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Vibe coding is coming to data analytics. Just showed how to build a custom sales dashboard from Snowflake data using Replit ⠕ Agent - nothing but natural language prompts. No SQL. No Python. No DevOps. Part 2 coming soon! Stay tuned. Timestamps: 0:00 Intro 3:18 Vibe coding coming to... show more

Manny Bernabe

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85,357 次观看 • 6 个月前 •via X (Twitter)

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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 By the time your agent retrieves the data, it's already outdated.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

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i tested a fully local ai coding setup: gemma4 from Google DeepMind running through LM Studio, paired with pi which is a minimal open source coding harness this is part 1 of a two part series. here we cover the why and the complete hands-on setup 0:00 - Running a coding agent fully local 0:47 - Why Pi as the coding agent harness 1:39 - Why Gemma 4 and which variant to pick 2:44 - Architecture: Pi, LM Studio and Gemma 4 3:45 - LM Studio setup and model download 5:01 - Starting the local server 5:19 - API sanity check with curl 6:08 - Installing the Pi coding agent 6:20 - Configuring models.json for local models 8:20 - First run: selecting the model in Pi 8:58 - Fixing the context length error 10:16 - Testing the working setup 10:50 - What is coming in Part 2

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52,563 次观看 • 1 年前

Solidus Ai Tech Presents Agent Forge: Transforming AI Technology! Agent Forge is more than a platform—it's a revolution in how users interact with AI agents. Accessible to everyone, from seasoned professionals to newcomers, it empowers users to: 🔹Create Autonomous AI Agents: Automate processes, execute strategies, and stay ahead 24/7. 🔹 Gain Real-Time Insights: Stay informed with market updates via leading data platforms like CoinGecko and CoinMarketCap. 🔹 Simplify Complex Systems: Build automated workflows and manage digital strategies effortlessly, with no coding required. 🔹 Optimize Financial Management: Track data, optimize resources, and manage workflows with ease. 🔹 Breaking Barriers in AI Automation: Agent Forge makes advanced AI accessible to all, eliminating traditional technical challenges. 💡 Powered by AITECH HPC Data Center, Agent Forge ensures speed, security, and eco-friendly operations. 🗓 Coming Soon Agent Forge isn’t just a launch—it’s a leap forward.

Solidus Ai Tech Presents Agent Forge: Transforming AI Technology! Agent Forge is more than a platform—it's a revolution in how users interact with AI agents. Accessible to everyone, from seasoned professionals to newcomers, it empowers users to: 🔹Create Autonomous AI Agents: Automate processes, execute strategies, and stay ahead 24/7. 🔹 Gain Real-Time Insights: Stay informed with market updates via leading data platforms like CoinGecko and CoinMarketCap. 🔹 Simplify Complex Systems: Build automated workflows and manage digital strategies effortlessly, with no coding required. 🔹 Optimize Financial Management: Track data, optimize resources, and manage workflows with ease. 🔹 Breaking Barriers in AI Automation: Agent Forge makes advanced AI accessible to all, eliminating traditional technical challenges. 💡 Powered by AITECH HPC Data Center, Agent Forge ensures speed, security, and eco-friendly operations. 🗓 Coming Soon Agent Forge isn’t just a launch—it’s a leap forward.

AITECH CLOUD NETWORK

171,755 次观看 • 1 年前

I'm a dev now (thanks to caffeine) In this video, I show how I went from content creator to building real apps on-chain using just natural language prompts ☕ #ICP 0:00 Intro 0:51 First look at the app 3:18 First prompt 4:01 Picking a better name for the app & designing the logo 5:22 Building an image hosting website 6:41 Second Chess website draft 7:40 Second prompt 8:08 Uploading the logo to the blockchain 8:35 Second Draft 8:47 Trying to fix the AI opponent 8:57 Third draft 9:23 Changing the app's name & logo 10:04 Closing thoughts

Alex (BCP)

