The Loop Asia

Aki Ranin has spent years helping organizations think clearly about AI strategy, and right now he is focused on a problem most companies are only beginning to notice: the deeper you embed AI agents into your business, the more exposed you become to providers you do not control. In this episode, recorded soon after his keynote at apidays Singapore 2026, Aki walks through what sovereign AI actually means in practice — not as a regulatory concept, but as a question of operational risk. If your agents can be switched off without warning, if you cannot quantify hallucination rates, if you do not own the code, you do not own your business.What you will learn:Why the AI supply chain carries the same fragility risks as physical supply chains — from TSMC and ASML to the concentration of frontier models in Silicon ValleyHow a startup of 40 people running on Claude APIs was accidentally banned for 24 hours, and what that tells you about building on closed platformsThe Shopify case study: how one team reduced their AI costs from $5 million per year to $70,000 by moving down the model stack without sacrificing accuracyWhy "AI inflation" may matter as much as financial inflation — and how token costs are rising even as providers keep calling new models "Flash"The difference between drag-and-drop agent platforms and code-owned agents, and why that distinction will determine who keeps the IPHow to build a sovereign AI stack as a gradient: from paid cloud APIs, to private cloud instances, to open models, to on-premise inference hardwareWhy AI governance belongs at the board level, not delegated to a single AI leadHow Singapore's Foreign Minister Vivian Balakrishnan is running a local AI second-brain on a Raspberry Pi — and what that signals about accessibility.The sovereign AI stack Aki describes:Free tools — acceptable for non-sensitive, public-domain research onlyPaid subscriptions — minimum bar for any work touching company dataPrivate cloud instances (AWS, Azure, GCP) — frontier models with access controls and no training data exposureOpen models via API — more portability, less vendor lock-inOpen models on your own hardware — maximum auditability, task-specific agents, sensitive workloadsAbout Aki Ranin: Aki Ranin is a two-time founder, AI advisor, and published author who has focused exclusively on machine learning and AI since 2016. He co-created the "Usable AI" transformation framework, advises startups, corporates, and VC funds on AI strategy, and serves as Affiliate Faculty in AI and ML at Singapore Management University. Follow Aki Ranin on Substack, especially his article "Not your AI, not your business" — https://recursivelabs.substack.com/p/not-your-ai-not-your-business

Most enterprise AI programmes produce proof-of-concepts that never reach production. Sutowo Wong, Managing Director of AI x Data at Temus, has a framework for diagnosing why — and fixing it. He calls it the AI Triangle: three conditions that must be satisfied simultaneously. Miss any one and the transformation stalls.Recorded after apidays Singapore 2026, this conversation covers the structural reasons AI initiatives fail to scale, why AI transformation has to be CEO-led, how to close the tempo gap between model releases and enterprise deployment, and why governance designed into architecture from the start is an accelerator — not a speed bump.What we cover:• The AI Triangle — transformative, sovereign and fast, explained• The POC trap and why it is a structural problem, not just a technology problem• Data sovereignty and contextual sovereignty in practice• Prototype in 6 hours, live deployment in 6–12 weeks• Why the CEO, not the Chief AI Officer, must drive AI transformation• Governance as accelerator — and why it must be baked in from the startConnect with Sutowo on LinkedIn: linkedin.com/in/sutowo/Temus: temus.comThe Loop Asia: www.theloop.asia

Manjunath Bhat leads software engineering research at Gartner and has been one of the most thoughtful voices tracking what AI is actually doing to the way we build software — not just the productivity story, but the structural changes to teams, platforms, and careers. He's a returning keynote speaker at apidays Singapore and apidays Australia.In this conversation we cover:The shift from AI-augmented human work to agent-driven development — and why Manju deliberately avoids calling these tools "peer programmers"Why the prototype-to-production gap hasn't closed, and where the real friction still livesThe hidden downside of vibe coding: when you fully offload to AI, you stop learning tooHow platform engineering is evolving from template-based governance to embedding intelligence directly into the development workflowThe three mismatches platform teams now have to resolve: speed, determinism, and accountabilityWhat junior engineers should actually focus on as AI absorbs more entry-level workWhy Gartner's position is that creativity — not productivity — will be the new measure of engineering excellenceManju will be delivering a keynote at apidays Singapore, 14–15 April 2026.Connect with Manju: linkedin.com/in/manjunathbhatapidays Singapore 2026: apidays.global/singaporeTheLoopAsia: www.theloop.asia

