Rate Limited

Adam/Eric/Ray

Discussion about the latest news in the world of AI assisted coding.

集數

  1. 2025/12/19

    2026 Predictions, 2025 Surprises, GPT 5.2 and more | Ep 7

    In this episode of the Rate Limited podcast, hosts Ray Fernando, Adam Larson, and Eric Provencher discuss the latest developments in AI, particularly focusing on GPT 5.2 and its implications for coding. They explore the rise of terminal UIs, the evolution of AI coding agents, and make predictions for 2026. The conversation also touches on the surprises of 2025 in AI labs, the potential for consumer AI, and the ongoing debate about whether we are in an AI bubble. The hosts reflect on their experiences with AI tools and share their hopes for the future of technology in software development. Links: Ray: https://www.youtube.com/@RayFernando1337 Eric: https://www.youtube.com/@pvncher Adam: https://www.youtube.com/@GosuCoder Chapters 00:00 Introduction to AI Predictions for 2025 00:37 Exploring GPT 5.2: Features and Improvements 03:07 User Experiences with GPT 5.2 05:23 The Rise of Violent Coding 10:01 Optimizing Workflows with AI Agents 12:14 Insights on GPT 5.2 Pro 16:55 Gemini 3 Flash: A New Contender 19:43 Reflections and Predictions for 2026 23:23 Meta's Decline and Industry Surprises 25:58 Predictions for 2026: Enterprise vs Consumer AI 29:42 Consumer AI Predictions: OpenAI vs Gemini 35:46 The Rise of AI Coding Agents 40:41 2026 Predictions for AI Coding Agents 47:01 Key Takeaways from 2025 50:22 Integrating Technology in Traditional Businesses 51:44 The Divide in the Programming Community 53:34 Hopes for 2026: Stability and User Experience 54:29 Blending Software Engineering Workflows 57:06 Wild Card Predictions for 2026 01:00:47 Are We in a Bubble? 01:06:23 The Future of Major Tech Companies

    1 小時 12 分鐘

  2. 2025/12/12

    Opus 4.5 is Next Level, Is Anyone using Gemini 3 Pro?, is 200k context enough? | Episode 6

    In this episode of the Rate Limited podcast, hosts Ray Fernando, Eric P, and Adam Larson discuss the latest advancements in AI models, focusing on Opus 4.5 and its performance compared to other models like Gemini 3 Pro. They explore the importance of context engineering, the impact of MCPs, and techniques for effective prompting. The conversation also delves into the use of AI in software engineering, particularly in code analysis and GitHub integration, while sharing personal experiences and insights on the evolving landscape of AI tools. Links: Ray: https://www.youtube.com/@RayFernando1337 Eric: https://www.youtube.com/@pvncher Adam: https://www.youtube.com/@GosuCoder

    54 分鐘

  3. 2025/11/28

    Gemini 3 Pro finally here, Opus 4.5 surprises everyone, GPT 5.1and more | Episode 5 Rate Limited

    In this episode of the Rate Limited podcast, hosts Ray Fernando and Eric, along with guest Adam Larson, dive deep into the latest developments in AI coding models, including updates on Codex, GPT 5.1, Gemini 3, and Opus 4.5. They discuss the performance of these models, their applications in real-world coding scenarios, and the challenges faced by developers working with legacy code. The conversation also touches on insights from the AI Native DevCon, highlighting the complexities of integrating AI into existing codebases and the evolving role of QA engineers in this landscape. Links: Ray: https://www.youtube.com/@RayFernando1337 Eric: https://www.youtube.com/@pvncher Adam: https://www.youtube.com/@GosuCoder Chapters 00:00 Introduction to AI Practitioners 00:57 Updates on Codex and Model Releases 02:54 Exploring GPT 5.1: User Experiences 05:45 Comparing GPT 5.1 and Gemini 3 09:03 Deep Dive into Gemini 3 Performance 12:47 Opus 4.5: A Game Changer? 22:51 Thoughts on AI Models and Their Applications 35:44 Navigating AI Pricing and Plans 38:11 Exploring AI Tools and Their Unique Features 39:33 Workflow Strategies for AI Coding 42:48 The Challenges of Legacy Code and AI Integration 50:25 Insights from the AI Native DevCon

