago

57,592 次观看 • 6 个月前

Start building for an agent-first world. If you have a product, you need to start offering skills for Claude, Codex, Cursor, and any other agents. Your skills should specify: • How to navigate and use your product • Best practices the agent must follow • Detailed instructions on how to accomplish things • Anti-patterns to avoid Redis is one of the most popular in-memory data stores in the world, and they just released their agent skills. It takes one second to install, and it will turn your agent into a Senior Redis Engineer: $ npx skills add redis/agent-skills In the attached video, I show you how to install it as a plugin in Claude Code and some of its benefits. This is the easiest way to "teach" models what they don't know and keep their knowledge up to date. If you ask me, skills is literally one of the most brilliant ideas that Anthropic has put out there. If you use Redis, their skill is a must-have. If you don't, this skill will show you how to build and structure yours. Here is what their skill teaches your agent: 1. Current patterns for common use cases: caching, rate limiting, session management, vector search, semantic caching, pub/sub, streams. 2. Which data structure to use and when: hashes vs. JSON vs. sorted sets vs. vector sets. 3. Anti-patterns to avoid: no KEYS in loops, no unbounded key growth, no large values that amplify every operation. 4. Production-aware defaults: connection pooling, pipelining, cluster compatibility, error handling that doesn't silently swallow failures.
4:44

Start building for an agent-first world. If you have a product, you need to start offering skills for Claude, Codex, Cursor, and any other agents. Your skills should specify: • How to navigate and use your product • Best practices the agent must follow • Detailed instructions on how to accomplish things • Anti-patterns to avoid Redis is one of the most popular in-memory data stores in the world, and they just released their agent skills. It takes one second to install, and it will turn your agent into a Senior Redis Engineer: $ npx skills add redis/agent-skills In the attached video, I show you how to install it as a plugin in Claude Code and some of its benefits. This is the easiest way to "teach" models what they don't know and keep their knowledge up to date. If you ask me, skills is literally one of the most brilliant ideas that Anthropic has put out there. If you use Redis, their skill is a must-have. If you don't, this skill will show you how to build and structure yours. Here is what their skill teaches your agent: 1. Current patterns for common use cases: caching, rate limiting, session management, vector search, semantic caching, pub/sub, streams. 2. Which data structure to use and when: hashes vs. JSON vs. sorted sets vs. vector sets. 3. Anti-patterns to avoid: no KEYS in loops, no unbounded key growth, no large values that amplify every operation. 4. Production-aware defaults: connection pooling, pipelining, cluster compatibility, error handling that doesn't silently swallow failures.

Santiago

37,546 次观看 • 6 个月前

Today we're launching Amplitude MCP MCP was made for data analytics. Ask a vague question and have an AI model iteratively query Amplitude to find you insights. Amplitude MCP exposes all of Amplitude's functionality so an agent can interact with it directly. It allows you to use Amplitude without having to know anything about Amplitude's user interface or your data taxonomy. It uses the intelligence of off the shelf AI agents, including Claude, Gemini, and Cursor, to query Amplitude data you already have to find answers. It leverages all of your existing Amplitude data and how it's used to navigate through large complex behavioral datasets. You can have conversations about your product data directly inside any AI model with MCP. It can create Amplitude dashboards and notebooks with what it finds and even make recommendations. This is the best MCP use case I've ever seen. Watching an AI agent think, reason, query Amplitude, and then repeat that process iteratively is magical. See it in action:
3:08

Today we're launching Amplitude MCP MCP was made for data analytics. Ask a vague question and have an AI model iteratively query Amplitude to find you insights. Amplitude MCP exposes all of Amplitude's functionality so an agent can interact with it directly. It allows you to use Amplitude without having to know anything about Amplitude's user interface or your data taxonomy. It uses the intelligence of off the shelf AI agents, including Claude, Gemini, and Cursor, to query Amplitude data you already have to find answers. It leverages all of your existing Amplitude data and how it's used to navigate through large complex behavioral datasets. You can have conversations about your product data directly inside any AI model with MCP. It can create Amplitude dashboards and notebooks with what it finds and even make recommendations. This is the best MCP use case I've ever seen. Watching an AI agent think, reason, query Amplitude, and then repeat that process iteratively is magical. See it in action:

