While much of the world is focused on large language models, our Salesforce AI Research teams are looking at smaller models that offer unique advantages in speed, cost, and accessibility. In this episode, learn what Small Language Models are, how they work and how they can be used for task-specific situations like personal agents on wearable devices like smart watches and robotics.

Learn more about Agentforce: https://www.salesforce.com/agentforce/
Learn more about AI Agents: https://www.salesforce.com/agentforce/ai-agents/

The AI Research Lab - Explained gives you a sneak peak of cutting-edge AI techniques developed by Salesforce’s very own AI Research group. Along the way, we’ll demystify complex concepts and share real-world insights—all from the forefront of research.

#Salesforce #Agentforce

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Improve customer relationships with Salesforce, the #1 AI CRM where humans with agents drive customer success together. Our integrated platform pairs your unified customer data with trusted agents that can assist, take action autonomously, and hand off seamlessly to your employees in sales, service, marketing, commerce, and more.

Disclaimer: This video is for demonstration purposes only. All account data depicted is fictional and does not contain personally identifiable information (PII). This content is intended solely to illustrate product functionality in a simulated environment.

Try Notion for free → https://ntn.so/techwithtim

👉 Check out PyCharm, the only Python IDE you need. Built for web, data, and AI/ML professionals. Download now. Free forever, plus one month of Pro included: https://jb.gg/check_out_pycharm_ide

Today I'm going to show you how to build an AI agent in Python in less than ten minutes.

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🎞 Video Resources 🎞
UV Video: https://www.youtube.com/watch?v=6pttmsBSi8M
Code in this video: https://github.com/techwithtim..../PythonAIAgentin10Mi

⏳ Timestamps ⏳
00:00 | Install & Setup
01:23 | OpenAI API Key
03:26 | Imports
04:42 | Tools
06:39 | LLM & Agent
07:43 | Driver Code
09:45 | Testing

Hashtags
#Python #AIAgents #Notion

Boris Cherny is the creator and head of Claude Code at Anthropic. What began as a simple terminal-based prototype just a year ago has transformed the role of software engineering and is increasingly transforming all professional work.

*We discuss:*
1. How Claude Code grew from a quick hack to 4% of public GitHub commits, with daily active users doubling last month
2. The counterintuitive product principles that drove Claude Code’s success
3. Why Boris believes coding is “solved”
4. The latent demand that shaped Claude Code and Cowork
5. Practical tips for getting the most out of Claude Code and Cowork
6. How underfunding teams and giving them unlimited tokens leads to better AI products
7. Why Boris briefly left Anthropic for Cursor, then returned after just two weeks
8. Three principles Boris shares with every new team member

*Brought to you by:*
DX—The developer intelligence platform designed by leading researchers: https://getdx.com/lenny
Sentry—Code breaks, fix it faster: https://sentry.io/lenny
Metaview—The AI platform for recruiting: https://metaview.ai/lenny

*Episode transcript:* https://www.lennysnewsletter.c....om/p/head-of-claude-

*Archive of all Lenny's Podcast transcripts:*
https://www.dropbox.com/scl/fo/yxi4s2w998p1gvtpu4193/AMdNPR8AOw0lMklwtnC0TrQ?rlkey=j06x0nipoti519e0xgm23zsn9&st=ahz0fj11&dl=0

*Where to find Boris Cherny:*
• X: https://x.com/bcherny
• LinkedIn: https://www.linkedin.com/in/bcherny
• Website: https://borischerny.com

*Where to find Lenny:*
• Newsletter: https://www.lennysnewsletter.com
• X: https://twitter.com/lennysan
• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/

*In this episode, we cover:*
(00:00) Introduction to Boris and Claude Code
(03:45) Why Boris briefly left Anthropic for Cursor (and what brought him back)
(05:35) One year of Claude Code
(08:41) The origin story of Claude Code
(13:29) How fast AI is transforming software development
(15:01) The importance of experimentation in AI innovation
(16:17) Boris’s current coding workflow (100% AI-written)
(17:32) The next frontier
(22:24) The downside of rapid innovation
(24:02) Principles for the Claude Code team
(26:48) Why you should give engineers unlimited tokens
(27:55) Will coding skills still matter in the future?
(32:15) The printing press analogy for AI’s impact
(36:01) Which roles will AI transform next?
(40:41) Tips for succeeding in the AI era
(44:37) Poll: Which roles are enjoying their jobs more with AI
(46:32) The principle of latent demand in product development
(51:53) How Cowork was built in just 10 days
(54:04) The three layers of AI safety at Anthropic
(59:35) Anxiety when AI agents aren’t working
(01:02:25) Boris’s Ukrainian roots
(01:03:21) Advice for building AI products
(01:08:38) Pro tips for using Claude Code effectively
(01:11:16) Thoughts on Codex
(01:12:13) Boris’s post-AGI plans
(01:14:02) Lightning round and final thoughts