    59 分鐘

  4. 2025/11/14

    OpenAI Codex changes the way they handle context | Episode 4

    Codex has introduced significant changes that affect its usability with external tools. The truncation of context in Codex has raised concerns among users. Claude's handling of context and contradictions is seen as superior to Codex. Chinese AI models are gaining traction and are being compared to Western models. User experiences with various AI models highlight the importance of context management. The competition among AI models is intensifying, with open-source models becoming more viable. Apple's potential entry into the AI space could disrupt existing market dynamics. The future of AI models may involve more integration with consumer hardware. The balance between speed and accuracy in AI models is crucial for effective use. The evolving landscape of AI tools requires users to adapt their workflows. Summary In this episode, the hosts discuss the latest developments in AI models, focusing on Codex and its recent changes, including context truncation issues. They compare Codex with Claude and other models, highlighting user experiences and the rise of Chinese AI models. The conversation also touches on the potential impact of Apple's entry into the AI space and the evolving dynamics of the AI market. The hosts share insights on the importance of context management and the future of AI tools, emphasizing the need for users to adapt their workflows as the landscape continues to change. Sound bites "Codex has introduced significant changes." "Claude handles contradictions better than Codex." "Chinese AI models are gaining traction." Chapters 00:00 Introduction to AI Language Models 03:00 Codex Research and Tool Limitations 06:02 Comparing Codex with Claude Code 08:55 Impact of Context Truncation on Performance 12:02 Exploring Chinese AI Models 15:06 Kimi K2 and MinMax M2 Insights 21:53 The Evolution of AI Models and Performance 23:29 Concerns Over Data Privacy and Model Origins 25:33 Quality and Safety in AI Model Deployment 30:46 Emerging Models and Competitive Pricing 32:49 Utilizing GLM 4.6 in Workflows 36:48 Budgeting for AI Tools and Services 43:36 The Impact of Cursor and Composer Models 45:55 Exploring Use Cases for AI Tools 48:57 The Evolution of Claude 2.0 52:00 The Importance of Architectural Planning 58:00 Anticipating Gemini 3.0 and Market Dynamics 01:01:40 The Future of AI Models and Competition

    1 小時 11 分鐘

  5. 2025/10/30

    Is GPT 5 Actually Degraded? | Episode 3

    Summary In this episode, the hosts discuss the latest features of Cursor 2.0, its positioning in the market compared to other coding agents, and the implications of AI on job markets. They explore the evolution of coding agents, the impact of teleoperation in robotics, and the future of AI in everyday life. The conversation also touches on community engagement and the potential for live shows. Takeaways Cursor 2.0 introduces an agent workflow focused on prompting. The speed and flow of Cursor 2.0 are key advantages over competitors. AI's impact on job markets is complex, with layoffs influenced by automation. The entry-level job market for engineers is currently very challenging. Teleoperation in robotics raises questions about privacy and surveillance. AI should enhance human capabilities rather than replace them. The evolution of coding agents is reshaping software engineering practices. Community engagement is vital for sharing experiences with AI models. The potential for live shows could enhance community interaction. The future of AI in everyday life is still uncertain but promising. Titles Exploring Cursor 2.0: The Future of Coding Agents AI and Job Markets: A Complex Relationship Sound bites "Cursor 2.0 just dropped!" "AI is not good enough to cut my job." "We're in a movie, guys!" Chapters 00:00 Introduction to Cursor 2.0 and Its Features 02:49 Benchmarking and Positioning of Cursor 2.0 05:53 The Evolution of Coding Agents 08:49 User Experiences with GPT-5 and Codex 12:00 Challenges in Context Management 15:02 Data Sharing and Privacy Concerns 18:04 Claude's New Skill System and Its Implications 30:05 Cloud-Based Skills and Automation 32:20 Creating Business Workflows with AI 34:40 Impact of AI on Job Market and Layoffs 38:27 Navigating AI's Role in Engineering Jobs 44:07 The Future of Robotics and Teleoperation

