Two Voice Devs

Mark and Allen

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Mark and Allen talk about the latest news in the VoiceFirst world from a developer point of view.

5 МАР.

Episode 270 - Beyond the Big Three: Open Models, Agents, & the Future of Devs

In part two of this insightful conversation, Allen and Sam Witteveen dive deep into the rapidly expanding world of AI models beyond the "big three." They explore the impact of open-weight and Chinese models like DeepSeek, Mistral, and Qwen, discussing their impressive efficiency and coding capabilities. The conversation shifts to the rise of agentic workflows and how tools like Claude Code are fundamentally changing the day-to-day lives of developers. They also tackle the tough questions: Are junior developers being replaced? Is AI just the next level of abstraction in programming? Finally, they cover the enterprise side of AI, from on-premise deployments to the evolving landscape of prompt engineering and observability frameworks like LangChain. Timestamps: [00:00:00] Introduction [00:00:49] Exploring Open Weights and Chinese Models [00:03:41] The Value of "Thinking" Models and Distillation [00:06:41] Running Models Locally [00:08:34] The Shift Towards Agentic Workflows [00:12:17] How AI is Changing the Role of Developers [00:29:04] AI as the Next Level of Abstraction [00:35:00] Best Models for Tool Calling and Coding [00:39:04] On-Premise Models and Enterprise Solutions [00:44:49] The Future of Prompt Engineering and LangChain [00:48:37] Outro and Where to Find Sam Hashtags: #TwoVoiceDevs #AI #OpenWeights #DeepSeek #Mistral #Qwen #ClaudeCode #Gemini #LangChain #SoftwareEngineering #AgenticAI #MachineLearning

49 мин.
3 МАР.

Episode 269 - The "Big Three" AI Models and Training Evolution

In Part 1 of a two-part series, guest host Sam Witteveen joins Allen to catch up and dive deep into the rapidly evolving world of AI models. Sam shares his fascinating journey from being a successful pop songwriter to becoming a Machine Learning Google Developer Expert (GDE) and running the massive Machine Learning Singapore meetup. The conversation shifts to the latest AI developments, exploring the "Big Three" model builders—Anthropic, OpenAI, and Google. Sam and Allen discuss the frenetic pace of new model releases, changes to the Gemini 3 API, and how developers navigate the trade-offs between intelligence, latency, and cost. Finally, they pull back the curtain on how these models are actually trained today. Discover why models are no longer trying to be "fact machines" and how post-training breakthroughs, code execution sandboxes, and Reinforcement Learning (RL) environments are dramatically improving AI capabilities. Stay tuned for the end of the episode, where they hint at what's coming in Part 2! Timestamps: [00:00:00] Introduction and catching up [00:01:33] Sam's fascinating journey from pop music to machine learning [00:05:23] Running the massive Machine Learning Singapore meetup [00:07:42] Stumbling into YouTube and teaching AI with Google Colab [00:12:38] Analyzing the "Big Three" AI models and rapid release cycles [00:17:52] Gemini 3 API updates, Flash models, and thinking levels [00:22:00] Tool use, knowledge cutoffs, and why LLMs aren't fact machines [00:26:00] How post-training and code sandboxes revolutionized AI [00:32:00] Scaling Reinforcement Learning (RL) environments for design [00:34:04] Structured outputs and the return to predictable rules [00:36:43] Tune in next time for more! And where to find Sam online Hashtags: #TwoVoiceDevs #AI #MachineLearning #DeepLearning #LLM #GoogleGemini #Gemini #OpenAI #ChatGPT #Anthropic #Claude #ReinforcementLearning #RAG #Developers #SamWitteveen

38 мин.
19 ФЕВР.

