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How to Use KaneAI — Best Gen AI Native (FULL GUIDE) 🔥” QA Engineers & DevOps: Stop wasting 80% of your time on manual tests. KaneAI converts natural language into executable End to End tests instantly: ✅ Upload JIRA issues, PDFs, or videos → Auto-generate test cases ✅ Self-healing... show more

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Stop writing tests. Start describing them. KaneAI converts natural language into end-to-end tests in seconds. ✔ JIRA / PDF / video uploads ✔ Self-healing UI tests ✔ GitHub PR-based test creation ✔ API & backend validation Modern testing, powered by GenAI Give it a try : Follow #AITesting #KaneAI #DevOps #QualityEngineering

Stop writing tests. Start describing them. KaneAI converts natural language into end-to-end tests in seconds. ✔ JIRA / PDF / video uploads ✔ Self-healing UI tests ✔ GitHub PR-based test creation ✔ API & backend validation Modern testing, powered by GenAI Give it a try : Follow #AITesting #KaneAI #DevOps #QualityEngineering

Marry claire

25,653 views • 7 months ago

🚀 Meet KaneAI TestMu AI the next-generation AI-powered testing assistant for modern QA teams. KaneAI helps teams plan, author, and evolve end-to-end tests using natural language, turning requirements directly into executable code. Built for enterprise-scale complexity, it handles sophisticated workflows across all major programming languages and frameworks. QA teams often face hurdles like rapid development cycles, test case debt, and complex framework management. KaneAI addresses these challenges by: ✅ Generating structured test cases from text, JIRA, PDFs, images, audio, video, or spreadsheets ✅ Enabling complex testing workflows with natural language ✅ Supporting multi-language code exports and deep integrations with JIRA and GitHub ✅ Automating API and database testing, smart versioning, and auto bug detection ✅ Self-healing tests for UI changes and flexible manual interaction KaneAI augments QA teams, boosting productivity, reducing errors, and helping teams focus on outcomes rather than repetitive tasks. Learn more about KaneAI here: Connect with TestMu AI : LinkedIn: Twitter: #QA #TestAutomation #AI #GenAI #KaneAI #TestMu

🚀 Meet KaneAI TestMu AI the next-generation AI-powered testing assistant for modern QA teams. KaneAI helps teams plan, author, and evolve end-to-end tests using natural language, turning requirements directly into executable code. Built for enterprise-scale complexity, it handles sophisticated workflows across all major programming languages and frameworks. QA teams often face hurdles like rapid development cycles, test case debt, and complex framework management. KaneAI addresses these challenges by: ✅ Generating structured test cases from text, JIRA, PDFs, images, audio, video, or spreadsheets ✅ Enabling complex testing workflows with natural language ✅ Supporting multi-language code exports and deep integrations with JIRA and GitHub ✅ Automating API and database testing, smart versioning, and auto bug detection ✅ Self-healing tests for UI changes and flexible manual interaction KaneAI augments QA teams, boosting productivity, reducing errors, and helping teams focus on outcomes rather than repetitive tasks. Learn more about KaneAI here: Connect with TestMu AI : LinkedIn: Twitter: #QA #TestAutomation #AI #GenAI #KaneAI #TestMu

Mohini Shewale

16,809 views • 7 months ago

Anyone who’s worked in QA knows the gap. Requirements live in one place and tests live somewhere else. Every change creates another round of rewriting. Kane AI by TestMu AI (formerly LambdaTest) approaches that gap differently. Instead of forcing teams to rewrite tests in a new abstraction, it lets you describe intent in natural language and turns that into structured, executable tests that can be exported into your existing frameworks. During exploration, the most practical part wasn’t just test generation, it was how expressive the language layer is. Complex assertions, branching conditions, and validations can be described without switching mental modes into code, but the resulting output still integrates cleanly with real pipelines. There’s also a strong emphasis on API coverage and auto-bug detection, which matters when UI tests aren’t enough. Kane AI by TestMu AI (formerly LambdaTest) can detect failures during execution and attempt self-healing based on original intent, while still requiring review and validation from the team. It doesn’t pretend QA disappears. It acknowledges QA is hard, contextual, and constantly changing. That honesty makes it useful. If you’re dealing with test maintenance and curious how natural-language testing fits into real QA work, Kane AI by TestMu AI (formerly LambdaTest) is available to try. See it in action: TestMu AI