From molecular biology to electronic health records, Prof. Karin Verspoor discusses why structured vocabularies still matter in the age of LLMs — and why domain expertise is the one thing AI can’t replace.GuestProfessor Karin Verspoor, Executive Dean of Computer Science, RMIT UniversityKeywordsnatural language processing, healthcare analytics, structured data, unstructured data, medical terminology, UMLS, SNOMED, ICD, electronic health records, AI governance, human-in-the-loop, knowledge representation, cognitive science, protein function prediction, clinical documentation, machine learningSummaryJon Scheele speaks with Professor Karin Verspoor, Executive Dean of Computer Science at RMIT University, about the critical role of language in making sense of healthcare data. Karin traces her journey from cognitive science and NLP research, through an AI startup and Los Alamos National Lab, to healthcare analytics — starting with a colleague’s question about protein function prediction when she didn’t even know what a protein was.They discuss how structured vocabularies like the Unified Medical Language System (UMLS), SNOMED, and ICD codes provide an anchoring framework for clinical data, why simple dictionary lookup falls short (especially with negation in medical records), and how LLMs are changing the landscape while still lacking domain-specific clinical context.The conversation explores the balance between generative AI tools and traditional predictive models, and why human oversight and domain expertise remain essential for safe, effective use of AI in healthcare.Key TakeawaysKarin’s path into healthcare started with a colleague asking her to apply NLP to protein function prediction — she didn’t know what a protein was at the time.Scientific literature and clinical records are overwhelmingly expressed in natural language, making NLP essential for extracting structured insights.The Unified Medical Language System (UMLS) unifies standards like ICD and SNOMED into a shared framework — and underpins billing systems worldwide.Simple dictionary lookup against these vocabularies is a useful starting point, but fails with negation (e.g., “no evidence of infection” being read as “infection”).LLMs have shifted clinician attitudes — before ChatGPT, many didn’t see the value of AI tools; now demand outpaces what can be safely deployed.AI scribes and documentation tools are among the first clinical adoptions, but rely on doctors manually verifying output — a model that may not scale.Generative AI won’t replace traditional predictive and classification models — healthcare will use a mix of approaches for different tasks.The key question to ask of any AI system is: “What’s not in your data?” LLMs lack the specific context of individual situations.Domain knowledge is what allows humans to critically evaluate AI output — without it, you can’t spot errors.Every situation is unique, and that contextual understanding is what humans bring that LLMs currently cannot.Sound Bites"What’s not in your data?”“I literally looked at him and said, what’s a protein?”“Every situation is unique — and that’s what a human can bring that the LLM doesn’t have access to.”“People don’t always use the terminology correctly.”“I checked it nine times and it was right… the tenth time, they just tick the box.”