Spenser Skates

32,332 次观看 • 10 个月前

There's probably $100+ billion up for grabs for people who build startup for AI agents Over the next 10 years you're going to have a market of billions of customers (agents) with millions of wallets that want to use your services. TLDR; The internet was built for people: 1. Search google 2. Read landing page 3. Book demo 4. Talk to sales 5. Buy Agents don’t do that. Agents will: 1. Ask which product to use 2. Read your docs/pricing/security pages 3. Compare you to competitors 4. Check if you have an MCP/API/tool layer 5. Buy or recommend you without ever “visiting” your site like a person Everyone is going to have personal agents and business agents. This feels inevitable at this point. OpenClaw, Hermes, Claude Code, Codex, Google Spark. The tools are here. Which means there will be more agents on the internet than humans. So, where's the opportunity?? Go look at every SaaS tool you use. Notion. Slack. Jira. Google Analytics. Now ask: what is the version of this built purely for agents? Agent-native payments. Agent-native communication. Agent-native memory. Every category gets rebuilt. I clearly break down this shift and explain you everything on today's ep of The Startup Ideas Podcast (SIP) 🧃. Over the next 10 years you're going to have a market of billions of customers (agents) with millions of wallets that want to use your services. The founders who build for them now are going to look like the people who built websites in 1995. Might feel janky at the moment, but also obvious in hindsight. This is the next shift. Link over here: Watch
13:59

There's probably $100+ billion up for grabs for people who build startup for AI agents Over the next 10 years you're going to have a market of billions of customers (agents) with millions of wallets that want to use your services. TLDR; The internet was built for people: 1. Search google 2. Read landing page 3. Book demo 4. Talk to sales 5. Buy Agents don’t do that. Agents will: 1. Ask which product to use 2. Read your docs/pricing/security pages 3. Compare you to competitors 4. Check if you have an MCP/API/tool layer 5. Buy or recommend you without ever “visiting” your site like a person Everyone is going to have personal agents and business agents. This feels inevitable at this point. OpenClaw, Hermes, Claude Code, Codex, Google Spark. The tools are here. Which means there will be more agents on the internet than humans. So, where's the opportunity?? Go look at every SaaS tool you use. Notion. Slack. Jira. Google Analytics. Now ask: what is the version of this built purely for agents? Agent-native payments. Agent-native communication. Agent-native memory. Every category gets rebuilt. I clearly break down this shift and explain you everything on today's ep of The Startup Ideas Podcast (SIP) 🧃. Over the next 10 years you're going to have a market of billions of customers (agents) with millions of wallets that want to use your services. The founders who build for them now are going to look like the people who built websites in 1995. Might feel janky at the moment, but also obvious in hindsight. This is the next shift. Link over here: Watch

GREG ISENBERG

55,882 次观看 • 3 个月前

If you use Cursor for coding, Claude Code for debugging, and local agents for automation, you almost certainly have a context problem. Every tool acts like an isolated employee. One assistant forgets what the other just learned. The biggest bottleneck in multi-agent workflows right now isn’t reasoning. It’s collective amnesia, combined with zero communication between agents. Memmy just launched a smart fix for this: a local, cross-agent memory layer. Instead of re-pasting your context everywhere, Memmy gives your stack a shared memory hub: → accumulate knowledge once, then use it across Cursor, Codex, and OpenClaw → automatically scan and import your existing agent history, so you don’t have to start from zero → keep your memory local, while model usage depends on your chosen provider or BYOK setup And it isn’t just a memory plugin. It’s a complete personal AI runtime with both MCP and a CLI. Memmy officially launched on Product Hunt, and the team is giving early users experiencing context fragmentation a free trial with 2M GPT tokens. Check it out and support the team with an upvote: → Best part? It’s also open-source for devs who want to build their own agents 🔥 Repo in 🧵↓
3:29

If you use Cursor for coding, Claude Code for debugging, and local agents for automation, you almost certainly have a context problem. Every tool acts like an isolated employee. One assistant forgets what the other just learned. The biggest bottleneck in multi-agent workflows right now isn’t reasoning. It’s collective amnesia, combined with zero communication between agents. Memmy just launched a smart fix for this: a local, cross-agent memory layer. Instead of re-pasting your context everywhere, Memmy gives your stack a shared memory hub: → accumulate knowledge once, then use it across Cursor, Codex, and OpenClaw → automatically scan and import your existing agent history, so you don’t have to start from zero → keep your memory local, while model usage depends on your chosen provider or BYOK setup And it isn’t just a memory plugin. It’s a complete personal AI runtime with both MCP and a CLI. Memmy officially launched on Product Hunt, and the team is giving early users experiencing context fragmentation a free trial with 2M GPT tokens. Check it out and support the team with an upvote: → Best part? It’s also open-source for devs who want to build their own agents 🔥 Repo in 🧵↓

