The Build - Ai dev and product show.

Cameron Rohn and Tom Spencer

Weekly deep dives on the most interesting dev, ai and product releases, research updates and emerging trends in the AI engineering, agent development and software industry.

Episodes

  1. 16 AUG

    Ep 12 - GPT 5 Post hype, Groq Desktop, LangChain DeepUi and Social Agent

    Lots of demos, deep discussions and ai injections. Check the vault for the show notes, links and more at buildaipod.com Chapters00:00 Introduction and Personal Updates00:46 Diving Deeper into GPT-5 Features and User Reactions01:48 Comparing GPT-5 with Previous Models04:08 User Feedback and Market Reactions06:37 Final Thoughts on GPT-5 and Future Directions10:57 Navigating Coding Agents and Abstraction Layers13:40 The Evolution of GPT Models and Their Applications18:07 Inference Compute and the Future of AI Investment19:57 Exploring Grok Desktop and Its Features27:25 Interoperability and Customization in AI Tools35:22 Introducing the Vault: A Centralized Resource for AI Applications42:02 Exploring Deep Agents and UI45:28 Running Deep Agents Locally47:19 Enhancing User Experience with UI Components50:13 Integrating Claude Code with Deep Agents56:37 Transitioning to Social Media Agents57:43 Complexity of Social Media Agent Architecture01:04:10 Monitoring and Managing Social Media Agents01:09:25 Streamlining Content Generation Processes01:12:54 Optimizing Code Repositories for AI Agents01:13:58 Navigating Corporate Culture Shifts01:16:49 Exploring Options Trading with AI01:22:47 Integrating AI with Financial Data01:28:42 Full Loop Development in AI Projectssign up to the vault to get all the details about the show - buildaipod.com

    1h 36m

  2. 8 AUG

    EP 11 - Open ai OSS via open coder, Langchain open SWE, local inference with ollama turbo, virtual audiences content testing

    We recorded August 7th, right before ChatGPT launched. We dove into GPT open source, OpenCode, Ollama Turbo, and deep agent setups. I wanted to see LangChain’s open suite and test agent environments. OpenCode stood out for its flexibility — multiple model providers, easy local setup, works with Ollama Turbo for $20/month. LM Studio runs similarly. I’m considering a high-spec NVIDIA rig and DGX Spark for local inference. GPT-OSS is cheap, fast, and excellent for coding and tool-calling, but weaker on general knowledge. Running it locally means more setup work but more control. Hybrid local-plus-cloud routing feels inevitable. We demoed OpenAgent Platform — fast, multi-provider agents without writing code. Then explored LangChain SWE — an open-source, multi-threaded coding agent with planner/programmer loops, GitHub integration, Daytona sandboxes, and detailed token-cost tracking. We looked at Vercel’s v0 API for quick generative UI, and the potential to run it privately for internal teams. I closed with Google’s upcoming AI-mode ads and Societies.io — a virtual audience simulation tool for testing and optimizing content before publishing. Chapters 00:00 Introduction to ChatGPT Launch and Demos 01:40 Exploring Open Code and LangChain 04:37 Local Inference and Olamma Integration 07:25 Cloud Acceleration with Turbo Service 10:11 Open Source Model Benchmarks and Feedback

    1h 39m

  3. 3 AUG

    EP - 10 - Claude Code Sub Agents Demo and Deep Dive

    Notes to come.

    1h 42m

  4. 1 AUG

    EP - 10 - Part 1 - Ai Labs Open Source Crushing It, Alpha Earth, Claude Code Sub Agents and GTP5 coming soon

    Part one of two, for this week's show. Updates , links and notes coming soon. Check out buildaipod.com and the Vault for all the details.

