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Snippet of a tutorial demo ono setting up a free Github review agent using Servflow and Kimi (Bring your own key) The entire process was about 4 minutes in the full video from install to PR reviews. Complete with log analysis on the dashboard. Servflow is in early beta...

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14,576 просмотров • 1 месяц назад •via X (Twitter)

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Snippet from a demo of me creating a Binance trading agent served over an API endpoint (for potential customers) with the upcoming Servflow release. 🫵Go sign up on the form on the website to be notified of release (and to have free early access 🤭)
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Snippet from a demo of me creating a Binance trading agent served over an API endpoint (for potential customers) with the upcoming Servflow release. 🫵Go sign up on the form on the website to be notified of release (and to have free early access 🤭)

¿kofo?

12,445 просмотров • 8 месяцев назад

As promised, here's a tutorial on how to do these special FX insane transitions on your own videos using a Glif agent! i literally use this on my iPhone on the couch, so the demo is done like that as well Link to the agent below, tag me if you're making sth cool with it!
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As promised, here's a tutorial on how to do these special FX insane transitions on your own videos using a Glif agent! i literally use this on my iPhone on the couch, so the demo is done like that as well Link to the agent below, tag me if you're making sth cool with it!

fabian

11,693 просмотров • 10 месяцев назад

pr reviews with Tembo are on another level. this isn't static diff analysis. every pr gets its own vm, runs with any agent you choose, and reviews your code like a real engineer would. fully customizable instructions, plus the ability to pull in sentry or any other context. this is what agentic pr reviews were supposed to be.
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pr reviews with Tembo are on another level. this isn't static diff analysis. every pr gets its own vm, runs with any agent you choose, and reviews your code like a real engineer would. fully customizable instructions, plus the ability to pull in sentry or any other context. this is what agentic pr reviews were supposed to be.

benja

13,624 просмотров • 8 месяцев назад

...Am I the only one hand-rolling my PR review agent? It's so easy to do: - Write a /pr-review skill with the formatting you want - Add a GitHub workflow that runs your agent of choice, ideally a different model from your primary agent to find gaps in thinking Done!
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...Am I the only one hand-rolling my PR review agent? It's so easy to do: - Write a /pr-review skill with the formatting you want - Add a GitHub workflow that runs your agent of choice, ideally a different model from your primary agent to find gaps in thinking Done!

Ben Holmes

14,322 просмотров • 25 дней назад

If you're doing an AI startup, one of the key things to have in your arsenal to sell to customers is a *GOLDEN MAGIC DEMO* This was $600M exited startup Casetext's golden demo. Being able to review all the Enron emails in minutes: 5 days of work done by LLMs in minutes
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If you're doing an AI startup, one of the key things to have in your arsenal to sell to customers is a *GOLDEN MAGIC DEMO* This was $600M exited startup Casetext's golden demo. Being able to review all the Enron emails in minutes: 5 days of work done by LLMs in minutes

Garry Tan

316,660 просмотров • 2 лет назад

I wanted to share a quick demo of what we've been working on with our ai agent cloud. This enables fast deployment of agents that have access to a suite of tools, and was designed with agent interoperability in mind. This demo shows how you can go from nothing to an AI twitter agent in a couple minutes. This is what we are using internally to manage deployments, so we will consistently upgrading its capabilities. The next goals are to enable simple TEE deployments for agents, and focus on building out feature for agent interoperability to simplify agent to agent collaboration.
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I wanted to share a quick demo of what we've been working on with our ai agent cloud. This enables fast deployment of agents that have access to a suite of tools, and was designed with agent interoperability in mind. This demo shows how you can go from nothing to an AI twitter agent in a couple minutes. This is what we are using internally to manage deployments, so we will consistently upgrading its capabilities. The next goals are to enable simple TEE deployments for agents, and focus on building out feature for agent interoperability to simplify agent to agent collaboration.