Anyone who’s worked in QA knows the gap. Requirements live in one place and tests live somewhere else. Every change creates another round of rewriting. Kane AI by TestMu AI (formerly LambdaTest) approaches that gap differently. Instead of forcing teams to rewrite tests in a new abstraction, it lets you describe intent in natural language and turns that into structured, executable tests that can be exported into your existing frameworks. During exploration, the most practical part wasn’t just test generation, it was how expressive the language layer is. Complex assertions, branching conditions, and validations can be described without switching mental modes into code, but the resulting output still integrates cleanly with real pipelines. There’s also a strong emphasis on API coverage and auto-bug detection, which matters when UI tests aren’t enough. Kane AI by TestMu AI (formerly LambdaTest) can detect failures during execution and attempt self-healing based on original intent, while still requiring review and validation from the team. It doesn’t pretend QA disappears. It acknowledges QA is hard, contextual, and constantly changing. That honesty makes it useful. If you’re dealing with test maintenance and curious how natural-language testing fits into real QA work, Kane AI by TestMu AI (formerly LambdaTest) is available to try. See it in action: TestMu AI

AI Highlight

61,494 views • 7 months ago

I'm thrilled to announce Bug0 Studio - a self-serve, AI-native browser testing tool. We're in private beta. DM me your email for access + $250/mo in credits for 3 months. What you can do today: - Create tests from video recordings - Natural language test steps - Self-healing tests (adapts to UI changes) - Live browser preview - CI/CD integration (Vercel, Netlify, GitHub Actions) - Scheduled runs + reports via Slack, email, or PRs - Auto-extract emails (OTPs, magic links) - Team collaboration Most QA tools hide behind "contact us for demo." But I believe powerful QA shouldn't be gatekept behind sales calls and enterprise pricing. Help us build the most user-friendly and powerful AI QA tool that is open and accessible to all🙏 Today it's private beta. Soon, it's open to everyone.

I'm thrilled to announce Bug0 Studio - a self-serve, AI-native browser testing tool. We're in private beta. DM me your email for access + $250/mo in credits for 3 months. What you can do today: - Create tests from video recordings - Natural language test steps - Self-healing tests (adapts to UI changes) - Live browser preview - CI/CD integration (Vercel, Netlify, GitHub Actions) - Scheduled runs + reports via Slack, email, or PRs - Auto-extract emails (OTPs, magic links) - Team collaboration Most QA tools hide behind "contact us for demo." But I believe powerful QA shouldn't be gatekept behind sales calls and enterprise pricing. Help us build the most user-friendly and powerful AI QA tool that is open and accessible to all🙏 Today it's private beta. Soon, it's open to everyone.

Sandeep

114,592 views • 7 months ago

Most AI app builders can generate a prototype. The real question is: Can they generate something you can actually launch? I recently explored MeDo, an AI-powered full-stack app generation platform that goes beyond just creating a frontend. With a single prompt, it can generate the frontend UI, backend logic, database structure, and plugin integrations. All in one workflow, without requiring coding or deployment experience. What stood out to me is the focus on building real products rather than simple demos. Whether you're creating SaaS tools, internal dashboards, e-commerce applications, games, or business automation tools. the goal is to move from idea → working product as quickly as possible. A few notable features: ✅ Full-stack generation from a single prompt ✅ Plugin ecosystem with integrations like Stripe and AI tools ✅ Auto bug-fixing capabilities ✅ Website cloning from screenshots ✅ Built-in UI enhancement options ✅ Marketplace of ready-made apps you can customize The AI app builder space is becoming increasingly competitive, and platforms are starting to differentiate themselves based on how close they get to a production-ready result rather than just generating code. For builders, founders, and creators exploring no-code AI development, it's an interesting category worth watching. Try it today and launch your next project with just a prompt:

Most AI app builders can generate a prototype. The real question is: Can they generate something you can actually launch? I recently explored MeDo, an AI-powered full-stack app generation platform that goes beyond just creating a frontend. With a single prompt, it can generate the frontend UI, backend logic, database structure, and plugin integrations. All in one workflow, without requiring coding or deployment experience. What stood out to me is the focus on building real products rather than simple demos. Whether you're creating SaaS tools, internal dashboards, e-commerce applications, games, or business automation tools. the goal is to move from idea → working product as quickly as possible. A few notable features: ✅ Full-stack generation from a single prompt ✅ Plugin ecosystem with integrations like Stripe and AI tools ✅ Auto bug-fixing capabilities ✅ Website cloning from screenshots ✅ Built-in UI enhancement options ✅ Marketplace of ready-made apps you can customize The AI app builder space is becoming increasingly competitive, and platforms are starting to differentiate themselves based on how close they get to a production-ready result rather than just generating code. For builders, founders, and creators exploring no-code AI development, it's an interesting category worth watching. Try it today and launch your next project with just a prompt:

Markandey Sharma

49,777 views • 3 months ago

Free GPT-5.6 Sol/Terra/Luna + Claude Sonnet 4.6 + a full IDE one code editor just dropped a 14-day Pro trial with popular AI models ( no card required, no BS ) what you get: - GPT-5.6 Sol, Terra, Luna (full family) - Claude Sonnet 4.6 - two weeks of real coding - native IDE built in Rust (10x faster than VS Code) - multiplayer coding + native AI integration how to get: 1. go to zed(.)dev, sign in via GitHub (account must be 1+ month old) 2. click Pricing, select Pro, hit "Start Trial Now" 3. download their IDE 4. open a project -> click the star icon bottom-left -> pick your model in other words, you get a full-featured IDE with leading AI tools that work for free for 14 days - all for $0. based on the tests I've run, I'd say the speed and ease of use are really great - on par with Cursor. btw I recently wrote a full guide on ways to pay $0 for every subscription you have - this is just one of them worth to read:

Free GPT-5.6 Sol/Terra/Luna + Claude Sonnet 4.6 + a full IDE one code editor just dropped a 14-day Pro trial with popular AI models ( no card required, no BS ) what you get: - GPT-5.6 Sol, Terra, Luna (full family) - Claude Sonnet 4.6 - two weeks of real coding - native IDE built in Rust (10x faster than VS Code) - multiplayer coding + native AI integration how to get: 1. go to zed(.)dev, sign in via GitHub (account must be 1+ month old) 2. click Pricing, select Pro, hit "Start Trial Now" 3. download their IDE 4. open a project -> click the star icon bottom-left -> pick your model in other words, you get a full-featured IDE with leading AI tools that work for free for 14 days - all for $0. based on the tests I've run, I'd say the speed and ease of use are really great - on par with Cursor. btw I recently wrote a full guide on ways to pay $0 for every subscription you have - this is just one of them worth to read:

kaize

35,775 views • 1 month ago

Claude will replace manual traders in 2026. New update lets you give it full control of your computer. That's why I decided to test it with $100 and total access. Asked to turn it into $1,000 on Polymarket or I shut it down. 3 hours later it was scanning every wallet on Polymarket for copy trading opportunities. It found best wallets and started testing them through this bot: At first, it lost $73 trying each wallet to understand which ones were profitable. Then it picked 7 wallets, executed copy trades automatically and did something i don't believe even now. $3,467 profit in 24 hours. Automatically. With no monitoring. What’s insane is how it works: • Claude monitors hundreds of wallets 24/7 • Evaluates win rates, market timing and sizing • Tests micro trades to find the best strategy • Executes automatically with AL and TP rules This is why AI is mandatory in 2026. Markets move faster than humans, I've been telling it for months. Your edge is speed, analysis, and execution. Anyone still clicking buttons manually will lose edge within months. I just reinvested the profits and let Claude keep copy trading. This is the future. Manual trading is probably dead FOREVER.