*Referenced:*
• Cursor: https://cursor.com
• The rise of Cursor: The $300M ARR AI tool that engineers can’t stop using | Michael Truell (co-founder and CEO): https://www.lennysnewsletter.com/p/the-rise-of-cursor-michael-truell
• Anthropic: https://www.anthropic.com
• Anthropic’s CPO on what comes next | Mike Krieger (co-founder of Instagram): https://www.lennysnewsletter.com/p/anthropics-cpo-heres-what-comes-next
• Claude Code Is the Inflection Point: https://newsletter.semianalysi....s.com/p/claude-code-
• Spotify says its best developers haven’t written a line of code since December, thanks to AI: https://techcrunch.com/2026/02..../12/spotify-says-its
• Anthropic co-founder on quitting OpenAI, AGI predictions, $100M talent wars, 20% unemployment, and the nightmare scenarios keeping him up at night | Ben Mann: https://www.lennysnewsletter.com/p/anthropic-co-founder-benjamin-mann
• Haiku: https://www.anthropic.com/claude/haiku
• Sonnet: https://www.anthropic.com/claude/sonnet
• Opus: https://www.anthropic.com/claude/opus
• Jenny Wen on X: https://x.com/jenny_wen
• Johannes Gutenberg: https://en.wikipedia.org/wiki/Johannes_Gutenberg
• Anthropic jobs: https://www.anthropic.com/careers/jobs
• Lenny’s AI poll post on X: https://x.com/lennysan/status/2020266745722991051
• Fiona Fung on LinkedIn: https://www.linkedin.com/in/fionafung
• Brandon Kurkela on LinkedIn: https://www.linkedin.com/in/bkurkela
• Cowork: https://www.anthropic.com/webinars/future-of-ai-at-work-introducing-cowork
• Chris Olah on X: https://x.com/ch402
• The Bitter Lesson: http://www.incompleteideas.net..../IncIdeas/BitterLess
...References continued at: https://www.lennysnewsletter.c....om/p/head-of-claude-

_Production and marketing by https://penname.co/._
_For inquiries about sponsoring the podcast, email [email protected]._

Lenny may be an investor in the companies discussed.

In this video, I walk through my complete workflow for tackling large coding projects using Claude Code's plan mode. I demonstrate how to start with a rough dictated prompt, use plan mode to explore the codebase and generate clarifying questions, and break complex work into multi-phase plans that can span multiple context windows. I show my custom rules configuration that keeps plans concise and adds unresolved questions, how to monitor context usage throughout implementation, and my strategy of storing plans as GitHub issues to preserve them across context resets. This approach combines upfront planning with aggressive auto-accept during implementation phases, allowing AI to handle substantial features while maintaining control and code quality. I share practical tips including my favorite concision rule, the benefits of multi-phase planning, and how to effectively manage context windows for large projects.

Join my newsletter on AI Hero:

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MIT 15.401 Finance Theory I, Fall 2008
View the complete course: http://ocw.mit.edu/15-401F08
Instructor: Andrew Lo

License: Creative Commons BY-NC-SA
More information at http://ocw.mit.edu/terms
More courses at http://ocw.mit.edu

🔥Agentic AI Training Course - Master AI Agents: https://www.edureka.co/agentic-ai-training-course

Explore the future of artificial intelligence with Agentic AI! In this video, we dive into the exciting developments and advancements that are set to shape the industry in 2025. We will learn what Agentic AI is and how it goes beyond traditional AI by acting with purpose and autonomy. You’ll discover 5 powerful secrets behind Agentic AI—from multi-agent collaboration to real-world tool integration and ethical guardrails. By the end, you’ll understand how Agentic AI is transforming industries and why it’s the future of intelligent systems.

Join us as we discuss the latest trends, innovations, and predictions for Agentic AI in 2025. Whether you're an AI enthusiast, a business leader, or simply curious about the future of technology, this video is for you. Stay ahead of the curve and discover what's next for Agentic AI!