Johnny

27,179 просмотров • 1 год назад

Airtable's Howie Liu says that basically everyone will need to graduate from being ICs to ICs that manage teams of 20-30 agents: "The best developers today don't just sit there in front of their IDEs and synchronously talk to their agent." "[Instead], you have like 30 separate branches that are each being worked on by a different agent. And you can have the agents continue to update the branches based on human and other agent feedback." "And I think this whole idea of it taking hours for that entire loop to complete — agent pushes some changes, the changes get feedback from other agents or humans, the agent responds to that — that whole loop could be hours, not just minutes. So you're not going to just sit there and watch it one at a time." "But the powerful thing about this is, each one is still actually operating faster than a human engineer. One agent on one branch can do the work of maybe three humans, operating 3x as fast. So it's like a 10x leverage factor just for one agent." "But the best engineers are now able to multitask and say, 'I'm going to oversee my own little team of 20-30 agents working concurrently.'" "Everyone needs to graduate from being an IC to an IC manager of agents. Meaning, if you're a VC analyst, your job should no longer be to go synchronously research one company. You need to go and research like 30 companies, and do them all faster, better, and higher quality than you could before." "That's the greatest leap that is going to be challenging for a lot of people in a lot of roles. Because it's a totally different mentality in how you operate, and what your role is."
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Airtable's Howie Liu says that basically everyone will need to graduate from being ICs to ICs that manage teams of 20-30 agents: "The best developers today don't just sit there in front of their IDEs and synchronously talk to their agent." "[Instead], you have like 30 separate branches that are each being worked on by a different agent. And you can have the agents continue to update the branches based on human and other agent feedback." "And I think this whole idea of it taking hours for that entire loop to complete — agent pushes some changes, the changes get feedback from other agents or humans, the agent responds to that — that whole loop could be hours, not just minutes. So you're not going to just sit there and watch it one at a time." "But the powerful thing about this is, each one is still actually operating faster than a human engineer. One agent on one branch can do the work of maybe three humans, operating 3x as fast. So it's like a 10x leverage factor just for one agent." "But the best engineers are now able to multitask and say, 'I'm going to oversee my own little team of 20-30 agents working concurrently.'" "Everyone needs to graduate from being an IC to an IC manager of agents. Meaning, if you're a VC analyst, your job should no longer be to go synchronously research one company. You need to go and research like 30 companies, and do them all faster, better, and higher quality than you could before." "That's the greatest leap that is going to be challenging for a lot of people in a lot of roles. Because it's a totally different mentality in how you operate, and what your role is."

TBPN

35,595 просмотров • 4 месяцев назад

The same kinds of productivity gains we've seen in coding with AI agents are heading to the rest of knowledge work. This is the jump when you go from having a chatbot to being able to actually have an agent go off and do work for minutes or even hours and come back with a complete work output that you then review. Here's an example of the new Box Agent filling out an RFP response from an existing knowledge base. This process would normally take hours to fill out, and requires the full attention of the user doing the work. Now, you provide the Box Agent with the RFP questions, and it will go off, make a plan, extract all the relevant questions, read through existing source material to come up with an answer, and then generate a new word document as the final output. All while you're doing something else. The key to this architecture is that the agent is able to use all of the same tools in the background that a user uses to get work done. The agent can search for documents, read entire files, run scripts and tools in the background, and even be able to write code on the fly to automate tasks it hasn't seen before. And best of all, the Box Agent will (soon) work from the Box MCP and CLI so you can invoke it in any agentic system as a step in a process. This kind of agent complexity would have been impossible even 6 months ago. Models consistently failed at tracking long running tasks or using the right tools at the right moment for the task. But this is all now possible because of models like GPT-5.4, Opus 4.6, and Gemini 3, and is only getting better by the month. Just as we moved from engineers writing code and using AI as an assistant to answer questions, in many areas of knowledge work -like legal, finance, consulting, sales, marketing, and more- when we have a problem we'll just kick off the AI agent to just go work on it for us in the background.
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The same kinds of productivity gains we've seen in coding with AI agents are heading to the rest of knowledge work. This is the jump when you go from having a chatbot to being able to actually have an agent go off and do work for minutes or even hours and come back with a complete work output that you then review. Here's an example of the new Box Agent filling out an RFP response from an existing knowledge base. This process would normally take hours to fill out, and requires the full attention of the user doing the work. Now, you provide the Box Agent with the RFP questions, and it will go off, make a plan, extract all the relevant questions, read through existing source material to come up with an answer, and then generate a new word document as the final output. All while you're doing something else. The key to this architecture is that the agent is able to use all of the same tools in the background that a user uses to get work done. The agent can search for documents, read entire files, run scripts and tools in the background, and even be able to write code on the fly to automate tasks it hasn't seen before. And best of all, the Box Agent will (soon) work from the Box MCP and CLI so you can invoke it in any agentic system as a step in a process. This kind of agent complexity would have been impossible even 6 months ago. Models consistently failed at tracking long running tasks or using the right tools at the right moment for the task. But this is all now possible because of models like GPT-5.4, Opus 4.6, and Gemini 3, and is only getting better by the month. Just as we moved from engineers writing code and using AI as an assistant to answer questions, in many areas of knowledge work -like legal, finance, consulting, sales, marketing, and more- when we have a problem we'll just kick off the AI agent to just go work on it for us in the background.