Most organizations don't discover what they have until crisis strikes. Akhil Bhaskar makes the case for software catalogs, scaffolding templates, and the "undifferentiated heavy lifting" that enables teams to move fast without breaking things.When a major security vulnerability hits, how quickly can you answer "How exposed are we?" For most organizations, it's a scramble. For Akhil Bhaskar's team, it took two hours to assess and four hours to fix—even though the Log4j vulnerability affected systems worldwide.The secret? A well-maintained software catalog and a commitment to technical hygiene.In this episode, Akhil shares lessons from his career spanning consulting, customer-side engineering leadership, and now AWS. We explore how tools like Backstage help organizations maintain visibility over their technology estates, why "undifferentiated heavy lifting" matters more than you think, and how the rise of agentic AI is changing what it means to be a software developer.Key Topics Discussed:How software catalogs transform crisis response (Log4j case study)The importance of technical hygiene and documentation disciplineUsing Backstage for software catalogs, golden paths, and scaffolding templatesManaging software supply chain dependenciesWhy contractors and efficiency drove investment in opinionated patternsThe shift from programmatic to intent-based developmentAgentic AI: boundaries, guardrails, and explainability requirementsEssential skills for the AI era: storytelling and critical thinkingHow AI can help with documentation without eliminating human responsibilityNotable Quotes:"Having had the rigor and the hygiene of maintaining what do we have, where do we have it, how do we have it, came in extremely handy for us.""The entire point of generative AI is it's probabilistic, but businesses want predictability, confidence, and control.""Storytelling and critical thinking—those two skills are fundamental. Storytelling is how you communicate intent, and critical thinking is how you verify the outcome."About the Guest:Akhil Bhaskar works at AWS and has extensive experience in consulting, engineering leadership, and digital transformation across the US, Australia, and Singapore. He specializes in building resilient, adaptable technology stacks and is currently working on applying software catalog concepts to agentic AI.Connect with Us:www.apiconnections.ioSubscribe & Review:If you found this episode valuable, please subscribe and leave a review on Apple Podcasts, Spotify, or YouTube. It helps other technology leaders discover these conversations. Timestamps:00:00 Introduction00:30 Welcome and background01:27 Akhil's background across consulting, customer, and vendor roles03:00 The Log4j supply chain vulnerability story03:46 How software catalogs saved the day05:28 Undifferentiated heavy lifting and contractor efficiency08:20 The importance of technical hygiene09:54 AI, governance, and technology estate management10:56 Generative vs. agentic AI: predictability matters12:26 Boundaries and explainability in agentic systems14:24 Intent-based development and documentation16:50 Essential skills: storytelling and critical thinking21:01 Closing thoughtsTags: #SoftwareDevelopment #TechLeadership #SoftwareCatalog #Backstage #Log4j #SupplyChainSecurity #AI #AgenticAI #DigitalTransformation #AWS #TechnicalHygiene #DevOps

In this conversation, Jon Scheele, Fethi Rabhi, and Alan Hsiao discuss the complexities of data integration, particularly in the context of e-invoicing. They explore the challenges faced by businesses in automating invoicing processes, the importance of standards like PEPPOL, and the limitations of current systems. The discussion also touches on the future of invoicing, automation, and the potential impact of AI and blockchain technology on business processes.TakeawaysData integration is a significant challenge for businesses.E-invoicing requires automatic production and consumption of invoices.Standards like PEPPOL facilitate communication but have limitations.The complexity of invoicing is compounded by various business processes.Microservices and APIs can help in evolving architectures.AI's impact on invoicing may take time to materialize.The future may see more hybrid systems for invoicing.Automation in invoicing can extend to procurement and pricing.Trust in communication is essential for effective invoicing.The digitization of impractical processes is on the horizon.Sound bites"The world effectively runs on this invoice.""We need a way of trust in the communication.""We do see a decline in ERP type systems."Chapters00:00 The Challenge of Data Integration01:48 Understanding E-Invoicing Complexity08:47 Standards in E-Invoicing: Benefits and Limitations14:01 Balancing Standardization and Innovation22:07 Future Trends in E-Invoicing and Automation

In this episode, we dive into the world of home automation and the hidden security risks that come with it. Join us as Joseph Yap, a cybersecurity expert, shares his journey from a personal interest in smart homes to uncovering alarming vulnerabilities in everyday devices. Discover how convenience often comes at the cost of security, and learn practical steps to protect your home network from potential threats. Tune in to understand why your smart fridge might be more than just a kitchen appliance and how to safeguard your digital front door.The discussion covers various aspects of cybersecurity, including the threats posed by interconnected devices, the importance of maintaining good cyber hygiene, and the differences between corporate and personal cybersecurity practices. Joseph also highlights the need for a structured approach to cybersecurity, advocating for regular audits and updates to ensure the safety of home networks.Keywordscybersecurity, home network security, personal cybersecurity, corporate cybersecurity, cyber threats, vulnerabilities, cyber hygiene, smart home security, cybersecurity practices, technology in cybersecurityTakeawaysCybersecurity is integral to everything we do.Home automation can introduce significant vulnerabilities.Singapore is a major source of DDoS attacks due to compromised devices.Many households are unknowingly compromised.Establishing an asset register is crucial for security.Devices have a shelf life and can become insecure over time.Implementing multiple layers of security is essential.Regular maintenance of devices is necessary for security.Cybersecurity practices should be scalable for home users.Taking ownership of personal cybersecurity is vital.Sound bites"Someone's hiding in your house.""Things do expire.""Be the path of greater resistance."Chapters01:30 The Ubiquity of Cybersecurity04:37 Personal Journey into Cybersecurity07:19 Understanding Cyber Threats and Vulnerabilities10:33 The Importance of Home Network Security13:26 Corporate vs. Personal Cybersecurity Practices16:32 Establishing Good Cyber Hygiene19:24 The Role of Technology in Cybersecurity22:19 Creating a Cybersecurity Workflow25:18 Scaling Cybersecurity Solutions for Homes28:35 The Future of Cybersecurity