Charly Wargnier

203,456 次观看 • 1 个月前

I made the worlds best Clipboard for your AI Agents Its called Bluey and its a dumb pointer which you can use to give 10x better context to your agent And you can point at your screen, talk to it, and it will generate a really good annotated screenshot which you can now give to your AI Agent You can use it while designing your website You can use it while explaining something on your screen. And it understands you and you can be really vague about things like "move this" , modify the color "here" and it will understand what you are pointing at. Im loving using it and I built it for myself as I was tired of clicking screenshots all the time and attaching it to my codex or claude code sessions Now I can just point, speak or type and drag and drop it anywhere I am giving free access to it in the comments and I would love for you to try it out. Join the discord and I am sharing the download link there. By the way everything stays 100 percent local. No screenshots are shared anywhere!
2:59

I made the worlds best Clipboard for your AI Agents Its called Bluey and its a dumb pointer which you can use to give 10x better context to your agent And you can point at your screen, talk to it, and it will generate a really good annotated screenshot which you can now give to your AI Agent You can use it while designing your website You can use it while explaining something on your screen. And it understands you and you can be really vague about things like "move this" , modify the color "here" and it will understand what you are pointing at. Im loving using it and I built it for myself as I was tired of clicking screenshots all the time and attaching it to my codex or claude code sessions Now I can just point, speak or type and drag and drop it anywhere I am giving free access to it in the comments and I would love for you to try it out. Join the discord and I am sharing the download link there. By the way everything stays 100 percent local. No screenshots are shared anywhere!

Milind S

12,085 次观看 • 3 个月前

There's no way this is free. Anthropic just put 20+ courses on using AI for $0 These are the official Anthropic courses for learning Claude and Claude Code. 20 courses that take you from zero to building real, complex things. Link: You'll find everything there: from AI basics, to advanced skills like building with MCP, the API, AWS, agents, and a lot more. And it's not just lectures. There are hands-on lessons where you practice what you learned. After each one, you get a certificate you can add to your LinkedIn, the kind that sets you apart from people who don't have it. Now you've got no excuse left for not knowing how to use AI. Bookmark this
1:21

There's no way this is free. Anthropic just put 20+ courses on using AI for $0 These are the official Anthropic courses for learning Claude and Claude Code. 20 courses that take you from zero to building real, complex things. Link: You'll find everything there: from AI basics, to advanced skills like building with MCP, the API, AWS, agents, and a lot more. And it's not just lectures. There are hands-on lessons where you practice what you learned. After each one, you get a certificate you can add to your LinkedIn, the kind that sets you apart from people who don't have it. Now you've got no excuse left for not knowing how to use AI. Bookmark this

Yarchi

15,915 次观看 • 1 个月前

I can search a database with 32 million records in less than 50 milliseconds. ​ This speed is insane! ​ There's no reason your search is slow. There's no reason you aren't using this library when building applications with a lot of data. ​ Take a look at typesense |. It's an open-source search engine. It's crazy fast and easy to use. They are sponsoring this post. ​ Here is their GitHub repository: ​ ​ You can use the library in Python, JavaScript, PHP, Ruby, Swift, and pretty much any other programming language out there. ​ Here are some of the things you can do with Typesense: ​ • Vector search over embeddings • Conversational search for RAG applications • Image similarity search • Voice search ​ And it does all of this extremely fast. ​ A few interesting notes about the library: ​ • Optimized for developer happiness • Works out of the box for most use cases • Very intuitive API • Easy to deploy and scale ​ Probably the best way to compare them is against ElasticSearch. The latter is much more complex to configure and run with a steep learning curve. ​ Check their GitHub repository. They have examples, tutorials, and everything you need.
1:18