    54 分鐘

  6. 2025/10/17

    The Real Cost of Free AI Coding: Episode 2 Rate Limited

    Summary In this episode of the Rate Limited podcast, hosts Ray Fernando, Adam (GosuCoder), and Eric Provencher dive into the implications of free AI agents, discussing the hidden costs associated with data privacy and sustainability. They explore the performance of Haiku 4.5 compared to Sonnet 4.5, the dynamics of ad targeting in the AI market, and the importance of effective planning and execution in AI models. The conversation also touches on retrieval techniques, the future of AI agents, and the significance of community engagement in navigating the rapidly evolving landscape of AI technology. Takeaways Free AI agents come with hidden costs, primarily related to data privacy. The sustainability of free AI models is questionable due to high token costs. Haiku 4.5 shows promise but has limitations compared to Sonnet 4.5. Ad targeting strategies may not align with the needs of high-end engineers. Effective planning in AI models can significantly improve output quality. Retrieval techniques like grep and embedding models have their pros and cons. Context management is crucial to avoid pollution in AI outputs. Community engagement is essential for sharing knowledge and experiences. Different AI models have unique strengths that can be leveraged for specific tasks. The evolution of AI technology requires ongoing discussions and collaboration. Chapters 00:00 Introduction to Free AI Agents 03:05 The Cost of Free: Data and Sustainability 06:11 Ad Targeting and User Engagement 08:54 Haiku 4.5: Performance and Comparisons 11:57 Complexity in AI Models 15:08 Optimizing Model Usage 18:01 Real-World Applications and Strategies 30:08 Debugging Complex Systems with Language Models 31:37 The Evolution of Planning Modes in Coding Tools 34:09 Cursor's Planning Mode: A Game Changer 36:30 Efficiency in Feature Shipping with Cursor 38:08 Retrieval Techniques: Grep vs. Embedding Models 40:31 Agentic Retrieval vs. Embedding: A Debate 43:39 The Importance of Context in Code Retrieval 46:39 The Rise of GPT-5 Pro and Its Impact 51:22 Comparing Grok and GPT-5 Pro 54:31 Community Engagement and Future Directions

    58 分鐘

  7. 2025/10/02

    Is Sonnet 4.5 the BEST coding model and more | Episode 1

    Keywords AI models, Sonnet, GPT-5, benchmarking, coding assistants, user experience, reasoning, bug fixing, community engagement, AI trends Summary In this episode of Rate Limited, the hosts discuss the latest developments in AI models, focusing on benchmarking Sonnet and GPT-5. They explore the nuances of model behavior, context windows, and real-world testing, particularly in bug fixing. The conversation highlights user experiences, challenges, and the importance of reasoning in AI models. The hosts also engage with the community, encouraging listeners to share their insights and experiences with various AI tools, while contemplating the future of AI coding assistants. Takeaways AI models are constantly evolving and improving. Benchmarking is crucial to determine the best model for specific tasks. User experience varies significantly between different AI models. Context windows play a vital role in model performance. Real-world testing reveals strengths and weaknesses of AI models. Community feedback is essential for understanding model effectiveness. Reasoning capabilities differ among AI models, affecting their output. Explicit prompts yield better results with AI models. AI models can be seen as teammates in coding tasks. The landscape of AI tools is rapidly changing, requiring continuous adaptation. Titles Navigating the AI Model Landscape Benchmarking Sonnet and GPT-5: A Deep Dive Sound bites "Best is so hard to measure." "GPT-5 is right up there with it." "Sonnet 4 was unusable for me." Chapters 00:00 Introduction to AI Models and Their Applications 01:48 Benchmarking Sonnet 4.5 and GPT-5 05:57 Exploring Model Behavior and Problem Solving 10:05 User Experiences with Sonnet and GPT-5 13:57 Context Management and Tool Usage in AI Models 17:56 Comparative Analysis of AI Models in Development 22:01 The Future of AI in Software Development 30:30 Exploring Coding Methodologies 32:30 The Evolution of AI Models 34:48 Tuning AI Models for Optimal Performance 38:58 Evaluating Chinese AI Models 42:57 The Importance of Rule Adherence in AI 44:57 Community Perspectives on AI Tools

    52 分鐘
  • 共 7 集

簡介

Discussion about the latest news in the world of AI assisted coding.

資訊

  • 創作者
    Adam/Eric/Ray
  • 活躍年代
    2025年
  • 集數
    7
  • 年齡分級
    兒少適宜
  • 版權
    © 2025 Rate Limited
  • 節目網站
    Rate Limited

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