In this conversation, Jon Scheele and Keith Carter explore the transformative impact of AI on business strategies, customer experiences, and career development. They discuss how organizations can leverage AI to enhance customer service, anticipate market moves, and foster creativity. Keith emphasizes the importance of actionable intelligence and the human element in AI-driven interactions, while also addressing the need for individuals to adapt and innovate in their careers amidst rapid technological changes.Key PointsKeith Carter, a seasoned expert in AI and digital finance, emphasizes that AI is more than just digital transformation. It's about enhancing business outcomes by understanding workflows and leveraging technology to improve customer service and profitability. AI's ability to perform hyper-personalization and market basket analysis allows businesses to anticipate customer needs and outperform competitors.Breaking Barriers with AI: AI reduces traditional barriers, enabling businesses to enter new markets and serve diverse customer bases. By automating language translation and market analysis, companies can expand their reach and deliver more value to existing customers, making relationships more "sticky" and reducing churn.The Human Element: Despite AI's capabilities, the human touch remains crucial. AI enhances, rather than replaces, human creativity and decision-making. As Keith Carter notes, AI distributes creativity, allowing teams to deliver high-quality outputs from anywhere in the world. This synergy between AI and human intelligence is where true innovation lies.AI is not just a tool; it's a strategic partner in business. As we embrace this technology, we must also inspire the next generation to be creators, not just consumers. The future of business strategy is here, and it's powered by AI.Chapters00:00 Navigating the AI Landscape10:28 AI's Role in Business Strategy19:52 Adapting Careers in the Age of AIKeywordsAI, business strategy, customer experience, technology, digital transformation, actionable intelligence, creativity, career development, innovation, data analytics

In this conversation, Jon Scheele and Buu Lam discuss the evolving landscape of API and AI gateways, the importance of security in technology, and the need for human oversight in AI-driven processes. They explore the challenges posed by evolving security threats and the necessity for individuals to adapt and embrace change in their careers.This interview features Jon Scheele speaking with Buu Lam, who is the Director of Community Evangelism at F5, at F5's App World event in Singapore.Key Discussion Points:F5's AI Gateway Launch Buu explains that F5 has launched an AI gateway (now in general availability) alongside their traditional API gateway. Unlike their existing API gateway architecture, the AI gateway uses WebAssembly processors that can build applications to handle AI flows, rather than relying on traditional TCL scripting and event-based programming.Unique Security Challenges with AI The conversation highlights how AI gateways face different security challenges than traditional API gateways. While API gateways primarily manage internal traffic with signature-based rules, AI gateways must analyze both incoming requests and outgoing responses for sophisticated attacks. Bad actors can use subtle language and semantics to bypass security measures through prompt injections, making traditional rule-based security insufficient.Human-in-the-Loop Considerations They discuss the balance between automated security responses and human oversight, particularly when dealing with high-stakes transactions worth millions of dollars. The question of how much "agency" to give AI security systems versus requiring human intervention for critical decisions remains a key consideration.Career Advice for Tech Professionals Buu offers provocative advice for technology professionals: actively work to replace yourself with AI. He argues that by pushing yourself to automate your current functions, you'll discover new areas where you can add value and evolve professionally, rather than being replaced by others who are already building these automated solutions.The interview emphasizes the evolving landscape of AI security and the need for professionals to adapt proactively to technological change.

