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MCP + Palantir AIP, enabling production-grade vibe coding. At DevCon 3, Lennar Manager of Data & Analytics Michael Seman described how Palantir’s new MCP integration enabled his teams to move faster, and automate more than ever before.

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114,805 görüntüleme • 1 yıl önce •via X (Twitter)

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incorporating palantir’s mcp could revolutionize data workflows—speed and automation are vital for success. exciting times ahead!

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Today we celebrate the end of production on the 747, the world's first jumbo jet -- a plane that enabled more people to fly farther, faster and more affordably than ever before. #QueenOfTheSkies Tune in here at 1 p.m. PST:

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454,969 görüntüleme • 3 yıl önce

An AI engineer at Microsoft has just revealed how their teams build AI agents using Anthropic (Claude). It’s a free 34-minute workshop delivered directly by the Microsoft team. Save it to your favorites and watch it as soon as possible. 🔖 Opus 4.7 + more than 1,400 MCP tools already ready to use. You connect Claude to an agent → add tools → deploy it to production. It’s way more practical and useful than most of those “vibe-coding” courses that sell for 500).
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An AI engineer at Microsoft has just revealed how their teams build AI agents using Anthropic (Claude). It’s a free 34-minute workshop delivered directly by the Microsoft team. Save it to your favorites and watch it as soon as possible. 🔖 Opus 4.7 + more than 1,400 MCP tools already ready to use. You connect Claude to an agent → add tools → deploy it to production. It’s way more practical and useful than most of those “vibe-coding” courses that sell for 500).

me

411,114 görüntüleme • 3 ay önce

MCP is mind-blowing. Here is a genius setup that will earn you a promotion with your manager. I have multiple data sources: data in S3, MySQL, and local files. Using Spice (an open-source project), I can co-locate all of that data behind a single SQL endpoint and augment it using MCP. Before, accessing data was slow, and I had to make multiple requests to get anything. After using Spice, I can query the data much faster (since it's mirrored locally), and I don't have to worry about where the data is coming from. Spice acts as an MCP server, so I can connect to it from my IDE or the Claude Desktop app and have access to all the data. But even more cool than that: Spice also acts as an MCP client, so it can connect to other MCP servers. This is where things get really interesting! Watch the video. I'm querying multiple data sources from my IDE and using the Google Maps MCP server for driving directions.
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MCP is mind-blowing. Here is a genius setup that will earn you a promotion with your manager. I have multiple data sources: data in S3, MySQL, and local files. Using Spice (an open-source project), I can co-locate all of that data behind a single SQL endpoint and augment it using MCP. Before, accessing data was slow, and I had to make multiple requests to get anything. After using Spice, I can query the data much faster (since it's mirrored locally), and I don't have to worry about where the data is coming from. Spice acts as an MCP server, so I can connect to it from my IDE or the Claude Desktop app and have access to all the data. But even more cool than that: Spice also acts as an MCP client, so it can connect to other MCP servers. This is where things get really interesting! Watch the video. I'm querying multiple data sources from my IDE and using the Google Maps MCP server for driving directions.

Santiago

142,696 görüntüleme • 1 yıl önce

🔮 MCP INTEGRATION NOW LIVE ON OPENSERV This is bigger than most realize. We're not just adding a feature - we're enabling a fundamentally new paradigm for agent infrastructure. Before MCP: agents trapped in walled gardens, limited by what you explicitly feed them. After MCP: agents that can access 10K+ tools, interact with your existing systems, and truly operate in your digital world. Think about this: -Every integration used to require custom code -Every data source needed specific formatting -Every agent had to be built for specific tools MCP eliminates all of that. One standard to connect any agent to any tool. This isn't just convenience - it's the unlock that makes agents actually useful in the real world. OpenServ + MCP = AI teams that can genuinely get things done, not just talk about doing them. This is the breakthrough that turns agents from toys into tools.
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🔮 MCP INTEGRATION NOW LIVE ON OPENSERV This is bigger than most realize. We're not just adding a feature - we're enabling a fundamentally new paradigm for agent infrastructure. Before MCP: agents trapped in walled gardens, limited by what you explicitly feed them. After MCP: agents that can access 10K+ tools, interact with your existing systems, and truly operate in your digital world. Think about this: -Every integration used to require custom code -Every data source needed specific formatting -Every agent had to be built for specific tools MCP eliminates all of that. One standard to connect any agent to any tool. This isn't just convenience - it's the unlock that makes agents actually useful in the real world. OpenServ + MCP = AI teams that can genuinely get things done, not just talk about doing them. This is the breakthrough that turns agents from toys into tools.

