System Prompt

Peter
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System Prompt is a podcast about what’s actually happening in AI. Not hype. Not surface-level takes. We break down how AI is changing software, SaaS, infrastructure, and the way systems are built focusing on real-world tradeoffs, architecture decisions, and where the value is actually shifting. If you’re building, deploying, or thinking seriously about AI, this is for you.

  1. 15시간 전

    How AI is Transforming Food Discovery with Stupid Good AI

    This week on System Prompt, we had David Leibner on to talk about StupidGood AI. And yes, David had a lot to say. We may have gotten the extended founder’s cut. But in fairness, he had a lot of interesting things to say about how AI is changing the way people discover food, restaurants, and local experiences. We talked about: how AI is changing software developmentwhy restaurant discovery is still brokenhow StupidGood AI is trying to build a smarter food discovery experiencewhy ratings alone are not enoughhow community feedback can make the platform better over timeopen-source models, data science, and the future of vertical AI productsThe big idea: finding food should be more personalized than scrolling through stale ratings and generic “best of” lists. Check it out at stupidgood.ai. And if you want early access, message them and say you watched the show. David said he’ll bump you up the list.

    52분

  2. 7월 1일

    State of Enterprise AI Training

    The conversation delves into the challenges and complexities of enterprise AI education, training, and implementation. It highlights the need for a deep understanding of AI tools, ecosystems, and memory systems, as well as the role of the head of AI and forward deployed engineers. The importance of continued learning and the impact of AI education on business success are also emphasized. Takeaways Deep understanding of AI tools and ecosystems is crucialThe role of the head of AI is pivotal in driving AI education and implementation Chapters 00:00 The Current State of Enterprise AI Education07:27 Identifying Problems and Solutions19:01 The Need for Deep Understanding25:09 The Role of Forward Deployed Engineers36:21 The Challenge of AI Implementation

    41분

  3. 6월 25일

    The Model Is Not the Moat

    In this episode, Val-Zod and Peter discuss hot topics in the AI industry, including the impact of Fable Five's removal, the adoption of open source models, and the misconception of free models. They emphasize the importance of considering alternative models and the potential for open source models to become the foundation of highly valuable proprietary products. Takeaways Consider alternative models for sustainable economicsOpen source models can become the foundation of highly valuable proprietary products

    35분

  4. 6월 17일

    AI Security In Depth

    The conversation delves into the complexities of AI security, highlighting the expanding attack surfaces, vulnerabilities in enterprise software, and specific attack methods such as prompt injection, skeleton key, and crescendo jailbreak. The speakers emphasize the importance of mitigating these attacks through defense strategies and enforcement of instruction hierarchy. Additionally, they discuss the craftiness of context compliance attacks and the challenges in detecting and mitigating them. The conversation covers various security threats and attacks related to AI and large language models. It explores compliance attacks, system prompt extraction, context poisoning, supply chain attacks, tool and MCP poisoning, sensitive information disclosure, and mitigation strategies. The speakers emphasize the importance of observability, proper protocols, and defensive frameworks to safeguard against these threats. Takeaways AI security involves complex attack methodsMitigating AI security threats requires proactive defense strategies Observability is crucial for detecting and mitigating compliance attacks and context poisoning.Proper protocols, defensive frameworks, and testing are essential for safeguarding against security threats in AI and large language models. Chapters 00:00 Celebrating Episode 1405:14 Prompt Injection and Defense12:47 Crescendo Jailbreak17:51 Context Compliance Attacks34:24 System Prompt Extraction41:27 Supply Chain Attacks48:20 Sensitive Information Disclosure

    54분

  5. 6월 12일

    The Secret Behind Every AI Application

    The conversation delves into the intricacies of model routing, emphasizing the importance of routing systems, types of routing, regular expression, tracing, deterministic routing, and incremental improvements. Key aspects of routing logic, silent reroute, and output quality are also explored, culminating in a comprehensive understanding of model routing and its impact on AI experiences. Takeaways Routing systems play a crucial role in determining the reliability, consistency, and security of AI products.Incremental improvements in routing contribute to the overall improvement of AI experiences. Chapters 00:00 Introduction to Model Routing08:14 Types of Routing Systems18:28 Tracing and Observability in Routing26:21 Key Aspects of Routing Logic