In this conversation, Jon Scheele interviews Erik Wilde about the OpenAPI Initiative and its significance in the tech industry. They discuss the evolution of the OpenAPI Specification, the role of standards in fostering innovation, and the importance of building on standardized models. Erik emphasizes the concept of platform thinking and how it can drive market development, as well as the need for scaling API practices to enhance organizational capabilities. The discussion highlights the future of APIs and the ongoing trends in the industry.TakeawaysThe OpenAPI Initiative promotes the value of standards.Innovation is often built on established platforms.Standardized models can lead to consistent API development.APIs enable new services that were previously unimagined.Platform thinking is crucial for market development.Scaling API practices is essential for organizational growth.Effective API building requires a focus on security and efficiency.The evolution of OpenAPI reflects changing industry needs.Collaboration and sharing of APIs can drive innovation.Future trends in technology will heavily involve API scaling.KeywordsOpenAPI, API standards, innovation, platform thinking, scaling APIs, apidays, Erik Wilde, API governance, API design, technology trendsChapters00:00 Setting the Stage: Introduction and Context00:08 Understanding OpenAPI: Standards and Their Importance03:36 Innovation Through Standards: The Automotive Analogy07:07 Building on Platforms: The Role of APIs in Innovation08:49 Looking Ahead: Scaling API Practices for the Future

In this conversation, Jed Ng discusses his journey from tech operator to angel investor, sharing insights on investment strategies, geographic focus, and the challenges startups face in different markets. He emphasizes the importance of having a clear exit strategy, understanding cultural differences, and the necessity of building a local team for successful market expansion. The discussion also highlights the role of angel networks in fostering a diverse investment ecosystem and the need for startups to have a deliberate approach to growth.TakeawaysJed Ng transitioned from tech operator to angel investor.He runs an angel network with 1400 investors globally.Investors should have a focus thesis.Startups need a clear exit strategy for investors.Cultural and regulatory challenges vary by region.Singapore's small market requires startups to plan for offshore expansion.Companies must internalize control in new markets.Market expansion requires a deliberate plan.Testing the market with partners is crucial.A well-thought-out strategy is key to avoiding failure.Chapters00:00 Introduction to Angel Investing and Networking02:49 Navigating Market Expansion for Startups05:22 Challenges of Scaling in Diverse Markets08:02 Strategies for Successful Market Entry

In this conversation, Jon Scheele and Uli Hitzel discuss the transformative impact of generative AI on the software development landscape. Uli shares his journey into AI, emphasizing the importance of understanding language and how to apply Generative AI tools in coding and productivity. They explore various tools available for software developers, the significance of team management in adopting these tools, and the role of AI throughout the system development life cycle, including testing and deployment. The discussion highlights the need for developers to adapt and learn how to effectively utilize AI tools while maintaining best practices in coding and documentation.TakeawaysGenerative AI is set to revolutionize various industries, especially software development.Understanding language is crucial for leveraging AI effectively.Productivity tools like GitHub Copilot can significantly enhance coding efficiency.It's important for developers to maintain a balance between using AI tools and understanding the underlying code.Team management and tool integration are key to successful AI adoption in enterprises.AI can assist in various stages of the software development life cycle, including ideation and testing.Documentation remains a critical aspect of software development, often overlooked by developers.Security and compliance are essential considerations when deploying AI tools in production.Developers should focus on continuous learning and adaptation to new tools and technologies.The journey of integrating AI into workflows is ongoing and requires a collaborative approach.Sound Bites"AI is going to change everything.""You don't have to be a technical person to get superpowers with AI.""It's almost like back in school where you're not supposed to use a calculator."Chapters00:00 Introduction to Generative AI and Its Impact03:12 Uli's Journey into AI and Its Applications06:00 Understanding Language Models and Their Usefulness09:13 Productivity Tools for Software Development11:58 Managing Development Teams and Tool Integration14:50 The Role of AI in Software Development Life Cycle17:52 Testing and Quality Assurance with AI21:01 Deployment and Security Considerations in AI24:00 Conclusion and Future of AI in DevelopmentKeywordsGenerative AI, productivity, software development, language models, coding tools, team management, testing, deployment, securityMore at: https://www.apiconnections.io/podcast/putting-genai-to-work-in-software-development-with-uli-hitzel