Aaron Levie

24,618 просмотров • 4 месяцев назад

I'm now building Executor full time as a startup! The state of tool calling is a mess: - Everyone is using different agents - You have no idea what actions are going to run - Destructive actions are treated the same as normal Executor lets you set up everything once & use it with any agent. You're able to control what tools can be called, require approval on destructive actions, and invite your team to all use them. Under the hood, it's built on codemode to let you add thousands of tools with 0 context bloat. I've been using it for a month so far and it has completely changed how I interact with agents. There's so much to be built here, immediately next up on the roadmap is workspaces, skills, workflows, and generative ui. Everything is being built open source over at there's a lot more coming on an SDK to embed it into your own agents, a self hostable cloud app, and plugins There's an early beta version over at It's very early on - if you hit any bugs let me know and I'll get them fixed up, excited to share more as I build it!
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I'm now building Executor full time as a startup! The state of tool calling is a mess: - Everyone is using different agents - You have no idea what actions are going to run - Destructive actions are treated the same as normal Executor lets you set up everything once & use it with any agent. You're able to control what tools can be called, require approval on destructive actions, and invite your team to all use them. Under the hood, it's built on codemode to let you add thousands of tools with 0 context bloat. I've been using it for a month so far and it has completely changed how I interact with agents. There's so much to be built here, immediately next up on the roadmap is workspaces, skills, workflows, and generative ui. Everything is being built open source over at there's a lot more coming on an SDK to embed it into your own agents, a self hostable cloud app, and plugins There's an early beta version over at It's very early on - if you hit any bugs let me know and I'll get them fixed up, excited to share more as I build it!

Rhys

220,477 просмотров • 3 месяцев назад

We are proud to announce the launch of our platform and the THREE initial agents: the Data Aggregation Agent, Sentiment Analysis Agent and Risk Manager Agent. This demo clip is a culmination of months of hard work and dedication to our vision. The platform have now entered a private alpha test which will be followed by a public beta. Tomorrow we will be doing a live streamed demo of the platform as it exists right now and will also be opening our waitlist to the general public. Thank you for your patience, belief and support. $cainam
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We are proud to announce the launch of our platform and the THREE initial agents: the Data Aggregation Agent, Sentiment Analysis Agent and Risk Manager Agent. This demo clip is a culmination of months of hard work and dedication to our vision. The platform have now entered a private alpha test which will be followed by a public beta. Tomorrow we will be doing a live streamed demo of the platform as it exists right now and will also be opening our waitlist to the general public. Thank you for your patience, belief and support. $cainam

