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Announcing Grain DDL: code generation by and for demanding engine developers. Define your structs and data once. Write custom generators for protocols, save files, language interop, shaders, databases, more. No macros, no metaprogramming. Generate reviewable code on every keystroke. 300kB compiler exe. Windows, Mac, Linux. Closed beta applications are...

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Michael Labbé

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14,273 次观看 • 3 个月前 •via X (Twitter)

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An AI assistant for Google Earth Engine is now available in QGIS! You can explore and visualize any dataset from the 80+ PB Earth Engine Data Catalog using natural language, and run scalable geospatial analysis on demand without writing code. Every interaction automatically generates reusable code, making it easy to reproduce results, customize workflows, and transition from no-code to full scripting when needed. Upgrade the plugin to get started and bring AI-powered geospatial analytics directly into your QGIS workflow. GitHub: QGIS plugin: GeoAgent: #EarthEngine #QGIS #OpenSource #GeoAI #Geospatial
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An AI assistant for Google Earth Engine is now available in QGIS! You can explore and visualize any dataset from the 80+ PB Earth Engine Data Catalog using natural language, and run scalable geospatial analysis on demand without writing code. Every interaction automatically generates reusable code, making it easy to reproduce results, customize workflows, and transition from no-code to full scripting when needed. Upgrade the plugin to get started and bring AI-powered geospatial analytics directly into your QGIS workflow. GitHub: QGIS plugin: GeoAgent: #EarthEngine #QGIS #OpenSource #GeoAI #Geospatial

Qiusheng Wu

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This is Scene Editor. Running on Flutter 3.47 stable. Flutter is excellent for building serious 3D desktop apps. Powered entirely by Flutter's built-in graphics stack, Flutter GPU and Impeller. No forks, no platform views, no external rendering contexts. Scene Editor is just a vanilla Flutter application. Build 3D apps for macOS, Linux, Windows, iOS, Android, Web, and custom embedders. Non-destructive importing, overrides on nested prefabs, live material and shader editing, custom gizmos, and component inspectors you define with property annotations. It watches the filesystem, and custom components you write become instantly available in the editor upon saving. Configure, build, and run your live app without leaving it. Flutter is now 3D.
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This is Scene Editor. Running on Flutter 3.47 stable. Flutter is excellent for building serious 3D desktop apps. Powered entirely by Flutter's built-in graphics stack, Flutter GPU and Impeller. No forks, no platform views, no external rendering contexts. Scene Editor is just a vanilla Flutter application. Build 3D apps for macOS, Linux, Windows, iOS, Android, Web, and custom embedders. Non-destructive importing, overrides on nested prefabs, live material and shader editing, custom gizmos, and component inspectors you define with property annotations. It watches the filesystem, and custom components you write become instantly available in the editor upon saving. Configure, build, and run your live app without leaving it. Flutter is now 3D.

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The next generation of mobile apps will run multimodal AI locally by default. Today, we’re making it practical for developers to ship. We just launched NexaSDK for Mobile on Product Hunt. Developers can run the latest multimodal AI models fully on-device in iOS & Android apps with Apple Neural Engine and Qualcomm Hexagon NPU acceleration. In just 3 lines of code, build chat, multimodal, search, and audio features with no cloud cost, complete privacy, 2x faster speed and 9× better energy efficiency. Try out NexaSDK for Mobile and we’d love your feedback (Product Hunt link in thread).