Claude will replace manual traders in 2026. New update lets you give it full control of your computer. That's why I decided to test it with $100 and total access. Asked to turn it into $1,000 on Polymarket or I shut it down. 3 hours later it was scanning every wallet on Polymarket for copy trading opportunities. It found best wallets and started testing them through this bot: At first, it lost $73 trying each wallet to understand which ones were profitable. Then it picked 7 wallets, executed copy trades automatically and did something i don't believe even now. $3,467 profit in 24 hours. Automatically. With no monitoring. What’s insane is how it works: • Claude monitors hundreds of wallets 24/7 • Evaluates win rates, market timing and sizing • Tests micro trades to find the best strategy • Executes automatically with AL and TP rules This is why AI is mandatory in 2026. Markets move faster than humans, I've been telling it for months. Your edge is speed, analysis, and execution. Anyone still clicking buttons manually will lose edge within months. I just reinvested the profits and let Claude keep copy trading. This is the future. Manual trading is probably dead FOREVER.

Oracle Boar

66,427 views • 5 months ago

"This will replace 80% of the apps that you have on your phone." Here's my new episode with Peter Steinberger 🦞 where he showed me: ✅ His personal OpenClaw use cases - flight check-in, home security, and much more ✅ His counterintuitive AI coding workflow - no plan mode, no MCPs, and no fancy prompts ✅ Practical advice for other builders and how to build product taste Some quotes from Peter: "It's like having a new weird friend that is also really smart and resourceful that lives on your computer." "Why should I use MyFitnessPal when I have an infinitely resourceful assistant that already knows I'm making bad decisions at KFC?" "I don't use MCPs or any of that crap. Just because you can build everything doesn't mean you should." 📌 Watch now: Thanks to our sponsors: Granola - The best AI meeting notes app I've ever used: Replit ⠕ - Create beautiful prototypes and full stack apps:

"This will replace 80% of the apps that you have on your phone." Here's my new episode with Peter Steinberger 🦞 where he showed me: ✅ His personal OpenClaw use cases - flight check-in, home security, and much more ✅ His counterintuitive AI coding workflow - no plan mode, no MCPs, and no fancy prompts ✅ Practical advice for other builders and how to build product taste Some quotes from Peter: "It's like having a new weird friend that is also really smart and resourceful that lives on your computer." "Why should I use MyFitnessPal when I have an infinitely resourceful assistant that already knows I'm making bad decisions at KFC?" "I don't use MCPs or any of that crap. Just because you can build everything doesn't mean you should." 📌 Watch now: Thanks to our sponsors: Granola - The best AI meeting notes app I've ever used: Replit ⠕ - Create beautiful prototypes and full stack apps:

Peter Yang

667,474 views • 7 months ago

$FAME and #AICON Launcher are officially LIVE on Base!🔥 A chance to be part of something BIG–Participate in the #AICON revolution and experience the top-tier seamless experience with #FameAI 🔗 Time to celebrate this milestone together! 🌟 ----------------------------------------------------------- 🚨 Early Access to Fame AI-CON Launcher is Now Available on BASE! 🚨 With FameAI's #AICON Launcher, you can: ✨ Create your human-like AICON ✨ Publish your AI-CON's token on the market $FAME will be tokenized as the first tradable #AICON on our platform! ----------------------------------------------------------- 🔥Early access will be available for selected $FMC stakers🔥 Stakers can enjoy full features being rolled out in the coming weeks. Next up, opening to the public! $FMC stakers, stake now if you haven't already! 👉 ----------------------------------------------------------- 🟣 How Does #FameAI's #AICON Launcher Work? 💻 No coding required! Anyone can create their own #AICON 🔗 Launch your #AICON token—graduated AI-CON can trade on Base Uniswap v2 ⚙️ Fully customizable and highly autonomous How to acquire $FMC on Base ----------------------------------------------------------- 🟣 $FAME Token and FAME Framework This is built to simulate human-like interactions on social platforms. 🎨 Generates content: Images, text, videos 🤖 Reflects personality, knowledge, and mood 💰 Powered by $FAME token ✨ CA: 0xB8e23ab4A1762Fe8dABb844EcC66FEEE3725c480 🔗 Read more here 👉 ----------------------------------------------------------- 🟣 Fame Studio Fame Studio lets you: ✅ Create hyper-realistic human identities ✅ Generate images, audio, music, and even videos V2 Update Coming Soon– Expanded features for more engaging content—perfect for creators and innovators! #AIAgents $FMC #FameAI $FAME ----------------------------------------------------------- 🟣 #FameAI Roadmap for Q1 2025 🚀 Skill Marketplace: Co-create #AICON, utilizing $FMC as the native currency 🧠 AI-Agent Learning: Train agents to learn specific tones, personalities, and behaviors with one click 🎥 Live Streaming: Superhuman-like models for business or lifestyle-focused live streams

$FAME and #AICON Launcher are officially LIVE on Base!🔥 A chance to be part of something BIG–Participate in the #AICON revolution and experience the top-tier seamless experience with #FameAI 🔗 Time to celebrate this milestone together! 🌟 ----------------------------------------------------------- 🚨 Early Access to Fame AI-CON Launcher is Now Available on BASE! 🚨 With FameAI's #AICON Launcher, you can: ✨ Create your human-like AICON ✨ Publish your AI-CON's token on the market $FAME will be tokenized as the first tradable #AICON on our platform! ----------------------------------------------------------- 🔥Early access will be available for selected $FMC stakers🔥 Stakers can enjoy full features being rolled out in the coming weeks. Next up, opening to the public! $FMC stakers, stake now if you haven't already! 👉 ----------------------------------------------------------- 🟣 How Does #FameAI's #AICON Launcher Work? 💻 No coding required! Anyone can create their own #AICON 🔗 Launch your #AICON token—graduated AI-CON can trade on Base Uniswap v2 ⚙️ Fully customizable and highly autonomous How to acquire $FMC on Base ----------------------------------------------------------- 🟣 $FAME Token and FAME Framework This is built to simulate human-like interactions on social platforms. 🎨 Generates content: Images, text, videos 🤖 Reflects personality, knowledge, and mood 💰 Powered by $FAME token ✨ CA: 0xB8e23ab4A1762Fe8dABb844EcC66FEEE3725c480 🔗 Read more here 👉 ----------------------------------------------------------- 🟣 Fame Studio Fame Studio lets you: ✅ Create hyper-realistic human identities ✅ Generate images, audio, music, and even videos V2 Update Coming Soon– Expanded features for more engaging content—perfect for creators and innovators! #AIAgents $FMC #FameAI $FAME ----------------------------------------------------------- 🟣 #FameAI Roadmap for Q1 2025 🚀 Skill Marketplace: Co-create #AICON, utilizing $FMC as the native currency 🧠 AI-Agent Learning: Train agents to learn specific tones, personalities, and behaviors with one click 🎥 Live Streaming: Superhuman-like models for business or lifestyle-focused live streams

