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Tested the updated Agnes 2.5-Flash inside Agnes Code on a real Python bug. Through it's multi-reasoning and tool calling, it inspected my local file, found the issue, applied the fix, and verified the result, all from one desktop workspace. If you're looking for an ultra-fast model reasoning in your... show more

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15,351 次观看 • 3 天前 •via X (Twitter)

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most AI APIs either cost too much or lock the best models behind expensive plans. then i came across Agnes AI. it’s one of the few platforms giving developers access to text, image, and video AI models through a single API. their ecosystem gives you direct access to top-tier models like - Agnes-2.0-Flash for text - Agnes-Image-2.0 for image - Agnes-Video-V2.0 for video Instead of managing different providers for different tasks, everything works from one place. what stood out to me: > one API for text, image, and video generation > OpenAI-compatible API, so integration is straightforward > built for speed and scalability > free access for developers to start building > useful for everything from chatbots to image generation and content automation if you’re building AI products, it’s worth taking a look while it’s still flying under the radar. sometimes the biggest advantage is finding great tools before everyone else does. check out Agnes AI here, get free access for developers : and if you’re building with it, join the developer community here: Agnes AI #AgnesAI #AgnesAPI #BuildWithAgnes #MultimodalAI #AIforDevs #DeveloperAPI #AIParity

most AI APIs either cost too much or lock the best models behind expensive plans. then i came across Agnes AI. it’s one of the few platforms giving developers access to text, image, and video AI models through a single API. their ecosystem gives you direct access to top-tier models like - Agnes-2.0-Flash for text - Agnes-Image-2.0 for image - Agnes-Video-V2.0 for video Instead of managing different providers for different tasks, everything works from one place. what stood out to me: > one API for text, image, and video generation > OpenAI-compatible API, so integration is straightforward > built for speed and scalability > free access for developers to start building > useful for everything from chatbots to image generation and content automation if you’re building AI products, it’s worth taking a look while it’s still flying under the radar. sometimes the biggest advantage is finding great tools before everyone else does. check out Agnes AI here, get free access for developers : and if you’re building with it, join the developer community here: Agnes AI #AgnesAI #AgnesAPI #BuildWithAgnes #MultimodalAI #AIforDevs #DeveloperAPI #AIParity

MIKE

14,591 次观看 • 14 天前

Freelance dev rant: Finally stop burning cash on paid closed-source AI Tired of deducting AI fees from my freelance profits? I’ve spent hundreds monthly on premium LLMs for client coding and design work before. A fellow freelancer recommended Agnes, whose benchmark results rank within the global top 10 tier. Agnes AI What’s surprising is the full three-model suite is unlimited free forever via API. Whether I need code bug fixes or custom promotional images for clients, no more per-call fees like Gemini/Claude. Occasionally I organize project brief slides with customers on its collaborative workspace, comments and editing separated neatly. Anyone taking sporadic dev orders really should try this cost-saving option. 🔗 #AgnesAI #Agnes2Flash #FreeAIModel #AIAgent #MultimodalAI #CodingWithAI #DeveloperTools #NoMorePaywalls #AIWorkflow

Freelance dev rant: Finally stop burning cash on paid closed-source AI Tired of deducting AI fees from my freelance profits? I’ve spent hundreds monthly on premium LLMs for client coding and design work before. A fellow freelancer recommended Agnes, whose benchmark results rank within the global top 10 tier. Agnes AI What’s surprising is the full three-model suite is unlimited free forever via API. Whether I need code bug fixes or custom promotional images for clients, no more per-call fees like Gemini/Claude. Occasionally I organize project brief slides with customers on its collaborative workspace, comments and editing separated neatly. Anyone taking sporadic dev orders really should try this cost-saving option. 🔗 #AgnesAI #Agnes2Flash #FreeAIModel #AIAgent #MultimodalAI #CodingWithAI #DeveloperTools #NoMorePaywalls #AIWorkflow

