הפודקאסטים הטובים ביותר ב-Scale (2025)

1
56 - n8n | Shay Shitrit 23:56

12d ago23:56

23:56

Getting started with no-code agentic automations, popular use cases and tips

1
55 - Context Engineering 29:10

1M ago29:10

29:10

The state of best practices for context engineering, focused on AI-coding as a leading use case

1
54 - Permissions | Or Weis (Permit.io) 23:44

2M ago23:44

23:44

Enabling secured flexibility to your agents and MCP servers

1
53 - Search & Retrieval | Guy Itach (Fiverr) 28:19

2M ago28:19

28:19

techniques to combine classic search with agentic retrieval

1
52 - Agents at scale | Adam Cohen Hillel 28:14

3M ago28:14

28:14

The story of building Suna - the open source alternative of Manus the generalist autonomous agenthttps://github.com/kortix-ai/suna

1
51 - Our AI-driven coding workflow | Oren Melamed 30:58

4M ago30:58

30:58

Sharing our workflow with Cursor, Claude Code, GitHub Copilot and others. Listed the useful MCPs and tools, how to measure efficiency gains, and our vision for the future of coding

1
50 - A2A protocol 20:37

4M ago20:37

20:37

Is this Agent2Agent new protocol by Google going to be the next MCP?

1
49 - Documents analysis 23:40

4M ago23:40

23:40

How to handle long docs like PDF and Docx effectively with LLMs

1
48 - Vibe coding | Sahar Carmel 30:12

5M ago30:12

30:12

Tips for AI-driven coding

1
47 - Tech stack for Agents 31:01

6M ago31:01

31:01

Python or JS? LangChain or Vanilla? In this episode we gave guidelines on important things to notice when picking a tech stack for new project or a company's platform

1
46 - Building coding multi-agent (LangTalks '25 conf) 37:23

6M ago37:23

37:23

Building SWE multi-agent with LangGraph: Zero to Hero | Lee & Gal (LangTalks GenAI 2025 Conference)Lecture video:https://www.youtube.com/watch?v=KroPK5DygWwRepo:https://github.com/langtalks/swe-agent

1
45 - AI PM: Spec for copilot feature 29:55

7M ago29:55

29:55

Example of product specification required from an AI PM for a new feature

1
44 - MCP intro 19:57

7M ago19:57

19:57

all you need to know about MCP and how to get started as a developer

1
43 - Building with GenAI-powered tools | Idan Benaun 33:05

8M ago33:05

33:05

this episode has 2 aspects - best practices to start a new product in 2025 and what tools can accelerate your process

1
42 - Text to SQL 23:45

9M ago23:45

23:45

how to build a text to sql agent

1
41 - GraphRAG 15:36

10M ago15:36

15:36

Deep dive on why GraphRAG approach was created and how it works

1
40 - Advanced RAG | Nir Diamant 27:20

12M ago27:20

27:20

advanced RAG techniques like RAPTOR and using Clues

1
39 - Code generation agents | Ziv Bakhajian 25:13

1y ago25:13

25:13

Cursor, RepoAgent, Aider, and some more coding agents - overview and interesting architectural concepts

1
38 - OpenAI Realtime API 18:57

1y ago18:57

18:57

Technical review of the new Realtime API introduced on the dev day

1
37 - Upgrading LLM | Dolev Pomeranz (Gong) 31:33

1y ago31:33

31:33

How to migrate the llm provider in your AI app safely

1
36 - MVP with open-source LLM | Yael Daihes (Anecdotes) 28:22

1y ago28:22

28:22

If you need to build an llm-app that uses an open-source llm, this episode is for you. Intermediate level

1
35 - LLM app dev guide | Almog Baku 28:04

1y ago28:04

28:04

end to end guide on how to get started and deploy to production your llm app

1
34 - Legal documents | Yaron Vazana (Darrow) 26:25

1+ y ago26:25

26:25

Build LLM-app with legal documents that have many references and domain verbiage

1
33 - LangGraph | Eden Marco 27:09

1+ y ago27:09

27:09

Getting started with LangGraph, the most popular multi agent framework

1
32 - AI PM: No-code Tools | Galit Galperin 28:44

1+ y ago28:44

28:44

Utilize no-code tools for fast POCs

1
31- Multi agents | Assaf Elovic ("GPT Researcher") 27:31

1+ y ago27:31

27:31

Review of why and how to build a multi-agent system. Assaf is Head of R&D @ Wix and GPT-researcher open source creator.