Fame AI | The Home of AI Agent 2.0 - AI-CON

23,775 views • 1 year ago

What they don't tell you about vibe coding: • Moltbook exposed 1.5M auth tokens. The owner hadn't written a single line of code. • Tea App leaked 72,000 government IDs. The database was just open, no sophisticated hack needed. • A researcher took control of a journalist's computer through her own vibe-coded game, without a single click. The code ran fine in all three cases, tests passed, reviews looked clean, and nothing raised a flag. That's the problem nobody is talking about. Teams are shipping faster than ever. AI writes the code. CI catches build failures. Tests catch regressions. Observability catches outages. But nobody is asking the one question that actually matters: What can an attacker do with this, right now? Because the bottleneck is no longer writing code. It's understanding what that code actually exposes once it's live. PR reviews miss auth edge cases. Unit tests don't probe broken access control. Staging environments don't simulate adversarial behavior. And business logic flaws look completely fine until someone decides to break them on purpose. Strix is an open-source tool that fills this gap. It reviews your running app the way an attacker would: - Crawls the app and maps every exposed route and flow - Probes abuse paths dynamically, not just at build time - Returns findings with proof-of-concepts and suggested fixes Strix was benchmarked against 200 real companies and open-source repos, where it found 600+ verified vulnerabilities including assigned CVEs. It's designed to fit into how modern teams already work. Run it before a release, after major changes, or continuously as the app evolves. If your team is shipping AI-generated code and you don't currently have a way to answer "what does this actually expose", it's worth looking at. GitHub link in the next tweet.

What they don't tell you about vibe coding: • Moltbook exposed 1.5M auth tokens. The owner hadn't written a single line of code. • Tea App leaked 72,000 government IDs. The database was just open, no sophisticated hack needed. • A researcher took control of a journalist's computer through her own vibe-coded game, without a single click. The code ran fine in all three cases, tests passed, reviews looked clean, and nothing raised a flag. That's the problem nobody is talking about. Teams are shipping faster than ever. AI writes the code. CI catches build failures. Tests catch regressions. Observability catches outages. But nobody is asking the one question that actually matters: What can an attacker do with this, right now? Because the bottleneck is no longer writing code. It's understanding what that code actually exposes once it's live. PR reviews miss auth edge cases. Unit tests don't probe broken access control. Staging environments don't simulate adversarial behavior. And business logic flaws look completely fine until someone decides to break them on purpose. Strix is an open-source tool that fills this gap. It reviews your running app the way an attacker would: - Crawls the app and maps every exposed route and flow - Probes abuse paths dynamically, not just at build time - Returns findings with proof-of-concepts and suggested fixes Strix was benchmarked against 200 real companies and open-source repos, where it found 600+ verified vulnerabilities including assigned CVEs. It's designed to fit into how modern teams already work. Run it before a release, after major changes, or continuously as the app evolves. If your team is shipping AI-generated code and you don't currently have a way to answer "what does this actually expose", it's worth looking at. GitHub link in the next tweet.

Akshay 🚀

52,399 views • 5 months ago

Excited to introduce MakeUGC — the #1 AI Ad Maker. We trained AI on 10,000+ viral ads and now it understands "attention" better than we do. MakeUGC ( is capable of generating ad scripts, catchy hooks, and high-converting ads in minutes. How it works: 1. Upload your product photo. MakeUGC will create product-in-hand videos, B-rolls, custom hooks, and more. 2. Describe the product to our AI scriptwriter, and it will generate an ad script in seconds. 3. Pick an AI actor, adjust voiceover, gender, tone, and emotions as per your guidelines. 4. Generate 100s of Titkok-style hooks and personalized ads in minutes. Run A/B tests and optimize without wasting weeks. While competitors with cheap rip-offs who are half as good as MakeUGC cost $2k-$5k/month, MakeUGC costs $7 per video and you get: → 150+ licensed AI actors: No copyright issues → 29+ languages: Global Reach. Local Impact. → 20+ scenes: Variety to match your style Want your custom AI avatar? Done. Want a creator to show your b2b saas? Done. Want the creator to hold your product? Done. 20,000+ brands like Prime by Logan Paul, Turkish Airlines, and Cranberry Apps are already using MakeUGC to scale their revenue. Our top client saved $100,000+ in ad spend last month. Incredible leverage, right? If you are a DTC brand, running an ad agency, or building an app, MakeUGC is here to make your life easier. The annual plan starts at $469/year. Don't like the results? No worries. We will process a 100% refund. No questions asked. Let's get your brand to the moon. If you're here, I have something for you 👇🏻