    1h 4m

  5. 25 JULY

    EP - 9 - AI Exec Orders, Qwen 3 Coder, JSON Veo3 Demo and Graph RAG Deep Dive with Neo4J

    In this episode, we dive into the latest AI news, covering new open-source models like Qwen3 Coder and OpenAI's new agent. We discuss a major AI breakthrough at the Math Olympiad, where models achieved gold medal scores, and unpack recent AI executive orders from the Trump administration. In our demo segment, we show how to use JSON for ad vanced AI video generation. We also introduce "The Build Vault," our new project for creating a searchable knowledge base from our podcast content using tools like LangGraph and Neo4j. Chapters 00:04:42 - New Open-Source AI Models00:13:45 - AI Wins Gold at the Math Olympiad00:22:42 - Trump Administration's New AI Policies00:40:48 - Demo: Advanced AI Video Generation with JSON01:00:25 - Introducing "The Build Vault"01:09:25 - How We Built the Vault: GraphRAG & Demos Insights The pace of AI development is accelerating faster than predicted, especially in complex reasoning.Training AI agents in virtual, sandboxed environments is becoming a new industry standard.Structured data like JSON provides granular control for getting better results from creative AI models.New government policies are set to significantly impact AI development, data center construction, and federal use.Knowledge graphs and retrieval-augmented generation (RAG) are powerful techniques for building intelligent apps on top of unstructured data. Keywords Qwen3 CodaOpenAI AgentJSON Veo3AI PolicyLangGraphNeo4jGraphRAGMCP 📢 Show Links📰 News & Updates Advanced version of Gemini with Deep Think (IMO Gold Medal – DeepMind) QWEN3 Coder ModelStudio Console WebDev Arena Introducing ChatGPT Agent (OpenAI) Model training in simple terms 🏛️ Executive Orders Promoting The Export of the American AI Technology Stack Accelerating Federal Permitting of Data Center Infrastructure Preventing Woke AI in the Federal Government 🧪 Demos and Discussion Veo3 JSON mode – Examples, Templates and Docs JSON Veo App JSON Veo App – GitHub The Build Vault The Build Podcast – GitHub Jupyter Notebook Embeddings Demo AssemblyAI

    2h 3m

  6. 19 JULY

    Ep 8 - Kimi2, Is RAG still a thing? and the coming SaaS bloodbath.

    Tom and Cam explore recent AI advancements, with particular focus on the Kimi model, its capabilities, and developer implications. They address SaaS industry challenges, including rising customer acquisition costs and the trend toward consumption-based pricing models. The conversation highlights developers' growing influence in AI technology development and the critical role of customer retention in SaaS business success. They also discuss enterprise AI adoption, RAG (Retrieval-Augmented Generation) applications, and effective data vectorization techniques. Additional topics include Cognition's acquisition of Windsurf, the continuing importance of ETL processes, and how local models can improve data processing efficiency. Throughout their discussion, they emphasize the value of layered data management approaches and how traditional methods remain relevant alongside emerging technologies. Chapters 00:00 Introduction and Technical Setup03:56 Exploring the Kimmy Model15:46 Developer-Centric AI Models23:25 Rapid Development in AI Tools25:00 Exploring Kimmy's Capabilities29:21 SaaS Industry Challenges and Changes33:23 Customer Acquisition Cost Insights38:13 The Future of SaaS in an AI-Driven World42:47 RAG and Vectorization in AI Development59:18 Understanding UMAP and Clustering in Data Representation01:02:14 Building a Mobile Inspection Tool for Real Estate01:05:23 Transforming Natural Language into Structured Data01:09:46 The Importance of ETL Processes in AI01:14:50 Defining Effective ETL Pipelines01:20:23 Exploring RAG and Its Applications01:28:39 The Role of Vector Stores in Data Management Links https://github.com/lmcinnes/umap https://www.nomic.ai https://pair-code.github.io/understanding-umap/ https://www.pinecone.io/ https://superlinked.com/ https://www.meilisearch.com/ https://www.pinecone.io/learn/vector-database/ LLM vectorization - https://bbycroft.net/llm UMAP - Vizualisation of embeddings, Nomic Atlas Vizualisation - https://atlas.nomic.ai/data/andrewgao22/hacker-news/map https://projector.tensorflow.org/ Example Superlinked Demo -https://hotel-search-recipe.superlinked.io/ https://docs.unsloth.ai/basics/kimi-k2-how-to-run-locally https://developers.googleblog.com/en/gemini-embedding-available-gemini-api/ https://moonshotai.github.io/Kimi-K2/ https://platform.moonshot.ai/docs/introduction#text-generation-model https://docs.superlinked.com/getting-started/why-superlinked Keywords AI, Kimi2 Model, SaaS, Technology, Coding, Developer Tools, Machine Learning, Open Source, API, Performance, SaaS, AI adoption, cloud computing, RAG, vectorization, ETL, Cognition, Windsurf, local models, data processing