Alif Khan

44,627 次观看 • 1 个月前

BREAKING: Microsoft just launched its own AI model family and the coding model inside GitHub Copilot. MAI-Code-1-Flash. Shipped to every Copilot tier. I just tested it to build an app. Check out the video 👇 85.8% benchmark score. 256K context. 60% token reduction on hard tasks. Here are the other models. → MAI-Code-1-Flash (coding, free) → MAI-Thinking-1 (reasoning, 35B params) → MAI-Image-2.5 (image generation) → MAI-Transcribe-1.5 (speech, 43 languages)

BREAKING: Microsoft just launched its own AI model family and the coding model inside GitHub Copilot. MAI-Code-1-Flash. Shipped to every Copilot tier. I just tested it to build an app. Check out the video 👇 85.8% benchmark score. 256K context. 60% token reduction on hard tasks. Here are the other models. → MAI-Code-1-Flash (coding, free) → MAI-Thinking-1 (reasoning, 35B params) → MAI-Image-2.5 (image generation) → MAI-Transcribe-1.5 (speech, 43 languages)

Priyanka Vergadia

37,018 次观看 • 2 个月前

NVIDIA built the best free AI API platform and nobody's talking about it. 100+ models and no credit card need and best thing is credits don't expire. Meta, Google, DeepSeek, Microsoft all in one place. I was looking for a free reasoning model API for a project and everything was paywalled. Then I found → Pick your model (chat, code, vision, reasoning it's all there) → Click "View Code" → Generate API key → Drop it in your project OpenAI-compatible endpoints with zero billing setup.

NVIDIA built the best free AI API platform and nobody's talking about it. 100+ models and no credit card need and best thing is credits don't expire. Meta, Google, DeepSeek, Microsoft all in one place. I was looking for a free reasoning model API for a project and everything was paywalled. Then I found → Pick your model (chat, code, vision, reasoning it's all there) → Click "View Code" → Generate API key → Drop it in your project OpenAI-compatible endpoints with zero billing setup.

Hasan Toor

18,499 次观看 • 1 个月前

Software Engineering Expectations for 2026 - The majority of your code should be written by AI now - Cursor/Codex/Claude Code/Gemini/etc - You should try all the tooling and switch between them, as each one gets an edge over the others depending on the release cycle. - You should be using AI to check the code that is written by AI - Have AI write tests - Have AI read logs - Have AI navigate your browser - I don't do this every time because sometimes it's simple enough to check it myself - You should still skim code changes - This can be a lighter skim on internal tools and a heavier read through on customer facing code - Use AI to help you define specs

Software Engineering Expectations for 2026 - The majority of your code should be written by AI now - Cursor/Codex/Claude Code/Gemini/etc - You should try all the tooling and switch between them, as each one gets an edge over the others depending on the release cycle. - You should be using AI to check the code that is written by AI - Have AI write tests - Have AI read logs - Have AI navigate your browser - I don't do this every time because sometimes it's simple enough to check it myself - You should still skim code changes - This can be a lighter skim on internal tools and a heavier read through on customer facing code - Use AI to help you define specs

Ben Awad

534,612 次观看 • 7 个月前

CLAUDE CODE JUST GOT EYES Claude Code on desktop can now open and use a real browser, right inside the app. No screenshots, no copy pasting, no separate tools. - It opens docs, designs, or any site next to your code - It clicks, types, and fills forms exactly like a human would - It takes its own screenshots to check if the code actually works - It runs in a clean separate profile, none of your logins touched Your AI coding assistant just stopped being blind.