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🚀 Today, we are thrilled to share that Amazon Q is now generally available. ◼Amazon Q is the most capable generative AI-powered assistant for accelerating software development and leveraging companies’ internal data. It eliminates tedious work for developers and employees across organizations. ◼Q helps to test, debug and write code, and has the highest reported code acceptance rates in the industry, for assistants that perform multi-line code suggestions. BT Group recently reported they accepted 37% of Q’s code suggestions and National Australia Bank reported a 50% acceptance rate. ◼Amazon Q Developer Agents can autonomously perform a range of tasks—everything from implementing features, documenting, and refactoring code, to performing software upgrades. Developers can ask Amazon Q to implement an application feature, and the agent will analyze their existing application code and generate a step-by-step implementation plan. ◼Amazon Q's capabilities extend beyond coding. It also allows employees to easily get insight from their company's internal data that is spread across multiple documents, systems, and applications. Q connects all these siloed sources and can answer questions, provide summaries, analyze trends, and generate content. ◼We're also introducing Q Apps, a powerful new way for anyone to create generative AI apps based on their organization's data—no prior coding experience required. Simply describe the app you need in natural language, and Q Apps will build it for you. This unlocks endless possibilities for teams to automate workflows and daily tasks. Customers across industries are using Amazon Q to transform the way they work. I'm incredibly excited to see what Q can do for you.
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🚀 Today, we are thrilled to share that Amazon Q is now generally available. ◼Amazon Q is the most capable generative AI-powered assistant for accelerating software development and leveraging companies’ internal data. It eliminates tedious work for developers and employees across organizations. ◼Q helps to test, debug and write code, and has the highest reported code acceptance rates in the industry, for assistants that perform multi-line code suggestions. BT Group recently reported they accepted 37% of Q’s code suggestions and National Australia Bank reported a 50% acceptance rate. ◼Amazon Q Developer Agents can autonomously perform a range of tasks—everything from implementing features, documenting, and refactoring code, to performing software upgrades. Developers can ask Amazon Q to implement an application feature, and the agent will analyze their existing application code and generate a step-by-step implementation plan. ◼Amazon Q's capabilities extend beyond coding. It also allows employees to easily get insight from their company's internal data that is spread across multiple documents, systems, and applications. Q connects all these siloed sources and can answer questions, provide summaries, analyze trends, and generate content. ◼We're also introducing Q Apps, a powerful new way for anyone to create generative AI apps based on their organization's data—no prior coding experience required. Simply describe the app you need in natural language, and Q Apps will build it for you. This unlocks endless possibilities for teams to automate workflows and daily tasks. Customers across industries are using Amazon Q to transform the way they work. I'm incredibly excited to see what Q can do for you.

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Exciting update on PantheonOS: Introducing Pantheon-Notebook & Pantheon-CLI — the first fully open-source, Python-based agentic tools that go beyond Claude Code in the field of data analysis. Pantheon-CLI runs entirely on your computer or server, supports 60+ tools and 50+ databases, and can call any Python, R, or Julia package alongside natural language. Chat with your data directly. It look like python-claude-code, but more appreciate for data analysis. Pantheon-Notebook brings the same agentic framework into Jupyter! Not just for writing code, it can also run and revise code automatically to generate the correct result, and even operate on files and study from website — beyond what any other tool can do! With Pantheon, you mix natural language + programming in one workflow, focusing on discovery instead of syntax barriers. We've applied Pantheon in some real-world cases: finance (customer explore), biology (Seurat, cell segmentation, annotation), sociology (survey analysis), and drug discovery (molecular docking). Pantheon is not just a CLI or a plugin — it's an agentic operating system for science, spanning both terminal and notebook. Why not try it now? We are actively preparing publications from this series of projects. Major contributors will be recognized in our GitHub repository and listed as key authors in these manuscripts. Feel free to reach out for collaborations, research assistant positions, visiting opportunities, rotation project or future PhD projects.

evo-devo

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English is the most powerful language in the world. MongoDB just added support for MCP, and literally anyone can now query data without knowing anything about databases. If you know English, you are all set. I recorded a quick video to show you how I connect to a sample Airbnb database and run different queries: • How many listings? • How many listings in the US? • What's the list of countries in these listings? It takes 10 seconds to configure Claude, Cursor, WindSurf, or any other AI assistant to connect to MongoDB's MCP Server. By the way, the server supports much more than queries: • You can explore your collections • You can fetch schema information • You can generate app code snippets • You can manage your databases • You can handle cluster/user/admin tasks Here is a link to the MCP server GitHub repository: This is huge for developers. It's even bigger for non-developers. Thanks to the MongoDB team for collaborating with me on this post.