00:00:00 Introduction
00:17:13 What is Agentic AI?
00:36:19 Agentic AI vs Generative AI
00:46:07 Agentic AI Roadmap
00:52:18 Introduction to Artificial Intelligence
00:58:37 Introduction to Deep Learning
02:28:29 Artificial Neural Network
03:08:09 Transformers Explained Using Generative AI
03:09:37 Transformers Neural Networks Explained
03:21:52 What are Large Language Models?
03:38:17 LLM vs SLM
03:41:59 What is LangChain?
03:59:35 What is RAG?
04:22:07 LLMOps: The Future of AI Development
04:29:57 Prompt Engineering
04:42:41 Natural Language Processing (NLP) & Text Mining using NLTK
05:22:21 KNN Algorithm using Python
05:45:23 Alibaba’s Qwen 2.5-Max Just Beat GPT-4 & DeepSeek?
05:49:47 DeepSeek vs OpenAI: Who Wins the AI Race?
06:02:06 Deep Learning Interview Questions

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𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬

🔵 DevOps Online Training: http://bit.ly/3VkBRUT
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🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐑𝐨𝐥𝐞-𝐁𝐚𝐬𝐞𝐝 𝐂𝐨𝐮𝐫𝐬𝐞𝐬

🔵 DevOps Engineer Masters Program: http://bit.ly/3Oud9PC
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🔵 Python Developer Masters Program: http://bit.ly/3EV6kDv


🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐔𝐧𝐢𝐯𝐞𝐫𝐬𝐢𝐭𝐲 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐬

🔵 Post Graduate Program in DevOps with Purdue University: https://bit.ly/3Ov52lT

🌕 Advanced Certificate Program in Data Science with E&ICT Academy, IIT Guwahati: http://bit.ly/3V7ffrh

🔵 Advanced Certificate Program in Cloud Computing with E&ICT Academy, IIT Guwahati: https://bit.ly/43vmME8

📌𝐓𝐞𝐥𝐞𝐠𝐫𝐚𝐦: https://t.me/edurekaupdates
📌𝐓𝐰𝐢𝐭𝐭𝐞𝐫: https://twitter.com/edurekain
📌𝐋𝐢𝐧𝐤𝐞𝐝𝐈𝐧: https://www.linkedin.com/company/edureka
📌𝐈𝐧𝐬𝐭𝐚𝐠𝐫𝐚𝐦: https://www.instagram.com/edureka_learning/
📌𝐅𝐚𝐜𝐞𝐛𝐨𝐨𝐤: https://www.facebook.com/edurekaIN/
📌𝐒𝐥𝐢𝐝𝐞𝐒𝐡𝐚𝐫𝐞: https://www.slideshare.net/EdurekaIN
📌𝐂𝐚𝐬𝐭𝐛𝐨𝐱: https://castbox.fm/networks/505?country=IN
📌𝐌𝐞𝐞𝐭𝐮𝐩: https://www.meetup.com/edureka/
📌𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐭𝐲: https://www.edureka.co/community/

- - - - - - - - - - - - - -

What is Agentic AI?
Agentic AI refers to artificial intelligence systems that can autonomously make decisions, take actions, and pursue goals with minimal human intervention. Unlike traditional AI, which adheres to predetermined rules, agentic AI may dynamically adapt to new situations. It is widely utilized in robotics, virtual assistants, self-driving cars, and sophisticated decision-making processes.

What are the prerequisites for this Agentic AI Training Course?
In order to complete this course successfully, participants need to have a basic understanding of the Python programming language, machine learning, deep learning, natural language processing, generative AI, and prompt engineering concepts.

Who should take this AI Agents Training Course?
The Agentic AI online Training Course is ideal for AI enthusiasts, developers, and professionals looking to build autonomous AI agents. It is best suited for LLM Engineers, Generative AI Engineers, AI Research scientists, AI/ML practitioners, and freshers who want to leverage Agentic AI for automation and decision-making.

For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: +18885487823(toll-free).

#agenticai #aiagents #agenticaicourse #generativeai

In this video we go through the most basic and essential tensor operations that really build the foundation to TensorFlow 2.0 and is important to know before moving on to building neural networks which we will start with in the next tutorial! :)

Knowledge in Linear Algebra is very important to have an easier time understanding many tensor operations we go through so I would view as a prerequisite. I think if you don't have that then this series by 3Blue1Brown can be helpful:
https://www.youtube.com/playli....st?list=PLZHQObOWTQD

I learned a lot and was inspired to make these TensorFlow videos by the TensorFlow Specialization on Coursera. Below you'll find both affiliate and non-affiliate links, the pricing for you is the same but a small commission goes back to the channel if you buy it through the affiliate link.
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TensorFlow Playlist:
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OUTLINE:
0:00 - Introduction
0:48 - Imports
2:21 - Initialization methods for Tensors
8:34 - Casting to different types
9:36 - Mathematical Operations
15:16 - Indexing a Tensor
19:18 - Reshaping a Tensor
20:40 - Ending words

Reviewing Lambda and Razer's Tensorbook, a laptop aimed at deep learning, with 16GB of VRAM (GPU memory), 64GB of RAM, 2TB of NVMe storage and an 8-core intel i7 11800H CPU.
https://lambdalabs.com/deep-le....arning/laptops/tenso

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