BuBBliK

49,154 次观看 • 24 天前

I tested a new coding assistant on 34,568 lines of code. (Cursor could not achieve what this tool did.) AI models are improving every day: - Faster inference - Longer context lengths But are AI coding assistants advancing at the same rate? Can they truly understand your entire project? I tested Augment Code on my ai-engineering repo with ~35k lines of code. Augment Code is a powerful AI Assistant built for developers working with large, evolving codebases—needing an assistant that understands the full context of their projects. In the video demo below, I asked it to: - Merge two projects. - Answer a global context question. Here’s what happened: - It understood dependencies across both projects. - It merged them intelligently—without breaking anything. - It even created a README file for the merged project. - It answered my global query instantly, pulling from the full codebase. This is the difference between AI autocomplete and an AI engineer that truly understands your repo. Augment Code is powerful because it indexes your entire repo upfront. This way, it can answer questions instantly, no matter how large your project is. Lastly, Augment Code is fully compatible with VSCode, JetBrains, Vim, Slack, and more. Try them now, I have shared a link in the next tweet! Thanks to Augment Code for showing me their powerful AI coding assistant and working with me on this post.

I tested a new coding assistant on 34,568 lines of code. (Cursor could not achieve what this tool did.) AI models are improving every day: - Faster inference - Longer context lengths But are AI coding assistants advancing at the same rate? Can they truly understand your entire project? I tested Augment Code on my ai-engineering repo with ~35k lines of code. Augment Code is a powerful AI Assistant built for developers working with large, evolving codebases—needing an assistant that understands the full context of their projects. In the video demo below, I asked it to: - Merge two projects. - Answer a global context question. Here’s what happened: - It understood dependencies across both projects. - It merged them intelligently—without breaking anything. - It even created a README file for the merged project. - It answered my global query instantly, pulling from the full codebase. This is the difference between AI autocomplete and an AI engineer that truly understands your repo. Augment Code is powerful because it indexes your entire repo upfront. This way, it can answer questions instantly, no matter how large your project is. Lastly, Augment Code is fully compatible with VSCode, JetBrains, Vim, Slack, and more. Try them now, I have shared a link in the next tweet! Thanks to Augment Code for showing me their powerful AI coding assistant and working with me on this post.

Akshay 🚀

30,848 次观看 • 1 年前

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:

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

296,570 次观看 • 10 个月前

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

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

17,453 次观看 • 3 个月前

CHINA JUST DROPPED AN AI CODING MODEL WITH A 1M CONTEXT WINDOW. And I connected it to Claude Code to see what it could actually do. Meet GLM-X Preview On paper, a few things immediately stood out: → 1M context window → Agentic coding capabilities → Works inside Claude Code → Designed for large-scale coding and reasoning workflows But specs don't matter much if the model can't deliver in practice. So I gave it a real-world task. THE TEST One prompt: > Build a modern AI lead generation dashboard using React and Tailwind CSS. Requirements: → Dark mode → Analytics dashboard → Lead table → Email outreach section → Responsive design → Production-ready component structure Instead of generating a few snippets, it planned the architecture, generated the dashboard components, created the Tailwind configuration, and walked through the implementation requirements. What impressed me most wasn't the code itself. It was how well it maintained context throughout the workflow. That's where a 1M context window starts becoming useful. Less time re-explaining requirements. Less context loss. More room for complex projects. The AI coding race is getting very interesting. And it's no longer just GPT, Claude, and Gemini competing for attention. Results from my test below 👇

CHINA JUST DROPPED AN AI CODING MODEL WITH A 1M CONTEXT WINDOW. And I connected it to Claude Code to see what it could actually do. Meet GLM-X Preview On paper, a few things immediately stood out: → 1M context window → Agentic coding capabilities → Works inside Claude Code → Designed for large-scale coding and reasoning workflows But specs don't matter much if the model can't deliver in practice. So I gave it a real-world task. THE TEST One prompt: > Build a modern AI lead generation dashboard using React and Tailwind CSS. Requirements: → Dark mode → Analytics dashboard → Lead table → Email outreach section → Responsive design → Production-ready component structure Instead of generating a few snippets, it planned the architecture, generated the dashboard components, created the Tailwind configuration, and walked through the implementation requirements. What impressed me most wasn't the code itself. It was how well it maintained context throughout the workflow. That's where a 1M context window starts becoming useful. Less time re-explaining requirements. Less context loss. More room for complex projects. The AI coding race is getting very interesting. And it's no longer just GPT, Claude, and Gemini competing for attention. Results from my test below 👇

