The Secure Developer

Episodios disponibles

5 de 169

Retrieval-Augmented Generation With Bob Remeika From Ragie
Episode SummaryBob Remeika, CEO and Co-Founder of Ragie, joins host Danny Allan to demystify Retrieval-Augmented Generation (RAG) and its role in building secure, powerful AI applications. They explore the nuances of RAG, differentiating it from fine-tuning, and discuss how it handles diverse data types while mitigating performance challenges. The conversation also covers the rise of AI agents, security best practices like data segmentation, and the exciting future of AI in amplifying developer productivity.Show NotesIn this episode of The Secure Developer, host Danny Allan is joined by Bob Remeika, co-founder and CEO of Ragie, a company focused on providing a RAG-as-a-Service platform for developers. The conversation dives deep into Retrieval-Augmented Generation (RAG) and its practical applications in the AI world.Bob explains RAG as a method for providing context to large language models (LLMs) that they have not been trained on. This is particularly useful for things like a company's internal data, such as a parental leave policy, that would be unknown to a public model. The discussion differentiates RAG from fine-tuning an LLM, highlighting that RAG doesn't require a training step, making it a simple way to start building an AI application. The conversation also covers the challenges of working with RAG, including the variety of data formats (like text, audio, and video) that need to be processed and the potential for performance slowdowns with large datasets.The episode also explores the most common use cases for RAG-based systems, such as building internal chatbots and creating AI-powered applications for users. Bob addresses critical security concerns, including how to manage authorization and prevent unauthorized access to data using techniques like data segmentation and metadata tagging. The discussion then moves to the concept of "agents," which Bob defines as multi-step, action-oriented AI systems. Bob and Danny discuss how a multi-step approach with agents can help mitigate hallucinations by building in verification steps. Finally, they touch on the future of AI, with Bob expressing excitement about the "super leverage" that AI provides to amplify developer productivity, allowing them to get 10x more done with a smaller team. Bob and Danny both agree that AI isn't going to replace developers, but rather make them more valuable by enabling them to be more productive.LinksRagie - Fully Managed Multimodal RAG-as-a-Service for DevelopersRagie ConnectOpenAIGemini 2.5Claude Sonneto4-miniClaudeClaude OpusCursorSnowflakeSnyk - The Developer Security Company Follow UsOur WebsiteOur LinkedIn
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Securing The Future Of AI With Dr. Peter Garraghan
Episode SummaryMachine learning has been around for decades, but as it evolves rapidly, the need for robust security grows even more urgent. Today on the Secure Developer, co-founder and CEO of Mindgard, Dr. Peter Garraghan, joins us to discuss his take on the future of AI. Tuning in, you’ll hear all about Peter’s background and career, his thoughts on deep neural networks, where we stand in the evolution of machine learning, and so much more! We delve into why he chooses to focus on security in deep neural networks before he shares how he performs security testing. We even discuss large language model attacks and why security is the responsibility of all parties within an AI organisation. Finally, our guest shares what excites him and scares him about the future of AI.Show NotesIn this episode of The Secure Developer, host Danny Allan welcomes Dr. Peter Garraghan, CEO and CTO of Mindgard, a company specializing in AI red teaming. He is also a chair professor in computer science at Lancaster University, where he specializes in the security of AI systems.Dr. Garraghan discusses the unique challenges of securing AI systems, which he began researching over a decade ago, even before the popularization of the transformer architecture. He explains that traditional security tools often fail against deep neural networks because they are inherently random and opaque, with no code to unravel for semantic meaning. He notes that AI, like any other software, has risks—technical, economic, and societal.The conversation delves into the evolution of AI, from early concepts of artificial neural networks to the transformer architecture that underpins large language models (LLMs) today. Dr. Garraghan likens the current state of AI adoption to a "great sieve theory," where many use cases are explored, but only a few, highly valuable ones, will remain and become ubiquitous. He identifies useful applications like coding assistance, document summarization, and translation.The discussion also explores how attacks on AI are analogous to traditional cybersecurity attacks, with prompt injection being similar to SQL injection. He emphasizes that a key difference is that AI can be socially engineered to reveal information, which is a new vector of attack. The episode concludes with a look at the future of AI security, including the emergence of AI security engineers and the importance of everyone in an organization being responsible for security. Dr. Garraghan shares his biggest fear—the anthropomorphization of AI—and his greatest optimism—the emergence of exciting and useful new applications.LinksMindgard - Automated AI Red Teaming & Security Testing‍Snyk - The Developer Security Company Follow UsOur WebsiteOur LinkedIn
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The Future is Now with Michael Grinich (WorkOS)
Episode SummaryWill AI replace developers? In this episode, Snyk CTO Danny Allan chats with Michael Grinich, the founder and CEO of WorkOS, about the evolving landscape of software development in the age of AI. Michael shares a fascinating analogy, comparing the shift in software engineering to the historical evolution of music, from every family having a piano to the modern era of digital creation with tools like GarageBand. They explore the concept of "vibe coding," the future of development frameworks, and how lessons from the browser wars—specifically the advent of sandboxing—can inform how we build secure AI-driven applications.Show NotesIn this episode, Danny Allan, CTO at Snyk, is joined by Michael Grinich, Founder and CEO of WorkOS, to explore the profound impact of AI on the world of software development. Michael discusses WorkOS's mission to enhance developer joy by providing robust, enterprise-ready features like authentication, user management, and security, allowing developers to remain in a creative flow state. The conversation kicks off with the provocative question of whether AI will replace developers. Michael offers a compelling analogy, comparing the current shift to the historical evolution of music, from a time when a piano was a household staple to the modern era where tools like GarageBand and Ableton have democratized music