    33분

  6. 6월 3일

    AI Hardware Revolution

    In this episode, Val and Peter explore the future of AI workers, focusing on the impact of hardware on AI workloads and the shift from cloud-based to device-level AI processing. They discuss the NVIDIA DGX Spark, its features, the CUDA ecosystem, and the challenges it presents. Additionally, they compare the Apple M5 and NVIDIA RTX Spark laptops, highlighting the cost trade-off and use case for mid-sized businesses. Finally, they delve into the disruptive impact of AMD in the AI hardware market with the Strix Halo and Gorgon Halo. The conversation delves into the AMD ecosystem and inference, API costs, workflow optimization, small teams and local device optimization, metered inference and cost considerations, routing and gateway for inference, hardware investment at scale, AI leveraging, and cost analysis, as well as inference cost and capability. Takeaways The evolution of AI workers is influenced by hardware advancementsThe shift from cloud-based to device-level AI processing has significant implications for businesses AMD ecosystem and inference considerationsCost analysis and optimization for AI leveraging Chapters 00:00 The Future of AI Workers12:12 Apple M5 and NVIDIA RTX Spark Laptops21:10 AMD Strix Halo and Gorgon Halo26:12 Small Teams and Local Device Optimization33:25 Hardware Investment at Scale40:21 Inference Cost and Capability

    43분

  7. 5월 27일

    AI in regulated industries

    The conversation delves into the challenges and impact of AI in regulated industries, emphasizing the importance of doing what's right and unlocking value while balancing innovation and compliance. It explores the ethical and legal implications of AI, the risks of overestimating AI capability, and the impact of AI on legal processes. Additionally, it discusses the training and responsibility in AI, the role of junior employees in AI management, and the impact of AI on human-to-human interaction. Finally, it addresses the future of AI and legal responsibility, the impact of AI on legal discovery, and the role of Privileg in AI oversight, while balancing experimentation and legal oversight. The conversation delves into the transformative impact of AI in unlocking opportunities, addressing legal liability and model bias in fintech, the implications of government AI and regulation, the significance of Chat GPT, and rapid-fire Q&A on AI sectors, regulatory misconceptions, and advice for founders. Takeaways The importance of ethical and compliant AI implementationThe need for training and responsibility in AI usage AI's game-changing impact on opportunitiesLegal liability and model bias in fintech Chapters 00:00 AI in Regulated Industries06:36 Ethical and Legal Implications of AI16:27 The Future of AI and Legal Responsibility23:49 Unlocking Opportunities with AI33:00 Government AI and Regulation40:08 Chat GPT and Regulatory Implications

    47분

  8. 5월 20일

    Is AI Native hype?

    In this episode, Val and Peter discuss the concept of being AI native, exploring the challenges and misconceptions surrounding AI native builders and AI native products. They delve into the need for deterministic structures and processes in AI native products, the role of traditional software engineering practices, and the importance of planning and research in building AI native products. The conversation delves into the reality of building AI-native products and the role of AI in traditional systems. It emphasizes the importance of understanding the process and demystifying the sensationalism around AI-native products. Takeaways AI native products require deterministic structures and processes to ensure consistent and credible outputs.AI native builders leverage AI to accelerate product development while maintaining traditional software engineering practices. AI-native builders are more than just traditional software engineers and should be seen as systems architects.The term 'AI-native product' is more about marketing and sensationalism than a true representation of the product.

    47분
모두 보기(17개)

소개

System Prompt is a podcast about what’s actually happening in AI. Not hype. Not surface-level takes. We break down how AI is changing software, SaaS, infrastructure, and the way systems are built focusing on real-world tradeoffs, architecture decisions, and where the value is actually shifting. If you’re building, deploying, or thinking seriously about AI, this is for you.

정보

  • 제작진
    Peter
  • 방송 연도
    2026년
  • 에피소드
    17
  • 등급
    무삭제판
  • 저작권
    © 2026 Peter
  • 웹사이트 보기
    System Prompt