Md Riyazuddin

31,199 次观看 • 1 个月前

Claude Code on desktop just added an embedded loop that can run your dev server, view the app, review local changes, and watch pull requests until they merge. It can now preview a running app inside the desktop UI while it iterates on fixes. It can also monitor CI for an open PR and either fix failures or merge when checks go green. Earlier “agentic coding” workflows usually bounced between a terminal, a browser, and GitHub, so the model could not directly see what the app rendered or stay attached to CI results without manual babysitting. The new server preview flow starts and stops dev servers from a Preview control, shows the app in an embedded browser, reads logs, and can interact with the page to verify changes. That closes a common gap where a model edits code but cannot reliably confirm the UI and runtime behavior match the intent. The local “Review code” step runs before pushing, and it leaves inline comments on the diff so basic bugs and risky changes get caught earlier. For PR monitoring, the desktop app will track status and CI checks, and it can use auto-fix to attempt repairs and auto-merge to land the PR once checks pass, using GitHub tooling under the hood. Session mobility adds a /desktop command to move a CLI session into the desktop app, and sessions can be pushed to the cloud to resume from web or phone.

Claude Code on desktop just added an embedded loop that can run your dev server, view the app, review local changes, and watch pull requests until they merge. It can now preview a running app inside the desktop UI while it iterates on fixes. It can also monitor CI for an open PR and either fix failures or merge when checks go green. Earlier “agentic coding” workflows usually bounced between a terminal, a browser, and GitHub, so the model could not directly see what the app rendered or stay attached to CI results without manual babysitting. The new server preview flow starts and stops dev servers from a Preview control, shows the app in an embedded browser, reads logs, and can interact with the page to verify changes. That closes a common gap where a model edits code but cannot reliably confirm the UI and runtime behavior match the intent. The local “Review code” step runs before pushing, and it leaves inline comments on the diff so basic bugs and risky changes get caught earlier. For PR monitoring, the desktop app will track status and CI checks, and it can use auto-fix to attempt repairs and auto-merge to land the PR once checks pass, using GitHub tooling under the hood. Session mobility adds a /desktop command to move a CLI session into the desktop app, and sessions can be pushed to the cloud to resume from web or phone.

Rohan Paul

33,431 次观看 • 5 个月前

By 2030, the data science field is projected to grow by 30% -- this is the tool I’d add to my learning path if I were re-skilling into data science: 𝐩𝐢𝐩 𝐢𝐧𝐬𝐭𝐚𝐥𝐥 𝐦𝐢𝐭𝐨-𝐚𝐢 It’s an open-source toolkit that adds AI to your Jupyter Notebooks, and it’s surprisingly helpful for learning by doing. Try now It lets you: • Use natural language to generate full data workflows • Upload an Excel file and watch it convert to clean Python code • Work with top models (ChatGPT, Claude, Gemini) right inside your notebook with no setup One thing I really like about Mito AI: it shows you exactly what it’s doing. (Which is super helpful for both beginners and debugging.) -The agent explains its assumptions - Every result links back to editable, transparent code That makes it a great companion if you're: • Transitioning from Excel • Exploring data automation or dashboards • Or just brushing up on how real data science pipelines work