creation. He argues that while the role of a software engineer will fundamentally change, it won't disappear; rather, it will enable more people to create software in entirely new ways.The discussion then moves into the practical and security implications of this new paradigm, including the concept of "vibe coding," where applications can be generated on the fly based on a user's description. Michael cautions that you can't "vibe code" your security infrastructure, drawing a parallel to the early, vulnerable days of web browsers before sandboxing became a standard. He predicts that a similar evolution is necessary for the AI world, requiring new frameworks with tightly defined security boundaries to contain potentially buggy, AI-generated code.Looking to the future, Michael shares his optimism for the emergence of open standards in the AI space, highlighting the collaborative development around the Model Context Protocol (MCP) by companies like Anthropic, OpenAI, Cloudflare, and Microsoft. He believes this trend toward openness, much like the open standards of the web (HTML, HTTP), will prevent a winner-take-all scenario and foster a more innovative and accessible ecosystem. The episode wraps up with a look at the incredible energy in the developer community and how the challenge of the next decade will be distributing this powerful new technology to every industry in a safe, secure, and trustworthy manner.LinksWorkOS - Your app, enterprise readyWorkOS on YouTubeMITMCP Night 2025Snyk - The Developer Security Company Follow UsOur WebsiteOur LinkedIn
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Open Authorization In The World Of AI With Aaron Parecki
Episode SummaryHow do we apply the battle-tested principles of authentication and authorization to the rapidly evolving world of AI and Large Language Models (LLMs)? In this episode, we're joined by Aaron Parecki, Director of Identity Standards at Okta, to explore the past, present, and future of OAuth. We dive into the lessons learned from the evolution of OAuth 1.0 to 2.1, discuss the critical role of standards in securing new technologies, and unpack how identity frameworks can be extended to provide secure, manageable access for AI agents in enterprise environments.Show NotesIn this episode, host Danny Allan is joined by a very special guest, Aaron Parecki, the Director of Identity Standards at Okta, to discuss the critical intersection of identity, authorization, and the rise of artificial intelligence. Aaron begins by explaining the history of OAuth, which was created to solve the problem of third-party applications needing access to user data without the user having to share their actual credentials. This foundational concept of delegated access has become ubiquitous, but as technology evolves, so do the challenges.Aaron walks us through the evolution of the OAuth standard, from the limitations of OAuth 1 to the flexibility and challenges of OAuth 2, such as the introduction of bearer tokens. He explains how the protocol was intentionally designed to be extensible, allowing for later additions like OpenID Connect to handle identity and DPoP to enhance security by proving possession of a token. This modular design is why he is now working on OAuth 2.1—a consolidation of best practices—instead of a complete rewrite.The conversation then shifts to the most pressing modern challenge: securing AI agents and LLMs that need to interact with multiple services on a user's behalf. Aaron details the new "cross-app access" pattern he is working on, which places the enterprise Identity Provider (IDP) at the center of these interactions. This approach gives enterprise administrators crucial visibility and control over how data is shared between applications, solving a major security and management headache. For developers building in this space today, Aaron offers practical advice: leverage individual user permissions through standard OAuth flows rather than creating over-privileged service accounts.LinksOktaOpenID FoundationIETFThe House Files PDX (YouTube Channel)WIMSEAuthZEN Working Groupaaronpk on GitHubSnyk - The Developer Security Company Follow UsOur WebsiteOur LinkedIn
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The Evolution Of Platform Engineering With Massdriver CEO Cory O’Daniel
Episode SummaryDive into the ever-evolving world of platform engineering with Cory O’Daniel, CEO and co-founder of Massdriver. This episode explores the journey of DevOps, the challenges of building and scaling infrastructure, and the crucial role of creating effective abstractions to empower developers. Cory shares his insights on the shift towards platform engineering as a means to build more secure and efficient software by default.Show NotesIn this episode of The Secure Developer, host Danny Allan sits down with Cory O’Daniel, CEO and co-founder of Massdriver, to discuss the dynamic landscape of platform engineering. Cory, a seasoned software engineer and first-time CEO, shares his extensive experience in the Infrastructure as Code (IaC) space, tracing his journey from early encounters with EC2 to founding Massdriver. He offers candid advice for developers aspiring to become CEOs, emphasizing the importance of passion and early customer engagement. The conversation delves into the evolution of DevOps over the past two decades, highlighting the constant changes in how software is run, from mainframes to serverless containers and now AI. Cory argues that the true spirit of DevOps lies in operations teams producing products that developers can easily use. He points out the challenge of scaling operations expertise, suggesting that IT and Cloud practices need to mature in software development to create better abstractions for developers, rather than expecting developers to become infrastructure experts. A significant portion of the discussion focuses on the current state of abstractions in IaC. Cory contends that existing public abstractions, like open-source Terraform modules, are often too generic and don't account for specific business logic, security, or compliance requirements. He advocates for operations teams building their own prescriptive modules that embed organizational standards, effectively shifting security left by design rather than by burdening developers. The episode also touches upon the potential and limitations of AI in the operations space, with Cory expressing skepticism about AI's current ability to handle the contextual complexities of infrastructure without significant, organization-specific training data. Finally, Cory shares his optimism for the future of platform engineering, viewing it as a return to the original intentions of DevOps, where operations teams ship software with ingrained security and compliance, leading to more secure systems by default.LinksMassDriverAnsibleChefTerraformDevOps is BullshitElephant in the CloudDockerPostgresOpenTofuHelmRedisElixirSnyk - The Developer Security Company Follow UsOur WebsiteOur LinkedIn
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