Cainam Ventures

12,101 просмотров • 1 год назад

We are excited to announce a powerful step for the future of FOMO! Taking a page out of Virtuals book on BASE, FOMO will be releasing the ability for future projects to be paired in $FOMO in the coming weeks. This is the biggest release we have ever announced. Launch your AI Agent Token + $FOMO trading pair Every individual agent token is paired with the $FOMO token in its liquidity pool. When launching an agent on you will need $FOMO tokens, which are used to create the liquidity pool. This process creates deflationary pressure for FOMO and the entire agent ecosystem. When creating your agent and token, you will have the option to pair your launch with FOMO or SOL, as our goal is not to alienate any project, but rather invite the best communities, CTO’s and builders to launch with us. If you decide to pair your project with FOMO you in turn get full marketing and dev support, once your project graduates the bonding curve and reaches Raydium. Further, as an added incentive, as our revenue grows we will be using part of the funds to support projects that have paired in FOMO. And Devs who launch tokens paired in FOMO will earn fees from their AI Agent token launch. Building the most robust agents using our framework will catapult us as one of the most prominent standards of the Solana ecosystem. Not only have we developed our own core infrastructure, but we also pull from some of the best repo’s and developer talent in all of AI, not just blockchain. Our team is comprised of 9 world class artificial intelligence engineers, PHDs in mathematics and engineering from the top companies on the cutting edge of AI. The future of AI Agents will be on Solana and we will help lead the way.
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We are excited to announce a powerful step for the future of FOMO! Taking a page out of Virtuals book on BASE, FOMO will be releasing the ability for future projects to be paired in $FOMO in the coming weeks. This is the biggest release we have ever announced. Launch your AI Agent Token + $FOMO trading pair Every individual agent token is paired with the $FOMO token in its liquidity pool. When launching an agent on you will need $FOMO tokens, which are used to create the liquidity pool. This process creates deflationary pressure for FOMO and the entire agent ecosystem. When creating your agent and token, you will have the option to pair your launch with FOMO or SOL, as our goal is not to alienate any project, but rather invite the best communities, CTO’s and builders to launch with us. If you decide to pair your project with FOMO you in turn get full marketing and dev support, once your project graduates the bonding curve and reaches Raydium. Further, as an added incentive, as our revenue grows we will be using part of the funds to support projects that have paired in FOMO. And Devs who launch tokens paired in FOMO will earn fees from their AI Agent token launch. Building the most robust agents using our framework will catapult us as one of the most prominent standards of the Solana ecosystem. Not only have we developed our own core infrastructure, but we also pull from some of the best repo’s and developer talent in all of AI, not just blockchain. Our team is comprised of 9 world class artificial intelligence engineers, PHDs in mathematics and engineering from the top companies on the cutting edge of AI. The future of AI Agents will be on Solana and we will help lead the way.

FOMO

129,867 просмотров • 1 год назад

This little device lets your agents do what they do best, whilst making sure you approve every important action. This is a Ledger Nano Gen5, a hardware signer that keeps your accounts secure. You can install a CLI and a set of skills in your projects. These will enable your agents to send their plan to the signer, so you can approve it. This is awesome: 1. You can have an automated agentic workflow 2. Your agents can't make costly mistakes Check the video I recorded to see how this works. You can run all of this in two commands: 1. Install the CLI 2. Install the skills for your agent From here, the agent can query my Ethereum accounts, check balances, and even initiate transactions as long as my Ledger Nano Gen5 is plugged into the computer. My keys are never stored in my computer and never shared with the agent. This is huge! Also, while the agent can set up transactions, it can't execute them unless a human approves them using the device. Pretty awesome! Thanks to the Ledger team for partnering with me on this post.
7:45

This little device lets your agents do what they do best, whilst making sure you approve every important action. This is a Ledger Nano Gen5, a hardware signer that keeps your accounts secure. You can install a CLI and a set of skills in your projects. These will enable your agents to send their plan to the signer, so you can approve it. This is awesome: 1. You can have an automated agentic workflow 2. Your agents can't make costly mistakes Check the video I recorded to see how this works. You can run all of this in two commands: 1. Install the CLI 2. Install the skills for your agent From here, the agent can query my Ethereum accounts, check balances, and even initiate transactions as long as my Ledger Nano Gen5 is plugged into the computer. My keys are never stored in my computer and never shared with the agent. This is huge! Also, while the agent can set up transactions, it can't execute them unless a human approves them using the device. Pretty awesome! Thanks to the Ledger team for partnering with me on this post.

