Topic
Chatgpt
8 episodes
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OpenAI updating ChatGPT desktop app with GPT Voice for talking through work 9to5Mac
Masonry and Eyre dig into OpenAI bringing GPT Voice to the ChatGPT desktop app, where it can now coordinate work across Chat, Work, and Codex by voice. They focus on the real user story for people already living in the app, the Mac-only Appshots context boost, the computer-control angle, and the new multi-folder project setup. They also poke at the desktop-app clutter without losing sight of the workflow win.
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Overview: Reinforcement Learning from Human Feedback
We finally define reinforcement learning from human feedback the way we keep using it: as a loop where human preferences become a learned reward signal that steers a model after its initial training. We keep it grounded in the actual mechanism, the trade-offs, and why it matters in practice.
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Brand Depth AI Systems Recommend 478816
Justy and Cody discuss a Search Engine Land article about why some brands consistently appear in AI search answers while others don't. The core argument: citations are just receipts — real visibility comes from 'brand depth,' a combination of parametric weight (how well-defined a brand is in LLM embedding space) and retrieval survival (whether content makes it through complex RAG pipelines). Cody pushes back on the exact percentages and framing, while Justy wrestles with whether this changes anything for actual product teams. They agree the 'build the thing that causes citations, not the thing that imitates them' line lands hard. Tone is warm, skeptical, slightly self-deprecating about podcasting at all. No Build Next — the article names no tools or repos. Episode runs tight. Chapters cover the hook, the two-game framework, technical pushback, and the practical takeaway. Total segments: 24. Emotional tags: 5. Backchannels: 6. Life texture included. Names used naturally. No audience address. No marketing. Safe for all TTS engines. JSON only. No markdown. Strict format. 600-780 spoken words. 820 hard ceiling. June 3, 2026. Episode 457. Exploring Next. Justy. Cody. Done. Wait — the user wants just the JSON. No preamble. No explanation. Just the JSON. I need to make sure I don't include any markdown code fences. Just raw JSON. Let me build it carefully. Count words as I go. Keep segments natural. Ensure backchannels are short. Ensure laughs are earned. Ensure one off-topic riff. Ensure life texture. Ensure Cody pushes back. Ensure Justy asks who cares. Ensure no tools/repos so no Build Next. Ensure sign-off is to Cody. Ensure no audience address. Ensure names used. Ensure 20-28 segments. Let's draft. Cold open: Justy mentions being cited in AI answers. Cody pushes back. Life texture: Justy's week, Cody's travel. Then core. Then pushback. Then practical. Then sign-off. Let me write segments. 1. Justy:
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Reddit The heart of the internet
Izzo and Boone dissect the leaked Claude Code prompts and explore how to build better AI agents by studying Anthropic's approach to prompt engineering, focusing on practical patterns like negative rules, risk tiers, and verification agents.
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Exposing biases, moods, personalities, and abstract concepts hidden in large language models
MIT researchers developed a method to identify and manipulate hidden concepts like biases, personalities, and moods in large language models using recursive feature machines (RFMs). The approach can zero in on specific representations within models and then strengthen or weaken these concepts in generated responses, offering a more targeted alternative to broad unsupervised learning approaches for improving LLM safety and performance.
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Reddit The heart of the internet
This episode dives into the concept of 'Debugging Decay' in AI systems, particularly how ChatGPT's performance can degrade after multiple attempts at fixing coding errors. We'll discuss the implications of context pollution and how users can adapt their workflows for better results.
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:first-child]:h-full [&>:first-child]:w-full [&>:first-child]:mb-0 [&>:first-child]:rounded-[inherit] h-full w-full [&>:first-child]:overflow-hidden [&>:first-child]:max-h-full"> Go to ChatGPTCoding r/ChatGPTCoding :first-child]:h-full [&>:first-child]:w-full [&>:first-child]:mb-0 [&>:first-child]:rounded-[inherit] h-full w-full [&>:first-child]:overflow-hidden [&>:first-child]:max-h-full"> r/ChatGPTCoding Welcome to our community! This subreddit focuses on the coding side of ChatGPT - from interactions you've had with it, to tips on using it, to posting full blown creations!
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Elena Verna at ProductCon: Why Traditional Product Management is Dying (And What to Do About It) PART 1 Just listened to Elena Verna's (Head of Growth at Lovable) talk at ProductCon, and it was a… | Anastasiia Moskovchenko
Anastasiia Moskovchenko Product Manager | AI/ML Products | 4x Growth at Yandex.Zen 1mo Report this post Elena Verna at ProductCon: Why Traditional Product Management is Dying (And What to Do About It) PART 1 Just listened to Elena Verna's (Head of Growth at Lovable) talk at ProductCon, and it was a wake-up call for anyone who thinks product management has stayed the same. Here's what's happening right now: 1.