    1h 25m

  7. 13 JULY

    EP 7 - A2A, Agent Dev Kit Deep Dive and Demos, Grok 4, Gemini Chrome Nano

    We chat through Grok 4 and Vending Bench, Chrome with Nano, Comet from Perplexity, A2A and the ADK kit and more from the AI, Agent engineering world. Chapters 00:00 Introduction 00:34 Grok 4, Vending Bench 06:25 Vending Bench Benchmarking 09:43 Replit brings the Vibes to Microsoft 18:05 Browser wars, Nano in Chrome and Comet launch 29:00 Understanding A2A Protocol and Agent Development Kit 31:34 Agents as Problem Solvers vs Tools 37:29 Agent Card Specifications and Metadata 42:27 Robustness and Reliability of A2A Protocol 51:06 Practical Applications and Code Demonstration 57:47 Understanding Agent Communication and Debugging 01:06:42 Agent Cards and Composability in Development 01:13:20 Demonstrating the A2A Web Application 01:15:17 Exploring JavaScript Agents and Orchestrator Functionality 01:20:41 Connecting Agents for Travel Planning 01:23:12 Clarifying User Interactions in Travel Booking 01:26:25 Introducing the Build Vault and RAG Agents 01:27:12 Video Agent Demonstration and Challenges 01:36:59 Future Integrations and Closing Thoughts

    1h 28m

  8. 7 JULY

    EP 6 - Agentic Medical AI, Claude’s Desktop Tools & The OpenRouter Mystery Model

    In this episode of The Build, Tom Spencer and Cameron Rohn break down some of the biggest developments in AI infrastructure, medical reasoning, and agent deployment. 🏥 Highlights: • Microsoft’s Agentic Medical AI paper and how LangGraph + Claude replicated the architecture • Claude’s new MCP desktop apps — AI agents as drag-and-drop tools • A mysterious new OpenAI model on OpenRouter with a 1M token context window • Cloudflare’s LLM paywall and “House of Mirrors” tech to trap AI crawlers • HIPAA-compliant retrieval with OpenEvidence • Local model deployments with Gemma 3n and hybrid edge computing • How startups are balancing inference cost vs. data infra as AI matures👀 Resources Mentioned: • Microsoft’s blog: https://microsoft.ai/new/the-path-to-medical-superintelligence/ • Cypher Alpha model on OpenRouter: https://openrouter.ai/openrouter/cypher-alpha:free • OpenEvidence: https://www.openevidence.com/ • State of AI 2025 (ICONIQ): https://www.iconiqcapital.com/growth/reports/2025-state-of-ai • LangGraph repo: https://github.com/langchain-ai/langgraph • MedAgent demo code: https://github.com/The-Build-Podcast/mediagent 🔧 Code + Demos:→ GitHub: https://github.com/The-Build-Podcast → LangGraph + Claude demo walkthrough→ LangSmith traces and architecture diagrams Chapters 00:00 Introduction and Overview 02:40 Microsoft Medical Agent Diagnosis 04:07 Claude AI and Desktop Applications 06:49 OpenAI and Competitive Landscape 09:23 State of AI Report Insights 17:58 Data Storage and Processing Costs 20:52 Cloudflare Innovations and AI Crawlers 30:29 The Explosion of AI Models 31:54 Exploring Multimodal Models 34:40 The Rise of Local AI Models 35:13 Innovations in On-Device AI 39:22 The Future of AI in Healthcare 45:53 AI in Medical Diagnostics 53:32 Limitations and Future Directions 58:11 Evaluations and Methodologies in AI 59:44 LangGraph and Langsmith Integration 01:01:05 Building a Medical Diagnostic Agent 01:04:59 Chain of Debate in Medical Diagnostics 01:08:22 Iterative Development and Debugging 01:12:55 Customizing Agent Architectures 01:18:55 Performance and Reasoning in AI Models 01:25:14 Future of AI in Medical ApplicationsShow Links https://openrouter.ai/openrouter/cypher-alpha:free https://www.openevidence.com/ https://www.iconiqcapital.com/growth/reports/2025-state-of-ai https://microsoft.ai/new/the-path-to-medical-superintelligence/ https://epoch.ai/data/large-scale-ai-models https://www.linkedin.com/posts/tomasztunguz_remember-when-you-took-a-family-photo-ghibli-styled-activity-7343312053211734016-TcVU https://lancedb.com/ https://theory.ventures/ https://www.cloudflare.com/en-au/press-releases/2025/cloudflare-just-changed-how-ai-crawlers-scrape-the-internet-at-large/ https://github.com/The-Build-Podcast https://microsoft.ai/new/the-path-to-medical-superintelligence/ https://arxiv.org/abs/2506.22405 https://github.com/The-Build-Podcast/mediagent

