LangTalks

A behind-the-scenes look at real agentic-coding workflows: visual planning, cloud-first agents, ephemeral PR environments, custom skills, and secrets management.

How to market and sell to AI agents — discovery channels, CLI vs MCP trade-offs, authentication patterns, and the emerging agent-driven economy.

A practical, stage-by-stage look at running your entire development lifecycle with AI agents: from PRD to coding to QA.

A practical look at managing AI budgets across coding agents, customer-facing models, and production inference

Two real-world use cases are covered: CVE Enrichment for open-source vulnerability detection and real-time Malicious Command Detection, along with practical tips on cost optimization, prompt caching, and open-source vs. commercial model trade-offs.

Site Reliability Engineer agent auto fixes production issues

Measure the actual impact of adopting AI across the R&D

Singularity and AGI are around the corner.

How AI is used across the SDLC in a real R&D org - requirements, tech design, validation, testing, and code review. What worked, what didn’t, and where teams get stuck.

Building and testing voice agents with realtime API or chained approach (TTS->LLM->STT)

The Neuroscience behind the human brain and memories

the production experience and considerations for fine-tuning a small language model for narrow tasks

Recap of the major announcements and innovations from the 2025 re:Invent conference, along with our predictions for where things are heading in 2026

Short and long term memory mechanisms for agents

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

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

Enabling secured flexibility to your agents and MCP servers

techniques to combine classic search with agentic retrieval

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

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

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

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

Tips for AI-driven coding

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

Building SWE multi-agent with LangGraph: Zero to Hero | Lee & Gal (LangTalks GenAI 2025 Conference)

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

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

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

how to build a text to sql agent

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

advanced RAG techniques like RAPTOR and using Clues

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

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

How to migrate the llm provider in your AI app safely

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

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

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

Getting started with LangGraph, the most popular multi agent framework

Utilize no-code tools for fast POCs

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

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

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

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

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

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

exploring the reranker component in the 2 stage retrieval system

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

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

LCEL, LangGraph, LangSmith

Indexing knowledgebases with KG for RAG applications