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44,855 次观看 • 1 年前

🏥 Launch Your Own Medical Clinic App – No Code Needed! Doctors, healthcare professionals, and clinic owners—streamline your appointment system with your own custom medical booking app! With our dApp Builder, you can create a cross-platform clinic app in minutes—no coding required. ✅ Accept Online Appointments & Manage Patients ✅ Cross-Platform by Default – Android, iOS, Web, Windows, Mac, Linux ✅ Decentralized & Secure – Built on #ION for direct, private transactions Say goodbye to expensive scheduling platforms—own your booking system, set your own rules, and offer seamless patient care. 🩺 The future of medical booking is here. Ready to build?
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🏥 Launch Your Own Medical Clinic App – No Code Needed! Doctors, healthcare professionals, and clinic owners—streamline your appointment system with your own custom medical booking app! With our dApp Builder, you can create a cross-platform clinic app in minutes—no coding required. ✅ Accept Online Appointments & Manage Patients ✅ Cross-Platform by Default – Android, iOS, Web, Windows, Mac, Linux ✅ Decentralized & Secure – Built on #ION for direct, private transactions Say goodbye to expensive scheduling platforms—own your booking system, set your own rules, and offer seamless patient care. 🩺 The future of medical booking is here. Ready to build?

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🍰 Launch Your Own Sweet Shop & Bakery App – No Code Needed! Bakers, confectioners, and dessert makers—it’s time to take your sweet business online with a custom app! With our dApp Builder, you can create a cross-platform sweet shop app in minutes—no coding required. ✅ Sell Cakes, Pastries, Chocolates & More – Directly to Customers ✅ Cross-Platform by Default – Android, iOS, Web, Windows, Mac, Linux ✅ Decentralized & Secure – Built on #ION for seamless orders & payments Forget marketplace restrictions—own your storefront, set your prices, and let customers order sweets anytime, anywhere. 🎂 The future of dessert e-commerce is delicious. Ready to build?

Ice Open Network

37,554 次观看 • 1 年前

🍕 Launch Your Own Pizzeria App – No Code Needed! Pizzeria owners and pizza lovers—bring your restaurant online with a custom app! With our dApp Builder, you can create a cross-platform pizza ordering app in minutes—no coding required. ✅ Sell Pizzas, Sides, Drinks & More – Directly to Customers ✅ Cross-Platform by Default – Android, iOS, Web, Windows, Mac, Linux ✅ Decentralized & Secure – Built on #ION for fast, fee-free transactions Say goodbye to food delivery platforms taking a big cut—own your ordering system, offer exclusive deals, and build customer loyalty. 🔥 The future of pizza delivery is here. Ready to build?
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🍕 Launch Your Own Pizzeria App – No Code Needed! Pizzeria owners and pizza lovers—bring your restaurant online with a custom app! With our dApp Builder, you can create a cross-platform pizza ordering app in minutes—no coding required. ✅ Sell Pizzas, Sides, Drinks & More – Directly to Customers ✅ Cross-Platform by Default – Android, iOS, Web, Windows, Mac, Linux ✅ Decentralized & Secure – Built on #ION for fast, fee-free transactions Say goodbye to food delivery platforms taking a big cut—own your ordering system, offer exclusive deals, and build customer loyalty. 🔥 The future of pizza delivery is here. Ready to build?

Ice Open Network

43,634 次观看 • 1 年前

Holy Sh*t... You can now share your localhost with anyone using only VS Code! 🤯 VS Code has a built-in Ports feature that lets you expose your local server to the internet, no need for third-party tools. Here’s how to use it: 1) Open the Ports tab in the terminal panel 2) Click Forward a Port 3) Enter your local port number (mine was 5173, yours could be 3000, 3001, etc.) 4) VS Code will generate a link, right-click and select Make Public 5) Copy the link and share it with anyone Perfect for demos, testing on other devices, or sharing work with clients and teammates :) Watch the video for a step-by-step demo 🎥 Follow me for more amazing AI, Coding & Web Dev insights 💎
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Holy Sh*t... You can now share your localhost with anyone using only VS Code! 🤯 VS Code has a built-in Ports feature that lets you expose your local server to the internet, no need for third-party tools. Here’s how to use it: 1) Open the Ports tab in the terminal panel 2) Click Forward a Port 3) Enter your local port number (mine was 5173, yours could be 3000, 3001, etc.) 4) VS Code will generate a link, right-click and select Make Public 5) Copy the link and share it with anyone Perfect for demos, testing on other devices, or sharing work with clients and teammates :) Watch the video for a step-by-step demo 🎥 Follow me for more amazing AI, Coding & Web Dev insights 💎