I can search a database with 32 million records in less than 50 milliseconds. ​ This speed is insane! ​ There's no reason your search is slow. There's no reason you aren't using this library when building applications with a lot of data. ​ Take a look at typesense |. It's an open-source search engine. It's crazy fast and easy to use. They are sponsoring this post. ​ Here is their GitHub repository: ​ ​ You can use the library in Python, JavaScript, PHP, Ruby, Swift, and pretty much any other programming language out there. ​ Here are some of the things you can do with Typesense: ​ • Vector search over embeddings • Conversational search for RAG applications • Image similarity search • Voice search ​ And it does all of this extremely fast. ​ A few interesting notes about the library: ​ • Optimized for developer happiness • Works out of the box for most use cases • Very intuitive API • Easy to deploy and scale ​ Probably the best way to compare them is against ElasticSearch. The latter is much more complex to configure and run with a steep learning curve. ​ Check their GitHub repository. They have examples, tutorials, and everything you need.

Santiago

160,154 次观看 • 2 年前

AgentRouter is handing out $125 in FREE API credits for OPUS 4.8 > No card. > GitHub sign-in. > One API key for Opus 4.8 / Opus 4.7 / Sonnet 4.6 / GLM 5.1 The useful part is not “another model gateway.” It is that you can point coding tools and agents at one OpenAI-compatible base URL instead of juggling separate keys for Claude and GLM, and others. What you get: • $125 signup balance • one API key • OpenAI-compatible endpoints • chat, responses, messages, embeddings, images, audio, rerank endpoints listed • claimed support for Cursor, Claude Code, Hermes, and other agent tools The flow is simple: 1. go to AgentRouter (link in comment) 2. sign in or create an account 3. generate an API key in the console 4. copy the base URL 5. paste it into Cursor / Claude Code / your agent runtime 6. run a small test before moving anything serious Caveat: AgentRouter’s own site currently has a notice saying Claude-series service was recently hit by stability issues and large-scale Claude access was suspended. So don’t treat this as “guaranteed free Claude forever.” Treat it as $125 of free routing credits to test which models are live, how the latency feels, and whether the gateway is stable enough for your workflow. Still a very solid save if you build with agents. Most people burn paid API credits just testing configs. This gives you room to test first, then decide if it belongs in your stack.
0:22

AgentRouter is handing out $125 in FREE API credits for OPUS 4.8 > No card. > GitHub sign-in. > One API key for Opus 4.8 / Opus 4.7 / Sonnet 4.6 / GLM 5.1 The useful part is not “another model gateway.” It is that you can point coding tools and agents at one OpenAI-compatible base URL instead of juggling separate keys for Claude and GLM, and others. What you get: • $125 signup balance • one API key • OpenAI-compatible endpoints • chat, responses, messages, embeddings, images, audio, rerank endpoints listed • claimed support for Cursor, Claude Code, Hermes, and other agent tools The flow is simple: 1. go to AgentRouter (link in comment) 2. sign in or create an account 3. generate an API key in the console 4. copy the base URL 5. paste it into Cursor / Claude Code / your agent runtime 6. run a small test before moving anything serious Caveat: AgentRouter’s own site currently has a notice saying Claude-series service was recently hit by stability issues and large-scale Claude access was suspended. So don’t treat this as “guaranteed free Claude forever.” Treat it as $125 of free routing credits to test which models are live, how the latency feels, and whether the gateway is stable enough for your workflow. Still a very solid save if you build with agents. Most people burn paid API credits just testing configs. This gives you room to test first, then decide if it belongs in your stack.

kocer

25,316 次观看 • 2 个月前

The most comprehensive Hermes Desktop tutorial on the internet NOW is LIVE. You'll learn sessions, profiles, artifacts, cost savings, and real use cases for making money and building startups with Hermes agents. Whether you're already running Hermes or haven't started yet, this is the episode for you. Alex Finn says this is the moment Hermes overtakes OpenClaw. S/o to Alex for walking me through it. "It's now the best way to use AI agents on your computer" I do think the desktop app of Hermes looks almost like an Apple product. Everything you need to know about Hermes Desktop App/agents in 43 minutes This episode is 100% free. No ads. The Startup Ideas Podcast (SIP) 🧃 I just want to see you win on the internet. And I think Hermes can help. Plus, It's fun thing to play with this weekend. Share this with a friend. Link below. YT: Watch
43:48