Episode 268 - The New @langchain/google Package

Allen has been busy! This week, he unveils the new `@langchain/google` package for LangChain JS. This major update consolidates five previous libraries into a single, standardized, and powerful tool for developers working with Gemini and Vertex AI. Allen walks Mark through the motivation behind the change, the focus on backward compatibility, and the exciting new features like simplified multimodal input/output and text-to-speech support. If you're building with Google AI and JavaScript, this is the update you've been waiting for. [00:00:57] The confusion of previous packages [00:02:52] Creating a unified package [00:03:45] Introducing @langchain/google [00:04:35] Backward compatibility [00:06:48] Multimodal inputs [00:07:54] Standardizing output and image generation [00:08:58] Text-to-Speech support [00:11:29] Simplifying parameters and reasoning [00:14:55] Future roadmap #LangChain #Gemini #NanoBanana #TextToSpeech #GoogleAI #JavaScript #TypeScript #VertexAI #OpenSource #AI #WebDevelopment #TwoVoiceDevs

18 мин.
6 ФЕВР.

Episode 267 - Behind the Scenes: How We Use AI to Build Two Voice Devs

Ever wonder how "Two Voice Devs" goes from a raw recording to a finished episode? In this episode, Allen Firstenberg takes Mark Tucker on a deep dive into his production workflow. They discuss how Descript’s text-based editing revolutionized their process, how Allen uses a custom Gemini CLI agent to automate show notes and descriptions, and the technical (and ethical!) journey of creating AI-generated thumbnails using Google's Nano Banana. It’s a candid look at how AI can act as a force multiplier for creators while keeping the "human in the loop." [00:00:01] Introduction and Check-in [00:01:27] Behind the Scenes: Why We Use AI [00:03:42] Descript: Text-Based Video Editing [00:05:24] Building a Knowledge Database from Transcripts [00:08:13] Editing Video Like a Document [00:12:34] Exploring Descript's AI [00:13:36] Automating Show Notes with Gemini CLI [00:14:10] The Power of System Instructions (GEMINI.md) [00:19:30] AI Thumbnail Generation with Nano Banana [00:26:10] The Ethics of Synthetic Media and Artistic Style [00:28:40] Keeping the Human in the Loop [00:33:00] Evolution of the Two Voice Devs Workflow #TwoVoiceDevs #PodcastProduction #GeminiAI #Descript #GeminiCLI #NanoBanana #Automation #ContentCreation #Ethics #GenerativeAI #AIWorkflow #PodcastEditing

37 мин.
29 ЯНВ.

Episode 266 - Supercharging Your AI Agent with Skills

Mark and Allen dive into the emerging world of Agent Skills, an open standard for extending the capabilities of AI coding assistants like GitHub Copilot, Claude Code, and Gemini CLI. They explore how these skills work, how they compare to the Model Context Protocol (MCP), and walk through creating and installing a custom skill using the `skills` CLI. They also discuss the skills.sh website by Vercel, which acts as a registry and leaderboard for the ecosystem. The conversation touches on the potential for standardization, the current fragmentation in the ecosystem, and critical security considerations for these powerful new tools. More Info: * https://agentskills.io * https://skills.sh * https://cra.mr/mcp-skills-and-agents [00:00:00] Introduction & Context: AI Agents and Tools [00:02:18] Getting Information into Context (Instructions files) [00:06:50] What are Agent Skills? (AgentSkills.io) [00:09:55] Agent Skills vs. MCP Servers [00:16:35] How Skills Work: Progressive Disclosure [00:19:50] Mark's Example: List Global NPM Skill [00:22:56] Installing Skills with skill.sh and the Skills CLI [00:26:55] Demo: Installing on GitHub Copilot [00:30:58] Demo: Installing on Gemini CLI [00:37:37] Discussion: Discovery, Standardization, and Security [00:43:05] Conclusion #AgentSkills #AI #GitHubCopilot #GeminiCLI #CodingAssistants #MCP #ModelContextProtocol #DeveloperTools #TwoVoiceDevs

43 мин.
23 ЯНВ.

Episode 265 - Gemini's New Personal Intelligence: A Second Brain?