12,552 次观看 • 10 个月前

Vibe coding is like politics, there is a lot of fluff and very few answers to the hard questions. 1. Of every $$ a vibe coding platform makes, what % goes to Anthropic? 2. How does the margin change when switching between models? 3. Do vibe coding platforms really have any defensibility… really? 4. Does Cursor and Cognition come down to eat consumer or do consumer platforms like Lovable, Replit and Base44 move up and eat more of the dev workflow? 5. Salesforce, Atlassian, Cloudflare, of all incumbents adding vibe coding, which is best and worst? Spotify 👉 Youtube 👉 Apple Podcasts 👉 My 6 takeaways with 👇 Timestamps: 00:00 Intro 01:13 The Decision Behind Selling Base44 11:56 How Base44 Thinks About Defensibility 16:37 Mapping the Future of the Market in 3–5 Years 23:18 I’m Worried About Google 30:47 Margins Do Not Matter 37:15 What’s the Metric for User Success? 41:52 Do Early Revenue Numbers Actually Matter in AI? 49:33 Where Should Smart Money Go Today? 53:01 How does Base44 beat Cursor? 57:47 Will the AI Boom Hit a Revenue Speed Bump? 01:01:13 Are AI Builders Overvalued or Is Wix Undervalued? 01:03:45 Does Not Being in Silicon Valley Help or Hurt You? 01:05:07 Quick-Fire Round

Vibe coding is like politics, there is a lot of fluff and very few answers to the hard questions. 1. Of every $$ a vibe coding platform makes, what % goes to Anthropic? 2. How does the margin change when switching between models? 3. Do vibe coding platforms really have any defensibility… really? 4. Does Cursor and Cognition come down to eat consumer or do consumer platforms like Lovable, Replit and Base44 move up and eat more of the dev workflow? 5. Salesforce, Atlassian, Cloudflare, of all incumbents adding vibe coding, which is best and worst? Spotify 👉 Youtube 👉 Apple Podcasts 👉 My 6 takeaways with 👇 Timestamps: 00:00 Intro 01:13 The Decision Behind Selling Base44 11:56 How Base44 Thinks About Defensibility 16:37 Mapping the Future of the Market in 3–5 Years 23:18 I’m Worried About Google 30:47 Margins Do Not Matter 37:15 What’s the Metric for User Success? 41:52 Do Early Revenue Numbers Actually Matter in AI? 49:33 Where Should Smart Money Go Today? 53:01 How does Base44 beat Cursor? 57:47 Will the AI Boom Hit a Revenue Speed Bump? 01:01:13 Are AI Builders Overvalued or Is Wix Undervalued? 01:03:45 Does Not Being in Silicon Valley Help or Hurt You? 01:05:07 Quick-Fire Round

Harry Stebbings

17,514 次观看 • 8 个月前

A Google Cloud engineer just showed how to build a full app with Claude from scratch he spent 26 minutes live on stage doing what most teams take weeks to do worth more than any $500 vibe-coding course here's what he covers: > zero to deployed app in a single session > handling five engineering roles alone with Claude > the exact workflow Google uses internally > no team, no setup, just Claude and a goal the people who figure out what Claude can actually do are building things everyone else thinks requires a team that's exactly why I wrote a step by step guide on how to build your first AI agent the guide is in the article below

A Google Cloud engineer just showed how to build a full app with Claude from scratch he spent 26 minutes live on stage doing what most teams take weeks to do worth more than any $500 vibe-coding course here's what he covers: > zero to deployed app in a single session > handling five engineering roles alone with Claude > the exact workflow Google uses internally > no team, no setup, just Claude and a goal the people who figure out what Claude can actually do are building things everyone else thinks requires a team that's exactly why I wrote a step by step guide on how to build your first AI agent the guide is in the article below