The most comprehensive Hermes Desktop tutorial on the internet NOW is LIVE. You'll learn sessions, profiles, artifacts, cost savings, and real use cases for making money and building startups with Hermes agents. Whether you're already running Hermes or haven't started yet, this is the episode for you. Alex Finn says this is the moment Hermes overtakes OpenClaw. S/o to Alex for walking me through it. "It's now the best way to use AI agents on your computer" I do think the desktop app of Hermes looks almost like an Apple product. Everything you need to know about Hermes Desktop App/agents in 43 minutes This episode is 100% free. No ads. The Startup Ideas Podcast (SIP) 🧃 I just want to see you win on the internet. And I think Hermes can help. Plus, It's fun thing to play with this weekend. Share this with a friend. Link below. YT: Watch

GREG ISENBERG

225,322 次观看 • 3 个月前

do you understand what just shipped? → AI agents can now design directly on Figma’s canvas. not cheesy mockups… or lame screenshots… real native Figma assets wired to your actual design system → the use_figma MCP tool lets Claude Code, Codex, Cursor, and 6 other coding agents write directly to your Figma files → agents read your component library first and build with what already exists… variables, tokens, auto layout, the works → skills let you teach agents HOW your team designs. a skill is just a markdown file… anyone who understands Figma can write one → also works with Copilot CLI, Copilot in VS Code, Factory, Firebender, Augment, and Warp → free during beta… usage based pricing coming later the design to code gap that’s haunted every product team just collapsed in front of our eyes. designers hand off to agents now no need to wait on developers anymore everyone can take a deep breath now if you’re building products and not connecting Figma to your agents yet, you’re leaving serious speed on the table. set this up today. you’ll thank me later
0:23

do you understand what just shipped? → AI agents can now design directly on Figma’s canvas. not cheesy mockups… or lame screenshots… real native Figma assets wired to your actual design system → the use_figma MCP tool lets Claude Code, Codex, Cursor, and 6 other coding agents write directly to your Figma files → agents read your component library first and build with what already exists… variables, tokens, auto layout, the works → skills let you teach agents HOW your team designs. a skill is just a markdown file… anyone who understands Figma can write one → also works with Copilot CLI, Copilot in VS Code, Factory, Firebender, Augment, and Warp → free during beta… usage based pricing coming later the design to code gap that’s haunted every product team just collapsed in front of our eyes. designers hand off to agents now no need to wait on developers anymore everyone can take a deep breath now if you’re building products and not connecting Figma to your agents yet, you’re leaving serious speed on the table. set this up today. you’ll thank me later

klöss

101,073 次观看 • 5 个月前

how to use firecrawl to give your AI eyes and actually build startups that outperform 99% of apps: 1. your AI is smart but blind. it can't go to a website, read a page, or grab data on its own. firecrawl fixes that. you put in a URL. you get back clean markdown, structured JSON, screenshots. feed it to any model. 2. three lines of code. that's it. no proxies. no anti-bot detection. no custom scrapers that break when a site changes. one API call. clean data back in seconds. works on 98%+ of sites. 3. firecrawl has six core capabilities: scrape a single page. crawl an entire site. map all URLs on a domain. search google and return full content. an agent endpoint where you describe what you want and it goes and finds it. and a browser sandbox where AI controls a real browser like filling forms, clicking buttons, handles logins. 4. the agent endpoint is wild. you can say "find all of YC's winter 24 dev tool companies and their founders and emails" and get back structured data. or "compare pricing tiers across stripe, square, and paypal" and get a side-by-side table. 5. the browser sandbox lets your AI stay logged in across sessions, navigate pagination, watch live as it browses. this is computer use without building the infrastructure yourself. 6. think of it in layers. every builder needs: an agent harness (claude code, cursor, codex), a search layer (perplexity, exa), a web data layer (firecrawl), an ops brain (obsidian, notion), and an outbound stack. the web data layer is the one most people are sleeping on. 7. this is the AWS moment for web data. in 2006 building a web app meant buying servers and managing racks. AWS said one API call, use our servers. some of the biggest companies of the last decade were built on that. firecrawl is doing the same thing for web data in 2026. 8. the framework i'd use for coming up with startup ideas building with clean data: take a massive horizontal platform. rebuild it for one niche using firecrawl. the vertical version always wins because people want specific, not generic. price for outcome. 9. a year ago firecrawl posted a job listing that said "please only apply if you're an AI agent." content creator agents. customer support agents. junior dev agents. it looked weird. it was a signal for where this is all going. the people who understand how to get clean web data, wrap it around an LLM, and package it as a product are the the ones with a 12-month head start. i use Firecrawl with Idea Browser . once you see what's possible with structured web data, you can't unsee it. episode is live on The Startup Ideas Podcast (SIP) 🧃 (full breakdown there) i tried to explain this as clear as possible for even the non technical. send it to a builder friend. watch
27:27