Allen and Mike discuss Google's new "Personal Intelligence" feature for Gemini. They explore how it connects to your personal data like Photos, Gmail, and Docs to provide context-aware answers. The conversation covers real-world use cases, privacy concerns regarding training data, and the importance of transparency and granular control in AI systems. They also touch on the "blackmail" scenario found in other AI research and what developers can learn from Google's implementation. More Info: * https://blog.google/innovation-and-ai/products/gemini-app/personal-intelligence/ [00:00:30] Google's Gemini Personal Intelligence announcement [00:01:48] Connecting personal data sources to Gemini [00:03:45] Google's unique advantage with user data [00:06:40] Real-world use case: Tracking travel history [00:07:30] Potential use case: Combining health data sources [00:09:15] Privacy: Is your data used for training? [00:12:40] The debate: Opting in vs. privacy concerns [00:16:30] AI safety and the "blackmail" scenario [00:18:50] Lessons for developers: Granular permissions and transparency [00:20:30] Verifiability and user trust [00:23:50] Conclusion #Gemini #GoogleAI #PersonalIntelligence #Privacy #MachineLearning #Developer #TechPodcast #AI #TwoVoiceDevs

24 мин.
20 ЯНВ.

Episode 264 - AI, Context, and the "No-UI" Future

Allen Firstenberg welcomes back guest host Mike Wolfson, an Android Google Developer Expert, to discuss the shifting landscape of User Experience (UX) in the age of Artificial Intelligence. As we move toward autonomous agents and multimodal interactions—incorporating voice, haptics, and environmental data—the reliance on traditional screens and touch interfaces is set to diminish. Mike shares insights on why "context" is the new "queen," illustrating the challenges of current AI with real-world examples (like his Meta glasses failing to find a decent breakfast burrito). The conversation tackles the critical question: "Who does the agent truly work for?" and explores how developers can avoid "notification fatigue" while ensuring users remain informed and in control. From the "creepy" factor of hyper-personalized data to the "Beverage Butler" concept, this episode dives deep into designing for a future where the best UI might be no UI at all. [00:00:00] Welcome and Introduction [00:01:21] The Evolution of UX: Beyond Touchscreens [00:03:52] The Importance of Context: A Meta Glasses Example [00:06:21] Privacy, Creepiness, and Agent Loyalty [00:08:43] Application Development in an AI World [00:11:34] Avoiding the "Seinfeld Assistant" of Notification Fatigue [00:17:15] Feedback Modalities: Tones vs. Speech [00:19:39] Discoverability of Features in Non-Visual Interfaces [00:23:00] The "Beverage Butler" and Future Outlook #AI #UX #UserExperience #ArtificialIntelligence #AndroidDev #ContextAwareness #VoiceUI #NoUI #TechPodcast #TwoVoiceDevs #GDE #GoogleDeveloperExpert #BeverageButler

25 мин.
16 ЯНВ.

Episode 263 - Exploring the Parlant Agent Framework

In this episode, Mark introduces Allen to Parlant, an open-source framework for building agentic AI. They explore how Parlant differs from other frameworks like LangChain and LangGraph by using concepts like "journeys" for flexible conversation flows and "guidelines" for conditional rule application. Mark walks through the key features, including the ability to define glossaries, tools, and the engine's matching process. They also discuss the recent version 3.1 updates, such as linked journeys and behavior criticality levels. Finally, they dive into "Emcie," Parlant's managed NLP service that utilizes a teacher-student model architecture to optimize performance and cost using Small Language Models (SLMs). [00:00:00] Welcome and Introduction [00:00:43] Introduction to Parlant [00:02:03] Journeys: Flexible Conversation Flows [00:03:36] Guidelines: Conditional Rules [00:06:27] Motivations and Compliance [00:08:44] NLP Services and Providers [00:11:42] The Balance Between Rigid and Loose Conversations [00:18:43] Parlant 3.1 Updates: Linked Journeys and Behavior Levels [00:22:20] Custom Matchers [00:23:14] Emcie: Parlant's Managed NLP Service [00:25:05] Model Tiers: Jackal and Bison [00:26:14] Teacher-Student Architecture and SLMs [00:30:26] Cost and Optimization with Student Models [00:35:19] Conclusion and Wrap-up #Parlant #AI #AgenticAI #LLM #SLM #OpenSource #SoftwareDevelopment #TwoVoiceDevs #Emcie #NLP

37 мин.

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Episode 10 Teaser

We have something special planned for our 10th episode! Curious what it might be?

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No langchain

10.04.2023

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Reading the readme may be better use of your time if you want to learn about langchain

Mark and Allen talk about the latest news in the VoiceFirst world from a developer point of view.

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Mark and Allen
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Two Voice Devs