By 2030, the data science field is projected to grow by 30% -- this is the tool I’d add to my learning path if I were re-skilling into data science: 𝐩𝐢𝐩 𝐢𝐧𝐬𝐭𝐚𝐥𝐥 𝐦𝐢𝐭𝐨-𝐚𝐢 It’s an open-source toolkit that adds AI to your Jupyter Notebooks, and it’s surprisingly helpful for learning by doing. Try now It lets you: • Use natural language to generate full data workflows • Upload an Excel file and watch it convert to clean Python code • Work with top models (ChatGPT, Claude, Gemini) right inside your notebook with no setup One thing I really like about Mito AI: it shows you exactly what it’s doing. (Which is super helpful for both beginners and debugging.) -The agent explains its assumptions - Every result links back to editable, transparent code That makes it a great companion if you're: • Transitioning from Excel • Exploring data automation or dashboards • Or just brushing up on how real data science pipelines work

Python Coding

107,495 次观看 • 10 个月前

The Orbofi Danny Trejo AI assistant is OUT now, your All-in-one AI, voiced and personified by me! Use it to get any question answered, generate images, code, and get stuff done. This is not your regular AI as you would assume. Enjoy a 50% discount now on the advanced mode. Be sure to Tag 3 friends in the comments for a chance to win an Advanced Danny AI subscription! Try it out now at #YODANNY #Orbofi #DannyAI

The Orbofi Danny Trejo AI assistant is OUT now, your All-in-one AI, voiced and personified by me! Use it to get any question answered, generate images, code, and get stuff done. This is not your regular AI as you would assume. Enjoy a 50% discount now on the advanced mode. Be sure to Tag 3 friends in the comments for a chance to win an Advanced Danny AI subscription! Try it out now at #YODANNY #Orbofi #DannyAI

Danny Trejo

26,964 次观看 • 1 年前

🚀 GeoAI Tutorial 12: Wetland Mapping with Deep Learning and GeoAI! 🌍 Unlock the power of your geospatial data! Learn to train an wetland detection model and run inference on large datasets—all with just a few lines of code. 🎥 Watch the full tutorial here: 📓 Explore the notebook: 🛠️ Check out the GitHub repository: 📚 Dive into the documentation: 📺 Check out the entire YouTube playlist: #GeoAI #geospatial #AI #Python #DeepLearning

🚀 GeoAI Tutorial 12: Wetland Mapping with Deep Learning and GeoAI! 🌍 Unlock the power of your geospatial data! Learn to train an wetland detection model and run inference on large datasets—all with just a few lines of code. 🎥 Watch the full tutorial here: 📓 Explore the notebook: 🛠️ Check out the GitHub repository: 📚 Dive into the documentation: 📺 Check out the entire YouTube playlist: #GeoAI #geospatial #AI #Python #DeepLearning

Qiusheng Wu

16,623 次观看 • 1 年前

Built this last night....... Claude Code Matrix Monitor hooks into Claude Code's native event system to visualize every tool call in real-time. All of Claude's file reads, searches, edits, and bash commands stream via WebSocket to a cyberpunk dashboard that renders radar sweeps, pulse rings, code rain with actual code edits / diffs, and glitch effects. It's project-local, non-invasive, and toggles on/off with one file. TLDR: you can watch the AI as it works....

Built this last night....... Claude Code Matrix Monitor hooks into Claude Code's native event system to visualize every tool call in real-time. All of Claude's file reads, searches, edits, and bash commands stream via WebSocket to a cyberpunk dashboard that renders radar sweeps, pulse rings, code rain with actual code edits / diffs, and glitch effects. It's project-local, non-invasive, and toggles on/off with one file. TLDR: you can watch the AI as it works....