    1h 34m

  9. 2 JULY

    EP 5 - The Build - Agent Architectures: The Next Frontier in AI

    Explore the future of AI agent architectures with Tom Spencer and Cameron Rohn. This deep-dive covers the power of multi-agent systems, from swarm intelligence to advanced agent collaboration, and how to build them using cutting-edge tools like LangChain, LangGraph, and the Model Context Protocol (MCP). Learn about the intersection of AI and cybersecurity, context management in LLMs, and the agentic workflows shaping the next wave of software development.🎙️ Hosts:• Tom Spencer: https://tomspencer.co• Cameron Rohn: https://cameronrohn.comCHAPTERS00:00 Intro: The Rise of AI Agents & Overview01:26 What are the latest developments in Model Context Protocol (MCP)?03:38 What were the key AI takeaways from Vercel Demo Day?06:14 How is AI creating a new frontier for SEO and AEO?11:32 How is content optimization evolving with AI?15:49 What is Vercel's role in modern AI application development?18:33 Which emerging tools and technologies are defining the space?22:44 What are the most effective agent communication protocols?26:43 How do AI and cybersecurity intersect in agentic solutions?34:52 How do current video models perform for content generation?37:39 What is the evolution of content production models?39:21 How can prompting techniques be refined for better AI results?41:22 What is the current state of text generation in video models?42:39 Where is OpenAI focusing its efforts for future video models?43:03 Diving into Agent Architectures44:52 Contrasting Perspectives on Agent Structures49:44 Navigating Errors in Multi-Agent Systems52:25 Understanding Swarm Architectures56:43 Complexity in Agent Interactions01:02:49 Introduction to MCP Tools and Agent Swarm01:04:09 Applications and Composability of Agents01:07:08 Marketplace of Agents and Microservices01:08:41 Context Degradation and Output Management01:10:38 Multimodal Agent Execution and Creative Work01:14:48 Deep Research with Langchain and Agent Architecture01:26:42 Multi-Agent Workflows and Practical Applications01:28:15 Understanding LLM Queries and Reports01:30:24 Context Engineering: Insights and Developments01:34:24 Evaluating AI Outputs and Traces01:38:36 Applications of AI in Real Estate and Research01:49:10 Building Effective AI Agents and Strategies🔗 Resources & Links Mentioned: • LangChain Blog on Multi-Agent Systems: https://blog.langchain.com/how-and-wh...• Cognition AI on Agent Architectures: https://cognition.ai/blog/dont-build-...• LangChain Open Deep Research Repo: https://github.com/langchain-ai/open_...• OpenAI Cybersecurity Agents Demo: https://github.com/openai/openai-cs-a...• LangGraph MCP Server Concepts: https://langchain-ai.github.io/langgr...• Cameron Rohn's MCP Server Demo: https://github.com/Cam10001110101/mcp...📌 Topics Covered:• Multi-Agent Systems & Swarm Intelligence• AI Agent Architecture & Collaboration• LangChain, LangGraph, and MCP Tools• Agentic Workflows & Context Management• AI in Cybersecurity & Threat Detection• AI for SEO (AEO) & Content Optimization• Deep Research Agents & Multimodal Execution• AI Applications in Real Estate🔔 Subscribe to The Build Podcast for more deep dives into the world of AI and software development! Like this video if you found it valuable and let us know your biggest takeaway in the comments below.#AIAgents #LangChain #TheBuildPodcast