OpenServ

34,665 görüntüleme • 1 yıl önce

Al has collapsed the time it takes to ship a feature. Now it's all about shipping the right thing. It's just as hard as it ever was. As coding gets automated, agentic analytics becomes the bottleneck. Teams that win will build within context rich environments that capture user behavior and customer feedback, making that data accessible to both builders and agents. Today Amplitude is launching our Al Analytics Platform with Agents and MCP. Autonomous analytics that helps builders and coding agents ship products that their customers actually want. Just as our partner Claude has reinvented software, Amplitude is reinventing analytics for the Al age. We have achieved 76% accuracy for complex production grade queries and agentic usage has grown 10x in 3 months. Don't just build fast, build what's right. Try it for free, today.
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Al has collapsed the time it takes to ship a feature. Now it's all about shipping the right thing. It's just as hard as it ever was. As coding gets automated, agentic analytics becomes the bottleneck. Teams that win will build within context rich environments that capture user behavior and customer feedback, making that data accessible to both builders and agents. Today Amplitude is launching our Al Analytics Platform with Agents and MCP. Autonomous analytics that helps builders and coding agents ship products that their customers actually want. Just as our partner Claude has reinvented software, Amplitude is reinventing analytics for the Al age. We have achieved 76% accuracy for complex production grade queries and agentic usage has grown 10x in 3 months. Don't just build fast, build what's right. Try it for free, today.

Spenser Skates

334,312 görüntüleme • 6 ay önce

Day 23 of vibe coding game since fable came back, we’ve been locked in on game development unreal new mcp isn’t that great, so we still have to do some stuff manually but at least i’m learning something lol added drifting today and made the car feel more realistic how does it look?
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Day 23 of vibe coding game since fable came back, we’ve been locked in on game development unreal new mcp isn’t that great, so we still have to do some stuff manually but at least i’m learning something lol added drifting today and made the car feel more realistic how does it look?

J A Z I I

19,287 görüntüleme • 2 ay önce

We knew from day one that unlocking constellation-scale manufacturing would be more than just a hardware challenge. That's why we built Octopus — our proprietary operating system, developed in-house to handle the many complexities of rapidly scaling satellite manufacturing. Octopus provides an end-to-end source of truth, from first customer conversation to orbit, enabling streamlined traceability that ensures speed never comes at the expense of quality. Octopus is built on Palantir's Foundry and AIP platforms, which provide the underlying infrastructure to rapidly prototype and deploy custom applications across the entire company. By building Octopus on Palantir, we have unified scheduling, procurement, receiving, inspection, inventory management, and production into a single integrated workflow — enabling predictable and secure, constellation-scale production. Hear from Apex CEO, Ian Cinnamon, and the rest of the team on how Apex's partnership with Palantir is unlocking rate production at Factory One, and laying the foundation for the next generation of satellite manufacturing.
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We knew from day one that unlocking constellation-scale manufacturing would be more than just a hardware challenge. That's why we built Octopus — our proprietary operating system, developed in-house to handle the many complexities of rapidly scaling satellite manufacturing. Octopus provides an end-to-end source of truth, from first customer conversation to orbit, enabling streamlined traceability that ensures speed never comes at the expense of quality. Octopus is built on Palantir's Foundry and AIP platforms, which provide the underlying infrastructure to rapidly prototype and deploy custom applications across the entire company. By building Octopus on Palantir, we have unified scheduling, procurement, receiving, inspection, inventory management, and production into a single integrated workflow — enabling predictable and secure, constellation-scale production. Hear from Apex CEO, Ian Cinnamon, and the rest of the team on how Apex's partnership with Palantir is unlocking rate production at Factory One, and laying the foundation for the next generation of satellite manufacturing.