Santiago

44,296 просмотров • 2 месяцев назад

Hi everyone! Just rolled out access for NoSpoon Studios to the first 110 folks or so. Huge thanks to Karan and Amit at Luma - thanks to them, I have a few more people that had commented getting complimentary beta access soon as well :). These videos are created with a single agent that does everything from concept to completion (including editing the video together). Therer are longer options too, but for the sake of cost and this demo, you'll be working with 20s max generations. The entire agent was built to only run Ray2 as the video model. My stack is this custom agent of mine (using OAI) > Ray2 for the video > Replit for the app for now. In the meantime, for those with access: here's a video tutorial on how to use the site. I'm quite exhausted, but here's the gist: 1. Sign up (and remember your password lol). Beta testers got free credits, but these are a bit limited - rolling out to a few more peeps but have to budget and need to expand my current code (which means redeploying - so expect more of you to have 2 free credits and access tmr! I have to find out the max I can allot with budget). 2. Just hit "generate short video" without anything in the prompt box and the agent will start immediately with the logline. Be very patient, wait about 6-8 minutes, and it will continue to output all of the scenes and processing - it's very important you do not refresh or navigate away from that tab at this time. You'll see your final video generated and displayed at the bottom of your screen once complete, along with a watermark (paid users don't have a watermark). You can also access your loglines and videos in your history tab, too :). You must refresh the page only after your generation in order to generate a new video - otherwise you'll lose your generation (annoying I know). 3. You can also input your own custom prompt! Control the story this way. Single words work great even, like "thriller" or "spy thriller set in greece" or even "black and white film noir" etc etc. It's not as great with animated styles yet for consistency, just a heads up. 4. I'm exhausted, I'm sure there's a lot I'm missing. But welcome to the NoSpoon Studios soft beta! More soon! Feel free to share your generations if you are already in. I'll see you all tomorrow night :) <3 Thanks everyone! More soon.
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Hi everyone! Just rolled out access for NoSpoon Studios to the first 110 folks or so. Huge thanks to Karan and Amit at Luma - thanks to them, I have a few more people that had commented getting complimentary beta access soon as well :). These videos are created with a single agent that does everything from concept to completion (including editing the video together). Therer are longer options too, but for the sake of cost and this demo, you'll be working with 20s max generations. The entire agent was built to only run Ray2 as the video model. My stack is this custom agent of mine (using OAI) > Ray2 for the video > Replit for the app for now. In the meantime, for those with access: here's a video tutorial on how to use the site. I'm quite exhausted, but here's the gist: 1. Sign up (and remember your password lol). Beta testers got free credits, but these are a bit limited - rolling out to a few more peeps but have to budget and need to expand my current code (which means redeploying - so expect more of you to have 2 free credits and access tmr! I have to find out the max I can allot with budget). 2. Just hit "generate short video" without anything in the prompt box and the agent will start immediately with the logline. Be very patient, wait about 6-8 minutes, and it will continue to output all of the scenes and processing - it's very important you do not refresh or navigate away from that tab at this time. You'll see your final video generated and displayed at the bottom of your screen once complete, along with a watermark (paid users don't have a watermark). You can also access your loglines and videos in your history tab, too :). You must refresh the page only after your generation in order to generate a new video - otherwise you'll lose your generation (annoying I know). 3. You can also input your own custom prompt! Control the story this way. Single words work great even, like "thriller" or "spy thriller set in greece" or even "black and white film noir" etc etc. It's not as great with animated styles yet for consistency, just a heads up. 4. I'm exhausted, I'm sure there's a lot I'm missing. But welcome to the NoSpoon Studios soft beta! More soon! Feel free to share your generations if you are already in. I'll see you all tomorrow night :) <3 Thanks everyone! More soon.