Anatoli Kopadze

459,568 次观看 • 2 个月前

How to build long-horizon AI agents: behavior specs, ontologies, process supervision - my conversation with Mitchell Troyanovsky, co-founder of Basis 01:09 Why Everyone at Basis Was Whispering to AI when Stephanie Palazzolo walked in 04:12 Accounting as "an Intelligence Over the Economy" 06:11 What Makes an Agent Truly Long-Horizon 08:24 Inside an Autonomous, Multi-Day Tax Return 10:19 Agents That Hand Off Like Senior Engineers 11:17 A Brief History of Agents: From ReAct to Today 12:33 Why LLMs Have No Long-Term Memory 14:13 Why AutoGPT Didn't Live Up to Its Promise 15:51 The Three Breakthroughs: Opus 3, o1, o3 17:07 Why Reasoning Models Unlocked Agents 18:23 "Let's Verify Step by Step": The Road Not Taken 20:32 Pushing Back on the METR Chart 22:09 Why Coding Agents Won First 25:14 Why Real-World Agents Are Harder 26:55 How Accountants Verify Non-Deterministic Work 29:18 You Can't Scale Tax Returns Like Math 33:16 100 Evals Pass - So What? 35:53 Right Answer, Wrong Process 36:37 Behavior Specs, Explained 39:58 How Specific Should Behaviors Be? 42:18 Context Is Runtime Training Data 44:21 Who Judges the Judge? 46:45 The Move 37 Objection 50:02 The Magic Box Mental Model 52:41 "Nothing Has Changed Since o3" 54:56 Open-Sourcing Behavior Specs with Ankur Goyal Braintrust 59:45 Ontologies: A World for Agents to Live In 01:04:20 Documentation as Codebase 01:06:33 Why the Founding Fathers Were Context Engineers 01:09:05 Onboarding 300 Brilliant Alien Employees 01:11:10 Self-Improving Agent Systems 01:12:50 The Context Mistake Agent Builders Make 01:14:29 RL on Behavior Adherence 01:17:01 Will the Bitter Lesson Swallow the Harness 01:18:46 "Technical Moats Are Not Real Moats" 01:21:03 Advice for AI Builders

How to build long-horizon AI agents: behavior specs, ontologies, process supervision - my conversation with Mitchell Troyanovsky, co-founder of Basis 01:09 Why Everyone at Basis Was Whispering to AI when Stephanie Palazzolo walked in 04:12 Accounting as "an Intelligence Over the Economy" 06:11 What Makes an Agent Truly Long-Horizon 08:24 Inside an Autonomous, Multi-Day Tax Return 10:19 Agents That Hand Off Like Senior Engineers 11:17 A Brief History of Agents: From ReAct to Today 12:33 Why LLMs Have No Long-Term Memory 14:13 Why AutoGPT Didn't Live Up to Its Promise 15:51 The Three Breakthroughs: Opus 3, o1, o3 17:07 Why Reasoning Models Unlocked Agents 18:23 "Let's Verify Step by Step": The Road Not Taken 20:32 Pushing Back on the METR Chart 22:09 Why Coding Agents Won First 25:14 Why Real-World Agents Are Harder 26:55 How Accountants Verify Non-Deterministic Work 29:18 You Can't Scale Tax Returns Like Math 33:16 100 Evals Pass - So What? 35:53 Right Answer, Wrong Process 36:37 Behavior Specs, Explained 39:58 How Specific Should Behaviors Be? 42:18 Context Is Runtime Training Data 44:21 Who Judges the Judge? 46:45 The Move 37 Objection 50:02 The Magic Box Mental Model 52:41 "Nothing Has Changed Since o3" 54:56 Open-Sourcing Behavior Specs with Ankur Goyal Braintrust 59:45 Ontologies: A World for Agents to Live In 01:04:20 Documentation as Codebase 01:06:33 Why the Founding Fathers Were Context Engineers 01:09:05 Onboarding 300 Brilliant Alien Employees 01:11:10 Self-Improving Agent Systems 01:12:50 The Context Mistake Agent Builders Make 01:14:29 RL on Behavior Adherence 01:17:01 Will the Bitter Lesson Swallow the Harness 01:18:46 "Technical Moats Are Not Real Moats" 01:21:03 Advice for AI Builders

Matt Turck

14,518 次观看 • 3 天前