Apex - Satellite Platforms 🛰

33,843 görüntüleme • 6 ay önce

Announcing Superblocks on Snowflake: Secure Enterprise Vibe Coding on the AI Data Cloud This couldn't be more timely. Vibe coding is exploding inside the enterprise. It’s also becoming the fastest path to a data breach. Every CEO is trying to accelerate adoption of vibe coding for business users automate, without blocking on engineering. Every VP of Data and CIO is trying to figure out how to lock down their data, harden their permissions, and gain centralized visibility. That’s exactly what this partnership unlocks. Superblocks becomes the enterprise platform for governed vibe coding across business teams, deeply embedded within Snowflake: > Snowflake Postgres becomes your secure vibe coding database. Superblocks spins it up in every app for fast writes and net new operational workflow data >Snowflake Cortex becomes the inference engine for Superblocks. Your prompts and vibe coded AI features run within your trusted security perimeter >Snowflake Warehouse governance is enforced. AI apps use federated token passthrough so your existing row level access policies, dynamic data masking, tag-based-access controls are respected “With Superblocks on Snowflake, any business team can safely build AI applications governed on their Snowflake data. It’s a dream come true.” -Unmesh Jagtap, Director of Product, Snowflake Now enterprises can stop playing whack-a-mole, and move your organization past the AI prototype graveyard. If you’re a Snowflake customer, book a demo (link in comments) Thanks to the Snowflake team for the partnership: Christian Kleinerman, Vivek Raghunathan, Bala Kasiviswanathan, Unmesh Jagtap, and Myles Borins for helping shape how the industry democratizes governed AI app development while centralizing control on the AI Data Cloud.
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Announcing Superblocks on Snowflake: Secure Enterprise Vibe Coding on the AI Data Cloud This couldn't be more timely. Vibe coding is exploding inside the enterprise. It’s also becoming the fastest path to a data breach. Every CEO is trying to accelerate adoption of vibe coding for business users automate, without blocking on engineering. Every VP of Data and CIO is trying to figure out how to lock down their data, harden their permissions, and gain centralized visibility. That’s exactly what this partnership unlocks. Superblocks becomes the enterprise platform for governed vibe coding across business teams, deeply embedded within Snowflake: > Snowflake Postgres becomes your secure vibe coding database. Superblocks spins it up in every app for fast writes and net new operational workflow data >Snowflake Cortex becomes the inference engine for Superblocks. Your prompts and vibe coded AI features run within your trusted security perimeter >Snowflake Warehouse governance is enforced. AI apps use federated token passthrough so your existing row level access policies, dynamic data masking, tag-based-access controls are respected “With Superblocks on Snowflake, any business team can safely build AI applications governed on their Snowflake data. It’s a dream come true.” -Unmesh Jagtap, Director of Product, Snowflake Now enterprises can stop playing whack-a-mole, and move your organization past the AI prototype graveyard. If you’re a Snowflake customer, book a demo (link in comments) Thanks to the Snowflake team for the partnership: Christian Kleinerman, Vivek Raghunathan, Bala Kasiviswanathan, Unmesh Jagtap, and Myles Borins for helping shape how the industry democratizes governed AI app development while centralizing control on the AI Data Cloud.