Benjamin De Kraker

38,552 次观看 • 7 个月前

Solana is the fastest blockchain — with low fees and a massive developer community. And now, building on Solana is easier than ever. We just deployed an SPL Locker Program (Solana Vesting Program) in under 6 minutes — and you can too. Check out our full tutorial on OctoMCP (Beta) — our AI-powered tool that builds, validates, and deploys Solana smart contracts and UIs in minutes. No coding. No setup. Just prompts. In this video, you'll learn: How to install OctoMCP How to connect it to Claude Desktop How to build and fix Anchor programs How to deploy to the Solana Network How to fetch your Program ID, IDL, .so file, and source code Docs: Deployed SPL Locker: TX: Source Code: Program Binary: IDL:

Solana is the fastest blockchain — with low fees and a massive developer community. And now, building on Solana is easier than ever. We just deployed an SPL Locker Program (Solana Vesting Program) in under 6 minutes — and you can too. Check out our full tutorial on OctoMCP (Beta) — our AI-powered tool that builds, validates, and deploys Solana smart contracts and UIs in minutes. No coding. No setup. Just prompts. In this video, you'll learn: How to install OctoMCP How to connect it to Claude Desktop How to build and fix Anchor programs How to deploy to the Solana Network How to fetch your Program ID, IDL, .so file, and source code Docs: Deployed SPL Locker: TX: Source Code: Program Binary: IDL:

OctonetAI

60,049 次观看 • 1 年前

I tested Genspark new AI Developer: an L4 agent that builds a working app from an idea. You can choose any model (including Claude), and it runs in your browser and in the app—including planning, code, testing, and fixes. The output looks like it was done by a senior developer. I used Prompt to build a functional newsflash page that creates and curates a newsletter for me by adding a few links! It's revolutionary. Prompt in the comments. Genspark

I tested Genspark new AI Developer: an L4 agent that builds a working app from an idea. You can choose any model (including Claude), and it runs in your browser and in the app—including planning, code, testing, and fixes. The output looks like it was done by a senior developer. I used Prompt to build a functional newsflash page that creates and curates a newsletter for me by adding a few links! It's revolutionary. Prompt in the comments. Genspark

Chubby♨️

235,727 次观看 • 11 个月前

Inside Every 📧: The AI-native startup with 5 products, 7-figure revenue, and 100% AI-written code With just 15 people, Every 📧 publishes a daily AI newsletter, ships AI products, and operates a million-dollar-a-year consulting arm—all while their engineers write virtually zero code. It’s the most radical example of an AI-first company, and Dan Shipper 📧 (CEO) is a prolific writer who has become a leading voice on how AI is transforming the way we live and work. In this conversation, we discuss: 🔸 Why every company needs an “AI operations lead” 🔸 The most underrated AI tool for non-programmers 🔸 Why Dan thinks AI will reshore jobs to the U.S. 🔸 An inside look at Every’s AI-first workflow 🔸 How Dan’s team uses an arsenal of AI agents (Claude, Codex, “Friday,” “Charlie”) in parallel, treating each AI like a specialist with unique strengths 🔸 Why generalists will thrive in an AI-first world, as rigid job titles blur and everyone becomes a “manager” of AI tools 🔸 Dan’s playbook for making any company AI-first—from the CEO setting the example, to hosting internal prompt-sharing sessions, to upskilling teams on AI tools 🔸 Much more Listen now 👇 • YouTube: • Spotify: • Apple: Thank you to our wonderful sponsors for supporting the podcast: 🏆 CodeRabbit—Cut code review time and bugs in half. Instantly: 🏆 DX—A platform for measuring and improving developer productivity: 🏆 PostHog—How developers build successful products:

Inside Every 📧: The AI-native startup with 5 products, 7-figure revenue, and 100% AI-written code With just 15 people, Every 📧 publishes a daily AI newsletter, ships AI products, and operates a million-dollar-a-year consulting arm—all while their engineers write virtually zero code. It’s the most radical example of an AI-first company, and Dan Shipper 📧 (CEO) is a prolific writer who has become a leading voice on how AI is transforming the way we live and work. In this conversation, we discuss: 🔸 Why every company needs an “AI operations lead” 🔸 The most underrated AI tool for non-programmers 🔸 Why Dan thinks AI will reshore jobs to the U.S. 🔸 An inside look at Every’s AI-first workflow 🔸 How Dan’s team uses an arsenal of AI agents (Claude, Codex, “Friday,” “Charlie”) in parallel, treating each AI like a specialist with unique strengths 🔸 Why generalists will thrive in an AI-first world, as rigid job titles blur and everyone becomes a “manager” of AI tools 🔸 Dan’s playbook for making any company AI-first—from the CEO setting the example, to hosting internal prompt-sharing sessions, to upskilling teams on AI tools 🔸 Much more Listen now 👇 • YouTube: • Spotify: • Apple: Thank you to our wonderful sponsors for supporting the podcast: 🏆 CodeRabbit—Cut code review time and bugs in half. Instantly: 🏆 DX—A platform for measuring and improving developer productivity: 🏆 PostHog—How developers build successful products:

Lenny Rachitsky

314,081 次观看 • 1 年前

Introducing AI Assistance in Chrome DevTools! 🤯🚀 Ever wish you could have a coding buddy to help you with CSS and layout? Well, your wish is granted! The new AI Assistance in Chrome DevTools is here to make your life as a developer easier, powered by Gemini. The new panel aims to help you find and fix issues. Just ask it questions about your code, and it provides tailored explanations and even suggests solutions. This is our first exploration into agentic AI in DevTools and we're excited to hear what you think of it. Some key features: 1. Conversational prompts: Get tailored suggestions and code snippets. 2. Contextual understanding: AI understands the code you're working on. 3. Step-by-step guidance: Get help with everything from styling to debugging. Want to see it in action? Check out my screencast below to see how I used it to add a dark mode.

Introducing AI Assistance in Chrome DevTools! 🤯🚀 Ever wish you could have a coding buddy to help you with CSS and layout? Well, your wish is granted! The new AI Assistance in Chrome DevTools is here to make your life as a developer easier, powered by Gemini. The new panel aims to help you find and fix issues. Just ask it questions about your code, and it provides tailored explanations and even suggests solutions. This is our first exploration into agentic AI in DevTools and we're excited to hear what you think of it. Some key features: 1. Conversational prompts: Get tailored suggestions and code snippets. 2. Contextual understanding: AI understands the code you're working on. 3. Step-by-step guidance: Get help with everything from styling to debugging. Want to see it in action? Check out my screencast below to see how I used it to add a dark mode.

Addy Osmani

95,964 次观看 • 1 年前

I'm giving away Claude Code for FREE. Yes, you read that right -- the world's best AI, now completely FREE. My mission is to get the next billion people to write great software. I believe EVERYONE should have access to the best AI, but so many are constrained by costs. I'm solving this by: disrupting the world's fastest growing industry = AI + with the most proven business model = Ads You can actually try it out now -- just one line of code, and you unlock all the powers of Claude Code, for free. how it works: 1. sign up on Giga AI Free 2. change Claude Code env variables to use our inference endpoint 2. to support the free usage, we'll add ads inside the AI responses (only contextual and relevant ads, no spam) Since we get too many signups, there's a waitlist, but we'll be rolling it out to the maximum people as we can. Watch the video to get started & comment and retweet to get access first.

I'm giving away Claude Code for FREE. Yes, you read that right -- the world's best AI, now completely FREE. My mission is to get the next billion people to write great software. I believe EVERYONE should have access to the best AI, but so many are constrained by costs. I'm solving this by: disrupting the world's fastest growing industry = AI + with the most proven business model = Ads You can actually try it out now -- just one line of code, and you unlock all the powers of Claude Code, for free. how it works: 1. sign up on Giga AI Free 2. change Claude Code env variables to use our inference endpoint 2. to support the free usage, we'll add ads inside the AI responses (only contextual and relevant ads, no spam) Since we get too many signups, there's a waitlist, but we'll be rolling it out to the maximum people as we can. Watch the video to get started & comment and retweet to get access first.

Namanyay

487,549 次观看 • 9 个月前