Kiri

15,513 просмотров • 1 год назад

Introducing /ui-test Give your agent a PR, and it'll test your feature in a real browser, generating an HTML report with UI fixes The planner agent generates adversarial test cases to break your app, assigns them to subagents, and evaluates the page using the Browserbase CLI We reviewed a merged PR on Cal.com and found a bunch of small UI nits:
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Introducing /ui-test Give your agent a PR, and it'll test your feature in a real browser, generating an HTML report with UI fixes The planner agent generates adversarial test cases to break your app, assigns them to subagents, and evaluates the page using the Browserbase CLI We reviewed a merged PR on Cal.com and found a bunch of small UI nits:

Shrey Pandya

57,825 просмотров • 4 месяцев назад

you don't have to keep your laptop open for your agents to keep running just type /handoff and send your agent to the cloud with Devin (and close your laptop) from there, your agent gets: - its own Linux VM - shell, IDE, browser - full desktop Computer Use - end-to-end test recordings - ready-to-review PRs - it's own review agent you can continue your session from your phone, computer, or anywhere with an internet connection and you can send as many sessions as you'd like in parallel.
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you don't have to keep your laptop open for your agents to keep running just type /handoff and send your agent to the cloud with Devin (and close your laptop) from there, your agent gets: - its own Linux VM - shell, IDE, browser - full desktop Computer Use - end-to-end test recordings - ready-to-review PRs - it's own review agent you can continue your session from your phone, computer, or anywhere with an internet connection and you can send as many sessions as you'd like in parallel.

nader dabit

61,367 просмотров • 3 месяцев назад

This agent relies on a marketplace of 2.8M+ specialized agents to complete a task. This is how I imagine the future of personal agents. Here is how this works: 1. Agentverse is a marketplace of agents 2. Anyone can build and publish an agent there 3. ASI:One is a personal agent with access to the marketplace 4. To solve a task, ASI:One finds the best agent for the job In other words: You have an agent that can solve pretty much *anything* because it knows how to outsource the work to a network of specialized agents. And you don't need to do any setup to get this working. The way ranking agents in the marketplace works is pretty cool: Fetch.ai, the company behind it, created an AgentRank algorithm that works much like Google's PageRank. Every time an agent calls another, it forms a connection. Over time, these connections build into a graph of who relies on whom. An agent that is frequently called by other reputable agents scores higher and surfaces higher in results. The end result here is that your agent will consistently use the best agents in the marketplace to accomplish a goal. You should give this a try: You don't need to pay or even register to try these agents. Thanks to the team for partnering with me on this post.
4:16

This agent relies on a marketplace of 2.8M+ specialized agents to complete a task. This is how I imagine the future of personal agents. Here is how this works: 1. Agentverse is a marketplace of agents 2. Anyone can build and publish an agent there 3. ASI:One is a personal agent with access to the marketplace 4. To solve a task, ASI:One finds the best agent for the job In other words: You have an agent that can solve pretty much *anything* because it knows how to outsource the work to a network of specialized agents. And you don't need to do any setup to get this working. The way ranking agents in the marketplace works is pretty cool: Fetch.ai, the company behind it, created an AgentRank algorithm that works much like Google's PageRank. Every time an agent calls another, it forms a connection. Over time, these connections build into a graph of who relies on whom. An agent that is frequently called by other reputable agents scores higher and surfaces higher in results. The end result here is that your agent will consistently use the best agents in the marketplace to accomplish a goal. You should give this a try: You don't need to pay or even register to try these agents. Thanks to the team for partnering with me on this post.