Brad Menezes

13,241 görüntüleme • 4 ay önce

Big moment for Postgres! AI coding tools have been surprisingly bad at writing Postgres code. Not because the models are dumb, but because of how they learned SQL in the first place. LLMs are trained on the internet, which is full of outdated Stack Overflow answers and quick-fix tutorials. So when you ask an AI to generate a schema, it gives you something that technically runs but misses decades of Postgres evolution, like: - No GENERATED ALWAYS AS IDENTITY (added in PG10) - No expression or partial indexes - No NULLS NOT DISTINCT (PG15) - Missing CHECK constraints and proper foreign keys - Generic naming that tells you nothing But this is actually a solvable problem. You can teach AI tools to write better Postgres by giving them access to the right documentation at inference time. This exact solution is actually implemented in the newly released pg-aiguide by Tiger Data - Creators of TimescaleDB, which is an open-source MCP server that provides coding tools access to 35 years of Postgres expertise. In a gist, the MCP server enables: - Semantic search over the official PostgreSQL manual (version-aware, so it knows PG14 vs PG17 differences) - Curated skills with opinionated best practices for schema design, indexing, and constraints. I ran an experiment with Claude Code to see how well this works, and worked with the team to put this together. Prompt: "Generate a schema for an e-commerce site twice, one with the MCP server disabled, one with it enabled. Finally, run an assessment to compare the generated schemas." The run with the MCP server led to: - 420% more indexes (including partial and expression indexes) - 235% more constraints - 60% more tables (proper normalization) - 11 automation functions and triggers - Modern PG17 patterns throughout The MCP-assisted schema had proper data integrity, performance optimizations baked in, and followed naming conventions that actually make sense in production. pg-aiguide works with Claude Code, Cursor, VS Code, and any MCP-compatible tool. It's free and fully open source. I have shared the repo in the replies!
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Big moment for Postgres! AI coding tools have been surprisingly bad at writing Postgres code. Not because the models are dumb, but because of how they learned SQL in the first place. LLMs are trained on the internet, which is full of outdated Stack Overflow answers and quick-fix tutorials. So when you ask an AI to generate a schema, it gives you something that technically runs but misses decades of Postgres evolution, like: - No GENERATED ALWAYS AS IDENTITY (added in PG10) - No expression or partial indexes - No NULLS NOT DISTINCT (PG15) - Missing CHECK constraints and proper foreign keys - Generic naming that tells you nothing But this is actually a solvable problem. You can teach AI tools to write better Postgres by giving them access to the right documentation at inference time. This exact solution is actually implemented in the newly released pg-aiguide by Tiger Data - Creators of TimescaleDB, which is an open-source MCP server that provides coding tools access to 35 years of Postgres expertise. In a gist, the MCP server enables: - Semantic search over the official PostgreSQL manual (version-aware, so it knows PG14 vs PG17 differences) - Curated skills with opinionated best practices for schema design, indexing, and constraints. I ran an experiment with Claude Code to see how well this works, and worked with the team to put this together. Prompt: "Generate a schema for an e-commerce site twice, one with the MCP server disabled, one with it enabled. Finally, run an assessment to compare the generated schemas." The run with the MCP server led to: - 420% more indexes (including partial and expression indexes) - 235% more constraints - 60% more tables (proper normalization) - 11 automation functions and triggers - Modern PG17 patterns throughout The MCP-assisted schema had proper data integrity, performance optimizations baked in, and followed naming conventions that actually make sense in production. pg-aiguide works with Claude Code, Cursor, VS Code, and any MCP-compatible tool. It's free and fully open source. I have shared the repo in the replies!

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187,076 görüntüleme • 8 ay önce

Mansa AI is an enterprise-grade AI + Web3 platform designed to move artificial intelligence from experimentation into real-world execution. Built for creators, developers, and businesses, it focuses on deploying AI that actually works across modern digital systems, not just in isolated demos. 🚀 Production-ready AI infrastructure Mansa AI enables teams to deploy AI systems designed for live environments, handling real workflows, real data, and real operational demands without constant manual oversight. 🧠 Autonomous AI agents At its core, Mansa AI allows users to build autonomous agents that automate decision-making, coordinate tasks, monitor live signals, and execute complex workflows across dynamic environments. ⚙️ Fully customizable logic Agents can be configured with custom behaviors, triggers, and responses. From content generation and analytics to operational automation and intelligent orchestration, logic adapts to specific business strategies. 🔗 Web3 and off-chain integration Mansa AI bridges blockchain ecosystems with traditional systems, enabling cross-chain coordination, smart contract interactions, and seamless integration with existing enterprise infrastructure. 📊 Real-world use cases The platform supports automation for operations, customer engagement, analytics, data pipelines, content workflows, and AI-driven optimization across products and teams. 📈 Built for scale Whether launching as a startup or deploying across enterprise systems, Mansa AI is designed to scale AI operations without adding complexity or fragmentation. Mansa AI transforms artificial intelligence into deployable infrastructure. By combining autonomy, customization, interoperability, and scalability, it enables teams to own, operate, and grow intelligent systems that deliver real value in production environments.
2:00