Ram Maheshwari

43,070 次观看 • 1 个月前

𝗢𝗹𝗹𝗮𝗺𝗮 + 𝗖𝗹𝗮𝘂𝗱𝗲 𝗖𝗼𝗱𝗲 𝗷𝘂𝘀𝘁 𝗺𝗮𝗱𝗲 𝗔𝗜 𝗰𝗼𝗱𝗶𝗻𝗴 𝗳𝗿𝗲𝗲. 𝗔𝗻𝗱 𝗶𝘁 𝗿𝘂𝗻𝘀 𝗰𝗼𝗺𝗽𝗹𝗲𝘁𝗲𝗹𝘆 𝗹𝗼𝗰𝗮𝗹. No subscriptions. No limits. No data leaving your machine. Claude Code used to cost $3-$15 per million tokens. Now you can run it with free open-source models on your computer. January 16th, 2026: Ollama version 0.14.0 became compatible with Anthropic's messages API. That means Claude Code now works with any Ollama model. Zero ongoing costs. Your code never leaves your computer. Here's the setup: Download Ollama. Run `ollama pull qwen3-coder`. Install Claude Code. Set two environment variables to connect them. Then run: `claude --model qwen3-coder` Give it tasks in plain English: "Write a function to process images." "Debug why my API calls are failing." It reads your files. Makes changes. Tests the code. Shows you what it did. Top models: Qwen 3-Coder for everyday tasks. GPT-OSS 20B for complex projects. This is completely legal. Explicitly supported by both tools.
9:06

𝗢𝗹𝗹𝗮𝗺𝗮 + 𝗖𝗹𝗮𝘂𝗱𝗲 𝗖𝗼𝗱𝗲 𝗷𝘂𝘀𝘁 𝗺𝗮𝗱𝗲 𝗔𝗜 𝗰𝗼𝗱𝗶𝗻𝗴 𝗳𝗿𝗲𝗲. 𝗔𝗻𝗱 𝗶𝘁 𝗿𝘂𝗻𝘀 𝗰𝗼𝗺𝗽𝗹𝗲𝘁𝗲𝗹𝘆 𝗹𝗼𝗰𝗮𝗹. No subscriptions. No limits. No data leaving your machine. Claude Code used to cost $3-$15 per million tokens. Now you can run it with free open-source models on your computer. January 16th, 2026: Ollama version 0.14.0 became compatible with Anthropic's messages API. That means Claude Code now works with any Ollama model. Zero ongoing costs. Your code never leaves your computer. Here's the setup: Download Ollama. Run `ollama pull qwen3-coder`. Install Claude Code. Set two environment variables to connect them. Then run: `claude --model qwen3-coder` Give it tasks in plain English: "Write a function to process images." "Debug why my API calls are failing." It reads your files. Makes changes. Tests the code. Shows you what it did. Top models: Qwen 3-Coder for everyday tasks. GPT-OSS 20B for complex projects. This is completely legal. Explicitly supported by both tools.

Julian Goldie SEO

168,725 次观看 • 7 个月前

Nobody is writing 90% of their code using AI. Here's the uncomfortable truth: The real productivity gain from using AI to write code is closer to 10%, nowhere near the 90% people claim. Sundar Pichai said in 2024 that 30% of the new code at Google was AI-generated. However, he went on to admit, during Lex Friedman's podcast, that engineering velocity had only increased by about 10%. AI-generated code isn't free code. It still has to be reviewed, tested, and made production-ready. Optimizing a single step (code generation) doesn't boost output if bottlenecks shift elsewhere (code reviews). It doesn't matter how much code you generate if you can't keep up the review process. The solution: Automate as much as you can the review and verification of your code. I'm working with Sonar, who is sponsoring this post, and they will take care of the code quality and security analysis of your code: • They review over 300B lines of code every single day • They cover reliability, security, and maintainability for your code • You can integrate them into your CI/CD pipeline • You can install them in your IDE (I use their VSCode extension) • Support for more than 30 languages Here is a link so you can check them out:
4:42

Nobody is writing 90% of their code using AI. Here's the uncomfortable truth: The real productivity gain from using AI to write code is closer to 10%, nowhere near the 90% people claim. Sundar Pichai said in 2024 that 30% of the new code at Google was AI-generated. However, he went on to admit, during Lex Friedman's podcast, that engineering velocity had only increased by about 10%. AI-generated code isn't free code. It still has to be reviewed, tested, and made production-ready. Optimizing a single step (code generation) doesn't boost output if bottlenecks shift elsewhere (code reviews). It doesn't matter how much code you generate if you can't keep up the review process. The solution: Automate as much as you can the review and verification of your code. I'm working with Sonar, who is sponsoring this post, and they will take care of the code quality and security analysis of your code: • They review over 300B lines of code every single day • They cover reliability, security, and maintainability for your code • You can integrate them into your CI/CD pipeline • You can install them in your IDE (I use their VSCode extension) • Support for more than 30 languages Here is a link so you can check them out:

Santiago

296,637 次观看 • 11 个月前

For a long time I've been teaching a self-extending design system to generate aerospace hardware from pure physics no CAD, just code and constraints. Tonight I hooked my CEM up to Fusion 360 via MCP after a design and it rebuilt it! Real feature trees a machinist can open, edit, and cut toolpaths from. The system that designs in code can now speak the language of every shop floor on Earth. So to answer if you can transfer your LEAP 71 work to CAD. Yes, you can.
0:26

For a long time I've been teaching a self-extending design system to generate aerospace hardware from pure physics no CAD, just code and constraints. Tonight I hooked my CEM up to Fusion 360 via MCP after a design and it rebuilt it! Real feature trees a machinist can open, edit, and cut toolpaths from. The system that designs in code can now speak the language of every shop floor on Earth. So to answer if you can transfer your LEAP 71 work to CAD. Yes, you can.

Dylan Small

15,054 次观看 • 1 个月前

No human is reading your resume. An algorithm trashes it in 6 seconds and you never even know you got buried. This guy got sick of feeding that meat grinder by hand. So he unleashed KIMI K2.6 Agent Swarm, hundreds of agents tailoring his resume for EVERY single job posting at once. More done in one evening than he used to do in a whole week. And then the real replies started flooding in. Save this post before it gets buried. If you’re job hunting right now this is your cheat code.
0:41

No human is reading your resume. An algorithm trashes it in 6 seconds and you never even know you got buried. This guy got sick of feeding that meat grinder by hand. So he unleashed KIMI K2.6 Agent Swarm, hundreds of agents tailoring his resume for EVERY single job posting at once. More done in one evening than he used to do in a whole week. And then the real replies started flooding in. Save this post before it gets buried. If you’re job hunting right now this is your cheat code.

shmidt

16,392 次观看 • 3 个月前

🚨 Electrical engineers are going to hate this. Someone just turned React into a circuit board factory. Write code. Get a real PCB manufactured and delivered to your door. It's called tscircuit. React for Electronics. No Altium. No $10,000/year licenses. No 6-month learning curve. You write React components. But instead of and , you write , , and . The same way you build a website. That's how you build a circuit board now. Here's what this thing actually does: → Design real circuit boards using TypeScript and React → Edit code in your IDE, watch the circuit update in real time → Auto-generates schematics, PCB layouts, and 3D previews from your code → Automatic part selection and bill of materials generation → Built-in autorouting algorithm for PCB traces → Export to Gerber files and send directly to a manufacturer → Online playground. Design circuits in your browser right now. Here's the wildest part: The creator wrote 40 lines of TypeScript. From that he got a full PCB, a schematic, and a 3D preview. Then he exported it, sent it to a manufacturer, and got a real working circuit board delivered. 40 lines of code. A real physical product. This is free. Write React. Get hardware. $20K+ in bounties already paid to contributors. 8 years in the making. 100% Open Source. MIT License.
3:42

🚨 Electrical engineers are going to hate this. Someone just turned React into a circuit board factory. Write code. Get a real PCB manufactured and delivered to your door. It's called tscircuit. React for Electronics. No Altium. No $10,000/year licenses. No 6-month learning curve. You write React components. But instead of and , you write , , and . The same way you build a website. That's how you build a circuit board now. Here's what this thing actually does: → Design real circuit boards using TypeScript and React → Edit code in your IDE, watch the circuit update in real time → Auto-generates schematics, PCB layouts, and 3D previews from your code → Automatic part selection and bill of materials generation → Built-in autorouting algorithm for PCB traces → Export to Gerber files and send directly to a manufacturer → Online playground. Design circuits in your browser right now. Here's the wildest part: The creator wrote 40 lines of TypeScript. From that he got a full PCB, a schematic, and a 3D preview. Then he exported it, sent it to a manufacturer, and got a real working circuit board delivered. 40 lines of code. A real physical product. This is free. Write React. Get hardware. $20K+ in bounties already paid to contributors. 8 years in the making. 100% Open Source. MIT License.