George Stock

42,050 views • 1 year ago

New short course: Vibe Coding 101 with Replit! Learn to build and host applications with an AI agent in this course, built in partnership with Replit ⠕ and taught by its President Michele Catasta and Head of Developer Relations . Coding agents are changing how we write code. "Vibe coding" refers to a growing practice where you might barely look at the generated code, and instead focus on the architecture and features of your application. However, contrary to popular belief, effectively coding this way isn't done by just prompting, accepting all recommendations, and hoping for the best. It requires structuring your work, refining your prompts, and having a systematic process that lead to a more efficient and effective workflow. I code frequently using LLMs, and asking an LLM to do everything in one shot usually does not work. I'll typically take a problem, partition it into manageable modules, spend time creating prompts to specify each module, and use the model to produce the code one module at a time, and test/debug each module before moving on. A process like this is making me and many other developers faster and more efficient. In this video-only course, you’ll learn how to use Replit’s cloud environment--with an integrated code editor, package manager, and deployment tools--to build and deploy web applications. Along the way, you’ll learn strategies for working effectively with agents and improve your development skills. In detail, you’ll: - Understand principles of agentic code development such as being precise, giving agents one task at a time, making prompts specific, keeping projects tidy, starting with fresh sessions for each new feature, and how to approach debugging. - Learn how to get started with Replit, and key skills for vibe coding: Thinking, using frameworks, checkpoints, debugging, and providing context. - Create a product requirement document (PRD) and wireframe for your agent to build a prototype of a website performance analyzer. - See how to use an agent to make your prototype more visually appealing, and deploy it application others to access . - Learn to build a head-to-head national park ranking app, from a sample dataset, with voting capabilities and persistent data storage, and refine further ask the assistant to recap and explain what it built to find room for improvement and reinforce your learning. By the end of this course, you’ll have a solid foundation in building with coding agents, and a process you can use to keep vibe coding effectively. Please sign up here:

New short course: Vibe Coding 101 with Replit! Learn to build and host applications with an AI agent in this course, built in partnership with Replit ⠕ and taught by its President Michele Catasta and Head of Developer Relations . Coding agents are changing how we write code. "Vibe coding" refers to a growing practice where you might barely look at the generated code, and instead focus on the architecture and features of your application. However, contrary to popular belief, effectively coding this way isn't done by just prompting, accepting all recommendations, and hoping for the best. It requires structuring your work, refining your prompts, and having a systematic process that lead to a more efficient and effective workflow. I code frequently using LLMs, and asking an LLM to do everything in one shot usually does not work. I'll typically take a problem, partition it into manageable modules, spend time creating prompts to specify each module, and use the model to produce the code one module at a time, and test/debug each module before moving on. A process like this is making me and many other developers faster and more efficient. In this video-only course, you’ll learn how to use Replit’s cloud environment--with an integrated code editor, package manager, and deployment tools--to build and deploy web applications. Along the way, you’ll learn strategies for working effectively with agents and improve your development skills. In detail, you’ll: - Understand principles of agentic code development such as being precise, giving agents one task at a time, making prompts specific, keeping projects tidy, starting with fresh sessions for each new feature, and how to approach debugging. - Learn how to get started with Replit, and key skills for vibe coding: Thinking, using frameworks, checkpoints, debugging, and providing context. - Create a product requirement document (PRD) and wireframe for your agent to build a prototype of a website performance analyzer. - See how to use an agent to make your prototype more visually appealing, and deploy it application others to access . - Learn to build a head-to-head national park ranking app, from a sample dataset, with voting capabilities and persistent data storage, and refine further ask the assistant to recap and explain what it built to find room for improvement and reinforce your learning. By the end of this course, you’ll have a solid foundation in building with coding agents, and a process you can use to keep vibe coding effectively. Please sign up here:

Andrew Ng

753,122 views • 1 year ago