    1h 51m

  10. 13 JUNE

    EP 4 - The Build - ChatGPT MCP, Where to look for agents and and VR updates

    Links from the show NAICS Analysis - A16Z - https://a16z.com/vsaas-vertical-saas-ai-opens-new-markets/  Codes - https://www.census.gov/naics/  https://github.com/BenDoyle/NAICS/blob/master/naics.csv ONet - Tasks - http://onetonline.org/link/summary/11-2022.00 https://www.anthropic.com/economic-index https://www.anthropic.com/news/the-anthropic-economic-index https://huggingface.co/datasets/Anthropic/EconomicIndex https://arxiv.org/html/2503.04761v1

    2h 10m

  11. 30 MAY

    E2 - Claude 4, Creative Tools and AI Memory

    Cameron Rohn and Tom Spencer explore the latest in AI—from voice assistants and generative tools to no-code platforms and agentic systems. They unpack challenges in AI memory, Claude 4 and the growing role of AI in creative workflows. Chapters 00:00 Introduction to Voice AI and Creative Tools 02:55 Deep Dive into Creative Tooling and Updates 05:46 Exploring Vercel and Figma's New Features 08:41 Gumloop and the Future of No-Code Solutions 11:30 Linear Agents and Their Impact on Development 14:23 Agentic Systems and Long-Running Workflows 17:18 The Importance of Benchmarks in AI 20:22 Impact of AI on Professional Services 23:12 Claude 4: Features and Economic Impact 26:01 System Prompts and Their Role in AI Behavior 35:33 Building Memory Engines in AI 37:44 The Art of Directing AI Responses 41:34 Understanding System Prompts and Tool Calls 45:18 The Impact of Package Choices on AI Outputs 49:02 Navigating Memory in AI Systems 58:29 The Future of Personalized AI Experiences 01:07:49 Exploring Memory in AI and Human Cognition 01:12:05 The Evolution of Generative AI Tools 01:15:06 Understanding Diffusion Models and Their Impact 01:20:24 The Future of Video Generation and AI 01:25:18 The Intersection of AI and Creative Expression 01:41:46 Exploring Interactive Animation with Remotion 01:44:27 Advancements in Interactive Environments 01:48:22 The Future of Creative Control in Video Production 01:53:47 Emerging Technologies: Neural Radiance Fields 01:57:48 The Metaverse and Its Implications for Creativity 02:01:11 The Evolution of Marketing and Technology Careers https://www.anthropic.com/research/tracing-thoughts-language-model https://www.tbench.ai/ https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B System Prompt Leaks - https://github.com/elder-plinius/CL4R1T4S/tree/main https://www.youtube.com/watch?v=ugvHCXCOmm4 Triplex.com https://x.com/noahmacca/status/1927014156152058075 https://platform.openai.com/docs/guides/evals   https://x.com/ns123abc/status/1927491593181004212   https://docs.anthropic.com/en/docs/build-with-claude/extended-thinking#interleaved-thinking https://every.to/chain-of-thought/vibe-check-claude-4-sonnet   https://x.com/simonw/status/1926636807875158060  https://huggingface.co/datasets/Anthropic/model-written-evals  https://github.com/anthropics/evals   https://www-cdn.anthropic.com/6be99a52cb68eb70eb9572b4cafad13df32ed995.pdf   https://huggingface.co/datasets/Anthropic/hh-rlhf  https://huggingface.co/Anthropic  https://www.tbench.ai/about https://assets.anthropic.com/m/2e23255f1e84ca97/original/Economic_Tasks_AI_Paper.pdf https://huggingface.co/datasets/Anthropic/EconomicIndex https://app.ltx.studio/motion-workspace https://www.florafauna.ai/ Fal.ai https://www.youtube.com/watch?v=UwvlPkAFx1Q https://remotion.dev/ https://github.com/pmndrs/react-three-fiber https://triplex.dev/ https://docs.nerf.studio/ https://deepmind.google/models/veo/ https://github.com/Vchitect/VBench gumloop.com linear.com

    2h 7m
  12. Ep 01 - LangChain Interrupt Drops, Google & Microsoft releases, and Daytona demo deep dive.

    23 MAY

    Ep 01 - LangChain Interrupt Drops, Google & Microsoft releases, and Daytona demo deep dive.