Nav Toor

381,057 次观看 • 5 个月前

Your agents can't keep up with real-time data. Especially when it's scattered across dozens of sources. Most teams waste weeks building custom connectors for every database, API, and data warehouse. Then they build ETL pipelines to sync everything. By the time your agent retrieves the data, it's already outdated. Picture this: Your Postgres database updated 5 minutes ago. Your MongoDB collection changed 2 minutes ago. Your agent is still pulling from yesterday's snapshot. This is why most production RAG systems fail. There's a better approach: MindsDB is an open-source AI platform with a federated data engine that lets you query multiple data sources in real-time using SQL - without moving any data. Here's what makes it different: ↳ Your data stays in place. No ETL pipelines or data duplication ↳ Query Postgres, MongoDB, REST APIs, and more using consistent SQL ↳ JOIN across different sources in real-time with a unified interface ↳ Works with both structured and un-structured data And here's the best part: You don't even need to write SQL. Just describe what you want in plain English, and MindsDB converts it to SQL automatically. The system does all the heavy lifting. The breakthrough for AI agents is simple: When data updates at the source, your agent gets fresh results immediately. No sync delays. No stale embeddings. No custom code for each integration. You can literally write a SQL query that joins a Postgres table with a MongoDB collection and gets live results. This is what production AI applications need but rarely get. In this video, I give you a complete walkthrough of what we just discussed and how to actually do it. Make sure you watch this till the end. I've shared the link to MindsDB's GitHub repo in the next tweet!
9:28

Your agents can't keep up with real-time data. Especially when it's scattered across dozens of sources. Most teams waste weeks building custom connectors for every database, API, and data warehouse. Then they build ETL pipelines to sync everything. By the time your agent retrieves the data, it's already outdated. Picture this: Your Postgres database updated 5 minutes ago. Your MongoDB collection changed 2 minutes ago. Your agent is still pulling from yesterday's snapshot. This is why most production RAG systems fail. There's a better approach: MindsDB is an open-source AI platform with a federated data engine that lets you query multiple data sources in real-time using SQL - without moving any data. Here's what makes it different: ↳ Your data stays in place. No ETL pipelines or data duplication ↳ Query Postgres, MongoDB, REST APIs, and more using consistent SQL ↳ JOIN across different sources in real-time with a unified interface ↳ Works with both structured and un-structured data And here's the best part: You don't even need to write SQL. Just describe what you want in plain English, and MindsDB converts it to SQL automatically. The system does all the heavy lifting. The breakthrough for AI agents is simple: When data updates at the source, your agent gets fresh results immediately. No sync delays. No stale embeddings. No custom code for each integration. You can literally write a SQL query that joins a Postgres table with a MongoDB collection and gets live results. This is what production AI applications need but rarely get. In this video, I give you a complete walkthrough of what we just discussed and how to actually do it. Make sure you watch this till the end. I've shared the link to MindsDB's GitHub repo in the next tweet!

Akshay 🚀

65,672 次观看 • 9 个月前

8 rules to improve your AI coding agent. All of these rules work with Claude Code, Cursor, VS Code, and with most programming languages. Automating these rules will 10x the code quality and security produced by your AI coding agents. 1. Dependency checks - Prevent your agent from suggesting insecure libraries based on outdated training data. 2. Secret exposure - Auto-fix the use of hardcoded credentials introduced by your coding agent. 3. File and function size - Automatically refactor any files or functions that exceed a reasonable length. 4. Complexity and parameter limits - Simplify overly complex code written by the agent. 5. SQL Injection - Auto-fix all database interactions with unsanitized user input. 6. Unused variables and imports - Detect and remove dead code. 7. Detect invisible unicode characters in AI rules files - Remove zero-width spaces, direction overrides, and other invisible characters that can hide malicious behavior. 8. Insecure OpenAI API usage - Enforce use of secure OpenAI endpoints, proper authentication, and context isolation Here is how you can automate this: Install the Codacy extension. This will give you access to a CLI for local scanning and an MCP server for agent communication. From here on out, every time you need to generate some code: 1. Your agent will write the code 2. It will then call Codacy's CLI to check it 3. It will find any issues in real time 4. Your coding agent will fix the issues 5. When the code passes all checks, you are done Level of effort on your side: literally zero! Code quality and security because of this: 100x better! Here is the link to download the extension for your IDE: Thanks to the Codacy team for collaborating with me on this post.
3:50