1
30 - Open Source Security | Avi Lumelsky (Oligo) 27:52

1+ y ago27:52

27:52

everything about adopting open source code and models for your llm app

1
29 - AI PM: trust & evaluation | Shira Weinberg Harel 28:12

1+ y ago28:12

28:12

build trust with users and stakeholders - transparency and explainability, reliability and consistency (how to fail safely), automation vs user control.how to evaluate with uncertainty, prompt engineering, effective bug reports

1
28 - Advanced agents 29:34

1+ y ago29:34

29:34

examples and practices of advanced agents, and use of LangGraph for effective tool usage by agents

1
27 - Latency optimization | Dor Ringel 27:26

1+ y ago27:26

27:26

how to solve latency issues with minimal compromise on quality and cost

1
26 - 12 RAG Pain Points and Proposed Solutions 30:40

1+ y ago30:40

30:40

The 12 most common challenges around building an effective RAG pipeline and the best practices for solutions

1
25 - Reranking 24:53

1+ y ago24:53

24:53

exploring the reranker component in the 2 stage retrieval system

1
24 - MVP best practices 28:40

1+ y ago28:40

28:40

how to define effective requirements for llm apps, and first steps after going to production

1
23 - LLM theory | Mike Erlihson 33:16

1+ y ago33:16

33:16

What are transformers, why it is so expensive to train a Transformer-based model and what is the architecture of the future LLMs

1
22 - LangChain v0.1 24:19

2y ago24:19

24:19

LCEL, LangGraph, LangSmith

1
21 - Knowledge Graph | Jesús Barrasa (Neo4j, ENG) 35:59

2y ago35:59

35:59

Indexing knowledgebases with KG for RAG applications

1
20 - RAG Evaluation | Jonathan Yarkoni 25:58

2y ago25:58

25:58

ragas framework for evaluating unstructured retrievals and generations

1
19 - RAG 26:10

2y ago26:10

26:10

Retrieval Augmented Generation process, Llama index vs LangChain, indexing

1
18 - OpenAI Dev Day 28:11

2y ago28:11

28:11

OpenAI DevDay announcements recap

1
17 - Evaluation | Philip Tannor (DeepChecks) 29:54

2y ago29:54

29:54

Evaluating LLMs and AI pipeline in dev and production environments. How to work with datasets

1
16 - Multi modal 25:38

2y ago25:38

25:38

multimodality is a type of model that can analyze multiple data types like language, images, voice, etc.

1
15 - Initiatives and volunteers matching 17:53

2y ago17:53

17:53

Find the most suitable project for volunteer support "Iron swords" war efforts

1
14 - Prompt engineering 27:19

2y ago27:19

27:19

Advanced prompt engineering techniques: skeleton of thoughts, directional stimulus prompting, graph of thoughts, augmentations

1
13 - Production environment | Idan Tovi (Vee) 24:17

2y ago24:17

24:17

Full stack LLM app development, Typescript vs Python

1
12 - Fine-tuning | Mike Erlihson 27:41

2y ago27:41

27:41

Finetuning techniques (SFT, RLHF...), pros & cons, tools (technical episode)

1
11 - Open source models | Matan Kleyman 33:20

2y ago33:20

33:20

why should you care about open source models, when and how to finetune, inference best practices, deployment & serving tools, models overview

1
10 - Summarizing mental health sessions | Amit Spinrad (Eleos Health) 29:38

2y ago29:38

29:38

Drill down on a summarization task use case

1
9 - Popular tools for LLM-app devs 30:01

2y ago30:01

30:01

Save time building applications with LLMs by utilizing tools like LangChain, Llama index, Guidance, GPTCache and many more

1
8 - Vector Databases | Uri Goren (Argmax) 30:53

2y ago30:53

30:53

Why you might need a VectorDB, which features to consider when choosing a provider, and use cases examples

1
7 - Agents in LangChain | Eden Marco 28:47

2y ago28:47

28:47

From an agent POC with LangChain to production challenges

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