Santiago

18,715 просмотров • 2 месяцев назад

AI agents are becoming increasingly capable of taking actions beyond the chat window and interacting with tools in the real world, such as web browsers. We explored this capability by having an AI agent present one of our interactive web-based demos. In this video, it's presenting our election interference demo. This agent is a Cursor coding agent and is equipped with tools to read and interact with the browser (using Playwright) and perform text-to-speech (with ElevenLabs), in addition to the standard Cursor tools.
3:23

AI agents are becoming increasingly capable of taking actions beyond the chat window and interacting with tools in the real world, such as web browsers. We explored this capability by having an AI agent present one of our interactive web-based demos. In this video, it's presenting our election interference demo. This agent is a Cursor coding agent and is equipped with tools to read and interact with the browser (using Playwright) and perform text-to-speech (with ElevenLabs), in addition to the standard Cursor tools.

CivAI

18,428 просмотров • 8 месяцев назад

.Box CEO Aaron Levie on why AI agents can't keep a secret. "The reason why you probably won't see a complete compression of software where it's just a an agent and a database is because there's a lot of logic in the workflow and in the the company's specific sort of business process that needs to be built into that and around that database." "The agent will make a mistake 1% of the time and it will share the wrong thing with somebody or open up an access privilege to the wrong person." "AI agents can't keep a secret." Watch the full episode on
1:42

.Box CEO Aaron Levie on why AI agents can't keep a secret. "The reason why you probably won't see a complete compression of software where it's just a an agent and a database is because there's a lot of logic in the workflow and in the the company's specific sort of business process that needs to be built into that and around that database." "The agent will make a mistake 1% of the time and it will share the wrong thing with somebody or open up an access privilege to the wrong person." "AI agents can't keep a secret." Watch the full episode on

The Information

311,076 просмотров • 1 год назад

I have done a speed paint to address the ai allegations. This was done completely live on twitch with a full display screen showing my entire process. The link to the VOD is down below. I am aware of the other things being said and everything will be addressed soon. There is a lot to go over and I want to make sure I address everything. This has been a lot to take in so i thank you for your patience.
1:00

I have done a speed paint to address the ai allegations. This was done completely live on twitch with a full display screen showing my entire process. The link to the VOD is down below. I am aware of the other things being said and everything will be addressed soon. There is a lot to go over and I want to make sure I address everything. This has been a lot to take in so i thank you for your patience.

