This episode covers the latest developments in AI models from Google, Anthropic, and others, exploring their capabilities, limitations, and implications for developers and the industry. The hosts share insights on model stability, speed, safety, and the future of AI in coding and business.

• Google Gemini 3.1 updates and stability issues
• The impact of model speed and inference hardware
• Model distillation and intellectual property concerns
• The role of AI in software engineering and code quality
• implications of AI model development

Chapters

00:00
Introduction to AI Models and Recent Developments

01:05
Exploring Google's Gemini 3.1 and User Experiences

04:52
Strengths and Weaknesses of AI Models in Development

09:37
Cerebris and Spark: Speed vs. Context in AI Models

17:29
Anthropic's Claims and Geopolitical Implications in AI

27:37
The Future of AI Development and Safety Concerns

28:06
The Evolution of AI in Code Generation

29:02
Managing Automated Code in Large Companies

30:49
The Disposability Principle in Code Design

32:37
Balancing Code Stability and Disposability

34:29
Navigating Complexity in AI-Generated Code

36:55
The Role of AI in Code Review and Development

40:40
The Future of AI and Human Collaboration in Coding

45:45
The Changing Landscape of Software Engineering

50:04
The Demand for Software Engineers in an AI World

In this episode of the Rate Limited podcast, hosts Ray Fernando, Adam Larson, and Eric discuss the latest AI model releases, including Opus 4.6 and Codex 5.3. They explore the implications of these advancements on coding practices, the emergence of swarm intelligence, and the challenges of managing multiple AI agents. The conversation also touches on the addictive nature of AI coding, the impact of AI on work-life balance, and the potential rise of AI spam in communication. The hosts emphasize the importance of taking breaks and maintaining a healthy relationship with technology as they navigate this rapidly evolving landscape.

Links:
Ray: https://www.youtube.com/@RayFernando1337
Eric: https://www.youtube.com/@pvncher
Adam: https://www.youtube.com/@GosuCoder

In this episode of the Rate Limited Podcast, hosts Ray, Adam, and Eric discuss the latest advancements in AI models and tools, including Codex, Opus, and Kimi K 2.5. They explore the intricacies of orchestration, task management, and the importance of security in AI applications. The conversation delves into the practical applications of these models in development and personal assistance, highlighting the balance between utility and risk. The hosts share their experiences and insights on using these tools effectively while navigating the evolving landscape of AI technology.

Links:
Ray: https://www.youtube.com/@RayFernando1337
Eric: https://www.youtube.com/@pvncher
Adam: https://www.youtube.com/@GosuCoder

In this episode of the Rate Limited podcast, hosts Ray Fernando, Adam Larson, and Eric Provencher dive deep into the latest advancements in AI, particularly focusing on Codex 5.2. They discuss user experiences, the steerability and speed of Codex, and the implications of the recent Claude crackdown on third-party agents. The conversation also explores the future of AI in software engineering, the innovative Ralph Loop approach, and the potential disruptions in various industries. The hosts emphasize the importance of adapting to these changes and maintaining a balance between automation and human oversight in coding practices.

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

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

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

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