Mansa AI is an enterprise-grade AI + Web3 platform designed to move artificial intelligence from experimentation into real-world execution. Built for creators, developers, and businesses, it focuses on deploying AI that actually works across modern digital systems, not just in isolated demos. 🚀 Production-ready AI infrastructure Mansa AI enables teams to deploy AI systems designed for live environments, handling real workflows, real data, and real operational demands without constant manual oversight. 🧠 Autonomous AI agents At its core, Mansa AI allows users to build autonomous agents that automate decision-making, coordinate tasks, monitor live signals, and execute complex workflows across dynamic environments. ⚙️ Fully customizable logic Agents can be configured with custom behaviors, triggers, and responses. From content generation and analytics to operational automation and intelligent orchestration, logic adapts to specific business strategies. 🔗 Web3 and off-chain integration Mansa AI bridges blockchain ecosystems with traditional systems, enabling cross-chain coordination, smart contract interactions, and seamless integration with existing enterprise infrastructure. 📊 Real-world use cases The platform supports automation for operations, customer engagement, analytics, data pipelines, content workflows, and AI-driven optimization across products and teams. 📈 Built for scale Whether launching as a startup or deploying across enterprise systems, Mansa AI is designed to scale AI operations without adding complexity or fragmentation. Mansa AI transforms artificial intelligence into deployable infrastructure. By combining autonomy, customization, interoperability, and scalability, it enables teams to own, operate, and grow intelligent systems that deliver real value in production environments.

King

155,637 görüntüleme • 9 ay önce

New course: Gemini CLI: Code & Create with an Open-Source Agent, built with Google Cloud Tech/Gemini CLI and taught by Jack Wotherspoon. Agentic coding assistants like Gemini CLI are transforming how developers work. This short course teaches you to use Google's open-source agent to coordinate local tools and cloud services for coding and non-coding workflows. Gemini CLI works from your terminal, so it works with your local files and development tools. You can also connect it to services through MCP. Then provide high-level instructions, and it autonomously plans and executes complex workflows. Skills you'll gain: - Build website features and automate code reviews with GitHub ActionsCreate data dashboards that combine local files with cloud data sources - Use MCP servers and extensions to orchestrate workflows across GitHub, Canva, and Google Workspace - Generate social media content from multimedia files like conference recordings I particularly appreciate that Gemini CLI is open-source. You can see exactly how it works, read the prompts it uses, and understand its architecture. The community has contributed thousands of pull requests. Since Gemini 3’s release I've found Gemini CLI highly capable - this is a tool worth having in your toolbox! Whether you're prototyping applications, automating workflows, or working with multimedia content, join to learn to delegate complex tasks and build faster:
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New course: Gemini CLI: Code & Create with an Open-Source Agent, built with Google Cloud Tech/Gemini CLI and taught by Jack Wotherspoon. Agentic coding assistants like Gemini CLI are transforming how developers work. This short course teaches you to use Google's open-source agent to coordinate local tools and cloud services for coding and non-coding workflows. Gemini CLI works from your terminal, so it works with your local files and development tools. You can also connect it to services through MCP. Then provide high-level instructions, and it autonomously plans and executes complex workflows. Skills you'll gain: - Build website features and automate code reviews with GitHub ActionsCreate data dashboards that combine local files with cloud data sources - Use MCP servers and extensions to orchestrate workflows across GitHub, Canva, and Google Workspace - Generate social media content from multimedia files like conference recordings I particularly appreciate that Gemini CLI is open-source. You can see exactly how it works, read the prompts it uses, and understand its architecture. The community has contributed thousands of pull requests. Since Gemini 3’s release I've found Gemini CLI highly capable - this is a tool worth having in your toolbox! Whether you're prototyping applications, automating workflows, or working with multimedia content, join to learn to delegate complex tasks and build faster:

Andrew Ng

125,385 görüntüleme • 7 ay önce

"Claude Code is the first AI tool that can actually recreate how a data scientist thinks." Here's my new episode with Sumeet Marwaha (Head of Data at Brex) on exactly how to build an AI analyst with Claude Code. We covered: ✅ 3 queries to build a data analyst MCP ✅ How to give the analyst both data + context ✅ Exclusive Brex data on which AI tools are crushing it in startups and enterprise Some quotes from Sumeet: "I've set up dashboards many times in my career. They end up getting ignored. Claude will always read it. Claude will always ask the right questions." "You have to set up Claude Code to not just look at the data. It should be able to search Slack, find the incident, and understand why your metrics look wrong." "This tool is absolutely crushing it based on our data. It's both the startup AND enterprise coding tool of choice." 📌 Watch now:
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"Claude Code is the first AI tool that can actually recreate how a data scientist thinks." Here's my new episode with Sumeet Marwaha (Head of Data at Brex) on exactly how to build an AI analyst with Claude Code. We covered: ✅ 3 queries to build a data analyst MCP ✅ How to give the analyst both data + context ✅ Exclusive Brex data on which AI tools are crushing it in startups and enterprise Some quotes from Sumeet: "I've set up dashboards many times in my career. They end up getting ignored. Claude will always read it. Claude will always ask the right questions." "You have to set up Claude Code to not just look at the data. It should be able to search Slack, find the incident, and understand why your metrics look wrong." "This tool is absolutely crushing it based on our data. It's both the startup AND enterprise coding tool of choice." 📌 Watch now:

Peter Yang

39,600 görüntüleme • 7 ay önce

🚨NEW EPISODE: AI Is Changing How We Work with Crypto Data🚨 In today's episode, we're joined by Kofi to discuss how AI agents are fundamentally changing crypto data analysis, research, and engineering workflows. We discuss: - The evolution from manual coding to AI-assisted development - How MCPs unlock onchain data exploration - Using Herd MCP to analyze smart contracts - AI agents for protocol research and data engineering - Context windows, planning, and agent workflows - Cursor vs OpenCode vs Claude Code (Anthropic) - Managing multiple agents simultaneously - Model selection, costs, and productivity tradeoffs - Building internal AI knowledge bases - Agent orchestration and autonomous workflows - Training agents to replicate human expertise - The future of AI-powered crypto analytics - And much more—enjoy! — Timestamps: (00:00) Introduction (01:24) AI replaces frontends (03:24) Herd MCP demo (05:40) Exploring contracts with AI (08:06) Exploration, planning, execution (11:38) Investigating onchain activity (17:10) Managing agent workflows (20:20) Multi-agent productivity (23:01) Model selection tradeoffs (29:11) Trusting AI outputs (31:28) Missing links today (34:37) Agent orchestration future (38:02) Training agents from work (38:20) Outro
38:58

🚨NEW EPISODE: AI Is Changing How We Work with Crypto Data🚨 In today's episode, we're joined by Kofi to discuss how AI agents are fundamentally changing crypto data analysis, research, and engineering workflows. We discuss: - The evolution from manual coding to AI-assisted development - How MCPs unlock onchain data exploration - Using Herd MCP to analyze smart contracts - AI agents for protocol research and data engineering - Context windows, planning, and agent workflows - Cursor vs OpenCode vs Claude Code (Anthropic) - Managing multiple agents simultaneously - Model selection, costs, and productivity tradeoffs - Building internal AI knowledge bases - Agent orchestration and autonomous workflows - Training agents to replicate human expertise - The future of AI-powered crypto analytics - And much more—enjoy! — Timestamps: (00:00) Introduction (01:24) AI replaces frontends (03:24) Herd MCP demo (05:40) Exploring contracts with AI (08:06) Exploration, planning, execution (11:38) Investigating onchain activity (17:10) Managing agent workflows (20:20) Multi-agent productivity (23:01) Model selection tradeoffs (29:11) Trusting AI outputs (31:28) Missing links today (34:37) Agent orchestration future (38:02) Training agents from work (38:20) Outro

Indexed Podcast

10,562 görüntüleme • 2 ay önce

Today we are launching the Hercules MCP. It is probably the craziest thing I have ever built - Hercules makes it easy to build apps and websites by chatting with AI - Hercules MCP makes it easy to do this at 100x the scale The Hercules MCP quite literally enables you to build 100 websites, purchase 100 domains, and publish all of them with just one prompt. It takes ~5 minutes. It's the best SEO-maxxing strategy for local businesses. Here is how some of our top customers have used it: - A plumber in the Netherlands created 4,000 unique websites for his business, one for every city in the Netherlands - An equipment wholesaler in Tennessee made ~100 unique websites, one for every product they sell A lot of these websites are already ranking #1 on Google To do this yourself: 1. Go to your favourite AI chat app (ChatGPT, Claude, Grok, etc) 2. Add the Hercules MCP (link in comment) 3. Ask Hercules to build 100 websites for whatever you'd like We are the only AI App Builder or coding agent that can build and publish websites at this scale. Enjoy!
0:28