𓆩ɢᴏᴍɪ𓆪

87,200 просмотров • 6 месяцев назад

What has been done and what's next. I'm writing this text mainly for myself so as not to forget some things. Later, based on it, we'll create a roadmap for the near future. And for you, dear $Gruta Fam, it will be useful for a general understanding of where we're heading. So, the goal is to create a unique AI-based analytical platform that includes several tools. AI agent Grufender - real-time analysis of crypto communities on X. Activity analysis, sentiment analysis, FUD and FUDders analysis, as well as the creation of other unique social metrics. The AI agent has been created and is functioning, collecting and analyzing data in real time. Its completeness can be estimated at 80 percent, as further improvements are required. The dashboard for this AI agent is also functioning but needs refinement and a new design. Its completeness can be estimated at 70 percent. The goal for the full dashboard release is to connect 50 - 100 top crypto communities to the AI agent. AI agent Grutector - analysis of any X users for contradictions (flip-flops). The AI agent has been created and is functioning. It has undergone beta testing by volunteers and needs adjustments. Its readiness can be estimated at 70 percent. The dashboard for this agent has also been created but needs rework and additional features - its readiness can be estimated at 50 percent. During the testing of Grutector , it became clear that the main user interest is in checking various KOLs, so an additional level of analysis specifically for KOLs will be created. More in-depth. How it will look: we'll select about 50- 100 KOLs to start with and fully analyze them using our AI agent - every tweet throughout the entire history of their accounts. And this full analysis of all these KOLs will appear on the Grutector dashboard (let's call this analysis L2, and the flip-flop analysis - L1). Every user will be able to access this analysis and get the full picture, for example, regarding Ansem 🐂🀄️ (who has over a hundred thousand tweets in his entire history!): how he became a KOL, what was the most interesting throughout the message history, what common patterns, which coins he promoted, and so on. And then the most interesting part - after reading this analysis, the user will be able to ask our AI agent: what did he say about women, for example? Or how did he promote certain coins? Or how consistent is he? And so on. Each such question will be paid. And, of course, we'll try to use #x402 in the internal payment system. Why is all this needed? Not only because it's interesting and will attract many users. But also if you've decided to buy a coin - you go to our analytical platform - and study the metrics for the coin's community, study the KOLs who shill the coin - and make a decision to buy the coin or abandon the purchase. And we're also currently creating a trading bot to participate in the trading AI bots contest from Aster 🥷 , which will make trading decisions based on metrics obtained from our AI agents 👀 Its readiness at the moment is approximately 15% of the planned functionality. Access to each product will be granted as it becomes ready. But right now, for example, you can explore the Grufender dashboard on the website along with beta testers (authorization via a wallet with a million $GRUTA tokens). In general, we're working, friends 🫡 $Gruta AI CA: 35t5DPbwJtB1tpGiSnqedLwQomi94BRKVDPyTRLdbonk
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What has been done and what's next. I'm writing this text mainly for myself so as not to forget some things. Later, based on it, we'll create a roadmap for the near future. And for you, dear $Gruta Fam, it will be useful for a general understanding of where we're heading. So, the goal is to create a unique AI-based analytical platform that includes several tools. AI agent Grufender - real-time analysis of crypto communities on X. Activity analysis, sentiment analysis, FUD and FUDders analysis, as well as the creation of other unique social metrics. The AI agent has been created and is functioning, collecting and analyzing data in real time. Its completeness can be estimated at 80 percent, as further improvements are required. The dashboard for this AI agent is also functioning but needs refinement and a new design. Its completeness can be estimated at 70 percent. The goal for the full dashboard release is to connect 50 - 100 top crypto communities to the AI agent. AI agent Grutector - analysis of any X users for contradictions (flip-flops). The AI agent has been created and is functioning. It has undergone beta testing by volunteers and needs adjustments. Its readiness can be estimated at 70 percent. The dashboard for this agent has also been created but needs rework and additional features - its readiness can be estimated at 50 percent. During the testing of Grutector , it became clear that the main user interest is in checking various KOLs, so an additional level of analysis specifically for KOLs will be created. More in-depth. How it will look: we'll select about 50- 100 KOLs to start with and fully analyze them using our AI agent - every tweet throughout the entire history of their accounts. And this full analysis of all these KOLs will appear on the Grutector dashboard (let's call this analysis L2, and the flip-flop analysis - L1). Every user will be able to access this analysis and get the full picture, for example, regarding Ansem 🐂🀄️ (who has over a hundred thousand tweets in his entire history!): how he became a KOL, what was the most interesting throughout the message history, what common patterns, which coins he promoted, and so on. And then the most interesting part - after reading this analysis, the user will be able to ask our AI agent: what did he say about women, for example? Or how did he promote certain coins? Or how consistent is he? And so on. Each such question will be paid. And, of course, we'll try to use #x402 in the internal payment system. Why is all this needed? Not only because it's interesting and will attract many users. But also if you've decided to buy a coin - you go to our analytical platform - and study the metrics for the coin's community, study the KOLs who shill the coin - and make a decision to buy the coin or abandon the purchase. And we're also currently creating a trading bot to participate in the trading AI bots contest from Aster 🥷 , which will make trading decisions based on metrics obtained from our AI agents 👀 Its readiness at the moment is approximately 15% of the planned functionality. Access to each product will be granted as it becomes ready. But right now, for example, you can explore the Grufender dashboard on the website along with beta testers (authorization via a wallet with a million $GRUTA tokens). In general, we're working, friends 🫡 $Gruta AI CA: 35t5DPbwJtB1tpGiSnqedLwQomi94BRKVDPyTRLdbonk

Dogtor

16,161 просмотров • 9 месяцев назад