    Join hosts Cameron Rohn and Tom Spencer for the inaugural episode of their weekly AI deep dive! Chapter Links 00:00 Intro 00:35 LangChain Interrupt Conference Recap 03:00 Ambient Agents in High-Risk Use Cases 04:45 LangChain Product Updates: LangGraph & LangSmith 06:00 LangGraph Platform and Prebuilt Agent Marketplace 07:45 LangChain's MCP Integration and Cloud Desktop Demo 09:00 Keynote Themes: Evals and Agent Simplicity 10:45 Open Evals and "LLM as a Judge" Concepts 12:00 Agent Inbox and Email Task Manager Demo 13:45 Human-in-the-Loop UX and LangGraph Publishing 15:00 Agent Engineer as a New Role 16:30 Architectural Standards and LangGraph Adoption 18:00 Interesting Talks: Docet ETL and Data Challenges 21:00 Greg Kamradt, Arch Prize, and Context Engineering 23:15 Devon's Deep Wiki and Contextual Agents 25:00 Google’s Gemini 2.5 Pro and Diffusion LLMs 27:30 Google Labs: VEO V3, Flow, and Creative Tools 29:30 SynthID, Agent UX, and Agent Mode OS Concepts 31:00 Microsoft’s Ecosystem: Teams, MCP, and Identity 33:15 MCP Native to Windows & Local Development 35:00 Daytona, Cloudflare Sandboxes, and Remote Agents 38:00 Cloud Execution Environments and Security 40:00 One-Time Use Software and Just-In-Time Apps 42:00 LangGraph Prebuilts and Computer Use Agents 44:00 AI Containers, Sharing Memory & Swarm Architectures 47:00 Outlook on Supervisor Models vs Workflow Models 49:00 Wrap-Up and Final Thoughts on the Agent Ecosystem Overview They kick things off by unpacking the flood of insights from the recent LangChain 'Interrupt' Conference in San Francisco. Discover how agents are being trusted in high-stakes scenarios like finance, and why 'Agent Engineering' might be the next big role. They cover LangChain's latest product launches, including LangGraph Platform and Agent Inbox, and its surprising lead over OpenAI in SDK downloads. Major announcements from Google and Microsoft's strategy, focusing on its ecosystem, AI Foundry, and building MCP (Multi-Agent Collaboration Protocol) natively into Windows and Teams. Finally, the duo gets hands-on, discussing and demoing remote AI sandboxes. They explore tools like Daytona, Cloudflare's upcoming containers, E2B, and Scrapybara, showing how these environments enable complex, secure, and even disposable AI applications. Plus, catch their live reaction as Anthropic appears to launch Claude 4 during the recording! Key Discussion Points: LangChain Conference Recap: Key themes (Simplicity, Agents, Evals), new products (LangGraph Platform, Agent Inbox, Pre-builts), MCP integration, and the Agent Engineer role.Google AI Updates: Scale, Gemini 2.5 Pro, Diffusion LLMs, Veo, AI Labs, Agent Mode, and Synth ID.Microsoft AI Strategy: Open source push, MCP in Windows, Teams integration, and the power of their identity ecosystem.OpenAI News: Acquisition of Jony Ive's IO startup.AI Tools & Demos: DocETL, Deep Wiki, NL Web, and a live demo of AI agents in Daytona remote sandboxes.The Future: Agent-to-Agent (A2A) communication challenges, the impact of remote execution environments, and the announcement of Claude 4. Mentioned Links & Resources: LangChain: https://www.langchain.com/LangGraph: https://github.com/langchain-ai/langgraph Agent Inbox: https://github.com/langchain-ai/agent-inbox DocETL: https://github.com/ShreyaGanesh/DocETL Deep Wiki (Devin): https://github.com/devin-ai/deep-wiki NL Web (Microsoft): https://github.com/microsoft/NL2Web Google AI Labs: https://labs.google/ Daytona: https://daytona.io/ E2B: https://e2b.dev/ Scrapybara: (Link Needed) Claude (Anthropic): https://www.anthropic.com/claude Follow Cameron & Thomas: Cameron Rohn: https://cameronrohn.com/ LinkedIn GitHub X YouTube Thomas Spencer: tomspencer.co https://linkedin.com/in/tomspencerdigital https://github.com/spencerthomas https://x.com/surfcodetom https://www.youtube.com/@tomspencer1286

    1h 50m
  • 12 Episodes

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Weekly deep dives on the most interesting dev, ai and product releases, research updates and emerging trends in the AI engineering, agent development and software industry.

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