Today we are launching the Hercules MCP. It is probably the craziest thing I have ever built - Hercules makes it easy to build apps and websites by chatting with AI - Hercules MCP makes it easy to do this at 100x the scale The Hercules MCP quite literally enables you to build 100 websites, purchase 100 domains, and publish all of them with just one prompt. It takes ~5 minutes. It's the best SEO-maxxing strategy for local businesses. Here is how some of our top customers have used it: - A plumber in the Netherlands created 4,000 unique websites for his business, one for every city in the Netherlands - An equipment wholesaler in Tennessee made ~100 unique websites, one for every product they sell A lot of these websites are already ranking #1 on Google To do this yourself: 1. Go to your favourite AI chat app (ChatGPT, Claude, Grok, etc) 2. Add the Hercules MCP (link in comment) 3. Ask Hercules to build 100 websites for whatever you'd like We are the only AI App Builder or coding agent that can build and publish websites at this scale. Enjoy!

Brendan Falk

21,688 görüntüleme • 2 ay önce

A third of Palantir's PMs go on to start their own company, and their alumni have gone on to start nine unicorns—the highest rate of any company in the world other than PayPal. I spoke with Nabeel S. Qureshi to understand why. Nabeel spent nearly eight years at Palantir, working as a forward-deployed engineer. His work at Palantir ranged from accelerating the COVID-19 response to applying AI to drug discovery to optimizing aircraft manufacturing at Airbus. He's also a founder, writer, researcher, and visiting scholar of AI policy at the Mercatus Center (alongside tylercowen). In our conversation, we discuss: 🔸 How the “forward-deployed engineer” model works and why it creates exceptional product leaders 🔸 How Palantir transformed from a “sparkling Accenture” into a $200 billion data/software platform company with more than 80% margins 🔸 The unconventional hiring approach that screens for independent-minded, intellectually curious, and highly competitive people 🔸 Why the company intentionally avoids traditional titles and career ladders—and what they do instead 🔸 Why they built an ontology-first data platform that LLMs love 🔸 How Palantir’s controversial “bat signal” recruiting strategy filtered for specific talent types 🔸 The moral case for working at a company like Palantir 🔸 Much more Listen now 👇 • YouTube: • Spotify: • Apple: Thank you to our wonderful sponsors for supporting the podcast: 🏆 WorkOS—Modern identity platform for B2B SaaS, free up to 1 million MAUs: 🏆 Attio—The powerful, flexible CRM for fast-growing startups: 🏆 OneSchema—Import CSV data 10x faster:
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A third of Palantir's PMs go on to start their own company, and their alumni have gone on to start nine unicorns—the highest rate of any company in the world other than PayPal. I spoke with Nabeel S. Qureshi to understand why. Nabeel spent nearly eight years at Palantir, working as a forward-deployed engineer. His work at Palantir ranged from accelerating the COVID-19 response to applying AI to drug discovery to optimizing aircraft manufacturing at Airbus. He's also a founder, writer, researcher, and visiting scholar of AI policy at the Mercatus Center (alongside tylercowen). In our conversation, we discuss: 🔸 How the “forward-deployed engineer” model works and why it creates exceptional product leaders 🔸 How Palantir transformed from a “sparkling Accenture” into a $200 billion data/software platform company with more than 80% margins 🔸 The unconventional hiring approach that screens for independent-minded, intellectually curious, and highly competitive people 🔸 Why the company intentionally avoids traditional titles and career ladders—and what they do instead 🔸 Why they built an ontology-first data platform that LLMs love 🔸 How Palantir’s controversial “bat signal” recruiting strategy filtered for specific talent types 🔸 The moral case for working at a company like Palantir 🔸 Much more Listen now 👇 • YouTube: • Spotify: • Apple: Thank you to our wonderful sponsors for supporting the podcast: 🏆 WorkOS—Modern identity platform for B2B SaaS, free up to 1 million MAUs: 🏆 Attio—The powerful, flexible CRM for fast-growing startups: 🏆 OneSchema—Import CSV data 10x faster:

Lenny Rachitsky

133,297 görüntüleme • 1 yıl önce

Introducing: AI agents that ship product videos whenever you ship features. Engineering teams today are releasing product updates faster than ever before. But creating videos for every new release still takes weeks. Now, whenever you ship a feature to your software, Clueso deploys a team of AI agents to create launch videos, product demos, help tutorials, and more. Content can finally ship as quickly as code. Get access at:
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Introducing: AI agents that ship product videos whenever you ship features. Engineering teams today are releasing product updates faster than ever before. But creating videos for every new release still takes weeks. Now, whenever you ship a feature to your software, Clueso deploys a team of AI agents to create launch videos, product demos, help tutorials, and more. Content can finally ship as quickly as code. Get access at:

Akash Anand

47,556 görüntüleme • 1 ay önce

While your team is just getting started vibe coding prototypes, the team at Stripe is vibe coding a full vibe coding platform. Owen Williams ⚡ is a design manager at Stripe who built Protodash - an internal AI prototyping tool that lets designers and PMs spin up real, clickable prototypes in minutes. In this ep he walks through: - why generic AI tools produce "blurple slop" that doesn't match your design system - how he built a full prototyping studio on top of dev boxes with cursor + cc - why more PMs than designers now use Protodash - the design review mode that lets teams ship feedback direct in the app Plus, we talk about getting to the ultimate dream: demos, not memos. ty to our sponsors! 🧠 CESAR - Intelligent automation built for AI 💻 Cursor - The best way to code with AI Full episode on yt:
0:41

While your team is just getting started vibe coding prototypes, the team at Stripe is vibe coding a full vibe coding platform. Owen Williams ⚡ is a design manager at Stripe who built Protodash - an internal AI prototyping tool that lets designers and PMs spin up real, clickable prototypes in minutes. In this ep he walks through: - why generic AI tools produce "blurple slop" that doesn't match your design system - how he built a full prototyping studio on top of dev boxes with cursor + cc - why more PMs than designers now use Protodash - the design review mode that lets teams ship feedback direct in the app Plus, we talk about getting to the ultimate dream: demos, not memos. ty to our sponsors! 🧠 CESAR - Intelligent automation built for AI 💻 Cursor - The best way to code with AI Full episode on yt:

claire vo 🖤

92,220 görüntüleme • 4 ay önce

🚨 New Feature in OctoMCP: AI Audits Are Live! OctoMCP now supports AI-powered audits for Generated Solana programs! Use the generate-AI-Audit tool to perform automated audits using the LLM configured in your MCP host. 🔍 What it does: Supports 3 audit types: basic, comprehensive, and security-focused Analyzes your program’s source code and IDL Detects critical, high, medium, low, and informational issues Reports code metrics like lines of code, functions, complexity, and nesting depth Provides security best practices and actionable recommendations Includes program context like name, instructions, accounts, and types Generates a clean, structured Markdown audit report 🚧 What’s coming next: We’re working on major updates including: AI Fuzzer Functions using open-source Solana fuzzing frameworks AI Testing Kit to auto-generate test files and validate your programs Octobuild – Build everything right in the browser, 3× faster than OctoMCP, no MCP setup required 🚀 Start vibe coding Solana Dapps + programs today! Deployed Piggybank Program:
2:49

🚨 New Feature in OctoMCP: AI Audits Are Live! OctoMCP now supports AI-powered audits for Generated Solana programs! Use the generate-AI-Audit tool to perform automated audits using the LLM configured in your MCP host. 🔍 What it does: Supports 3 audit types: basic, comprehensive, and security-focused Analyzes your program’s source code and IDL Detects critical, high, medium, low, and informational issues Reports code metrics like lines of code, functions, complexity, and nesting depth Provides security best practices and actionable recommendations Includes program context like name, instructions, accounts, and types Generates a clean, structured Markdown audit report 🚧 What’s coming next: We’re working on major updates including: AI Fuzzer Functions using open-source Solana fuzzing frameworks AI Testing Kit to auto-generate test files and validate your programs Octobuild – Build everything right in the browser, 3× faster than OctoMCP, no MCP setup required 🚀 Start vibe coding Solana Dapps + programs today! Deployed Piggybank Program:

OctonetAI

30,888 görüntüleme • 1 yıl önce