8 rules to improve your AI coding agent. All of these rules work with Claude Code, Cursor, VS Code, and with most programming languages. Automating these rules will 10x the code quality and security produced by your AI coding agents. 1. Dependency checks - Prevent your agent from suggesting insecure libraries based on outdated training data. 2. Secret exposure - Auto-fix the use of hardcoded credentials introduced by your coding agent. 3. File and function size - Automatically refactor any files or functions that exceed a reasonable length. 4. Complexity and parameter limits - Simplify overly complex code written by the agent. 5. SQL Injection - Auto-fix all database interactions with unsanitized user input. 6. Unused variables and imports - Detect and remove dead code. 7. Detect invisible unicode characters in AI rules files - Remove zero-width spaces, direction overrides, and other invisible characters that can hide malicious behavior. 8. Insecure OpenAI API usage - Enforce use of secure OpenAI endpoints, proper authentication, and context isolation Here is how you can automate this: Install the Codacy extension. This will give you access to a CLI for local scanning and an MCP server for agent communication. From here on out, every time you need to generate some code: 1. Your agent will write the code 2. It will then call Codacy's CLI to check it 3. It will find any issues in real time 4. Your coding agent will fix the issues 5. When the code passes all checks, you are done Level of effort on your side: literally zero! Code quality and security because of this: 100x better! Here is the link to download the extension for your IDE: Thanks to the Codacy team for collaborating with me on this post.

Santiago

49,331 次观看 • 10 个月前

I'm teaching a new course! AI Python for Beginners is a series of four short courses that teach anyone to code, regardless of current technical skill. We are offering these courses free for a limited time. Generative AI is transforming coding. This course teaches coding in a way that’s aligned with where the field is going, rather than where it has been: (1) AI as a Coding Companion. Experienced coders are using AI to help write snippets of code, debug code, and the like. We embrace this approach and describe best-practices for coding with a chatbot. Throughout the course, you'll have access to an AI chatbot that will be your own coding companion that can assist you every step of the way as you code. (2) Learning by Building AI Applications. You'll write code that interacts with large language models to quickly create fun applications to customize poems, write recipes, and manage a to-do list. This hands-on approach helps you see how writing code that calls on powerful AI models will make you more effective in your work and personal projects. With this approach, beginning programmers can learn to do useful things with code far faster than they could have even a year ago. Knowing a little bit of coding is increasingly helping people in job roles other than software engineers. For example, I've seen a marketing professional write code to download web pages and use generative AI to derive insights; a reporter write code to flag important stories; and an investor automate the initial drafts of contracts. With this course you’ll be equipped to automate repetitive tasks, analyze data more efficiently, and leverage AI to enhance your productivity. If you are already an experienced developer, please help me spread the word and encourage your non-developer friends to learn a little bit of coding. I hope you'll check out the first two short courses here!
3:40

I'm teaching a new course! AI Python for Beginners is a series of four short courses that teach anyone to code, regardless of current technical skill. We are offering these courses free for a limited time. Generative AI is transforming coding. This course teaches coding in a way that’s aligned with where the field is going, rather than where it has been: (1) AI as a Coding Companion. Experienced coders are using AI to help write snippets of code, debug code, and the like. We embrace this approach and describe best-practices for coding with a chatbot. Throughout the course, you'll have access to an AI chatbot that will be your own coding companion that can assist you every step of the way as you code. (2) Learning by Building AI Applications. You'll write code that interacts with large language models to quickly create fun applications to customize poems, write recipes, and manage a to-do list. This hands-on approach helps you see how writing code that calls on powerful AI models will make you more effective in your work and personal projects. With this approach, beginning programmers can learn to do useful things with code far faster than they could have even a year ago. Knowing a little bit of coding is increasingly helping people in job roles other than software engineers. For example, I've seen a marketing professional write code to download web pages and use generative AI to derive insights; a reporter write code to flag important stories; and an investor automate the initial drafts of contracts. With this course you’ll be equipped to automate repetitive tasks, analyze data more efficiently, and leverage AI to enhance your productivity. If you are already an experienced developer, please help me spread the word and encourage your non-developer friends to learn a little bit of coding. I hope you'll check out the first two short courses here!

Andrew Ng

1,225,465 次观看 • 2 年前