how to use firecrawl to give your AI eyes and actually build startups that outperform 99% of apps: 1. your AI is smart but blind. it can't go to a website, read a page, or grab data on its own. firecrawl fixes that. you put in a URL. you get back clean markdown, structured JSON, screenshots. feed it to any model. 2. three lines of code. that's it. no proxies. no anti-bot detection. no custom scrapers that break when a site changes. one API call. clean data back in seconds. works on 98%+ of sites. 3. firecrawl has six core capabilities: scrape a single page. crawl an entire site. map all URLs on a domain. search google and return full content. an agent endpoint where you describe what you want and it goes and finds it. and a browser sandbox where AI controls a real browser like filling forms, clicking buttons, handles logins. 4. the agent endpoint is wild. you can say "find all of YC's winter 24 dev tool companies and their founders and emails" and get back structured data. or "compare pricing tiers across stripe, square, and paypal" and get a side-by-side table. 5. the browser sandbox lets your AI stay logged in across sessions, navigate pagination, watch live as it browses. this is computer use without building the infrastructure yourself. 6. think of it in layers. every builder needs: an agent harness (claude code, cursor, codex), a search layer (perplexity, exa), a web data layer (firecrawl), an ops brain (obsidian, notion), and an outbound stack. the web data layer is the one most people are sleeping on. 7. this is the AWS moment for web data. in 2006 building a web app meant buying servers and managing racks. AWS said one API call, use our servers. some of the biggest companies of the last decade were built on that. firecrawl is doing the same thing for web data in 2026. 8. the framework i'd use for coming up with startup ideas building with clean data: take a massive horizontal platform. rebuild it for one niche using firecrawl. the vertical version always wins because people want specific, not generic. price for outcome. 9. a year ago firecrawl posted a job listing that said "please only apply if you're an AI agent." content creator agents. customer support agents. junior dev agents. it looked weird. it was a signal for where this is all going. the people who understand how to get clean web data, wrap it around an LLM, and package it as a product are the the ones with a 12-month head start. i use Firecrawl with Idea Browser . once you see what's possible with structured web data, you can't unsee it. episode is live on The Startup Ideas Podcast (SIP) 🧃 (full breakdown there) i tried to explain this as clear as possible for even the non technical. send it to a builder friend. watch

GREG ISENBERG

135,254 次观看 • 5 个月前

Claude just got a massive upgrade today and I am proud to be part of it. From today on, Claude can generate videos, podcasts or host apps just like Lovable and Replit. We just launched SkillBoss a skill plugin for Claude that enables Claude to: ✅ Generate videos, images, audio, postcast ✅Build apps with logins, DBs, & payments built-in ✅ Send bulk marketing campaigns ✅ Host custom domains SkillBoss credit will cover all of the above with access to VEO, ElevenLabs, Sora API and 50 more. All you need is to go to download and drag to Claude. Then ask Claude to "make a cat video" or "build an app that charges $5"! SkillBoss also works with Codex, Codex, OpenCode and even OpenClaw(yeah I know!) To celebrate the launch, if you comment "skillboss", you will get 15 credit for free.
1:16

Claude just got a massive upgrade today and I am proud to be part of it. From today on, Claude can generate videos, podcasts or host apps just like Lovable and Replit. We just launched SkillBoss a skill plugin for Claude that enables Claude to: ✅ Generate videos, images, audio, postcast ✅Build apps with logins, DBs, & payments built-in ✅ Send bulk marketing campaigns ✅ Host custom domains SkillBoss credit will cover all of the above with access to VEO, ElevenLabs, Sora API and 50 more. All you need is to go to download and drag to Claude. Then ask Claude to "make a cat video" or "build an app that charges $5"! SkillBoss also works with Codex, Codex, OpenCode and even OpenClaw(yeah I know!) To celebrate the launch, if you comment "skillboss", you will get 15 credit for free.

Xiaoyin Qu

291,624 次观看 • 7 个月前