In this conversation, Jon Scheele and F5's Community Evangelist, Buu Lam discuss key themes in DevOps resilience and observability. They explore the ongoing shift to multi-cloud strategies, the importance of ecosystem partnerships, and the challenges organizations face in integrating new technologies. The discussion also highlights the significance of resiliency and observability in cybersecurity, emphasizing the need for organizations to be aware of various signals and data points to make informed decisions.TakeawaysThe move to multi-cloud is essential for flexibility.Ecosystem partnerships are crucial for technology integration.Organizations must adapt their change management processes.Resiliency involves both machine and human elements.Observability is key to understanding system performance.Multiple data points are necessary for effective decision-making.The experience level of operators impacts incident response.Automation can enhance the ability to detect patterns.Compliance is critical for government and financial sectors.Understanding signals can prevent potential issues.Chapters00:00 Introduction to Cybersecurity and Observability02:33 Navigating Multi-Cloud Environments05:30 The Importance of Ecosystem Collaboration07:50 Resiliency and Observability in OperationsKeywordscybersecurity, multi-cloud, ecosystem partnerships, observability, resiliency, DevOps, automation, F5, Govware, technology integration

In this conversation, Jon Scheele and F5's Field CISO Chuck Herrin discuss the critical importance of API security in today's digital landscape, where API traffic constitutes a significant portion of overall internet traffic. They explore the unique vulnerabilities associated with APIs, the relevance of OWASP's Top 10 for API security, and the evolving threat landscape that organizations face. The discussion emphasizes the need for visibility and discovery of APIs, the risks posed by third-party APIs, and the emerging vulnerabilities related to AI. Herrin highlights the necessity of understanding the architecture and attack surfaces to effectively manage security risks.TakeawaysAPI traffic constitutes over 70% of overall internet traffic.OWASP's Top 10 for API security is more granular than traditional web security.Defenders often overlook API vulnerabilities due to legacy focus.Visibility is crucial for understanding API exposure and risks.Third-party APIs pose significant risks if not properly managed.AI introduces new vulnerabilities that require updated security measures.Organizations must understand their API architecture to protect against attacks.Monitoring and governance are essential for API security.The cybercrime economy is larger than the global drug trade.Defense in depth remains a fundamental principle in cybersecurity.KeywordsAPI security, OWASP, cybersecurity, vulnerabilities, third-party APIs, AI security, visibility, threat landscape, data protection, application securitySound Bites"APIs are just as much a cyber target.""API traffic is now the majority of web traffic.""You can't protect what you can't see."00:00 The Importance of API Security08:23 Understanding OWASP's Top 10 for API Security16:27 The Evolving Threat Landscape of APIs25:06 Visibility and Discovery of APIs33:41 Third-Party API Risks and Management42:00 AI and Emerging Vulnerabilities in API Security

SummaryIn this conversation, Jon Scheele and Nilesh Gule discuss the critical role of automation in DevOps, particularly through the use of Kubernetes. They explore the benefits and challenges of Kubernetes, emphasizing the complexities involved in debugging and managing Kubernetes clusters. Nilesh introduces K8sGPT, a generative AI tool designed to assist in diagnosing and resolving issues within Kubernetes environments. The discussion also touches on the future of Kubernetes management, highlighting the potential for AI to enhance operational efficiency while still requiring human oversight.TakeawaysAutomation is essential for effective DevOps practices.Kubernetes simplifies deployment but adds complexity in debugging.Debugging in Kubernetes requires expertise across multiple components.K8S GPT leverages AI to assist in Kubernetes troubleshooting.Generative AI can provide solutions in multiple languages.Human operators remain crucial in the debugging process.Visualizing Kubernetes issues can enhance understanding and resolution.AI tools can help onboard new developers more efficiently.Partial automation of minor issues could improve operational efficiency.The future of Kubernetes management will increasingly involve AI assistance.Sound Bites"Automation is one of the key tenets of DevOps.""Kubernetes has become like a de facto orchestrator.""The more moving parts there are, the more that can go wrong."Chapters00:00 The Importance of Automation in DevOps08:59 Understanding Kubernetes: Benefits and Challenges18:03 Leveraging AI for Kubernetes Debugging24:52 Future of Kubernetes Management with AIReferences:K8sGPT web sitehttps://k8sgpt.ai/K8sGPT GitHub repohttps://github.com/k8sgpt-ai/k8sgpt

SummaryIn this conversation, Jon Scheele and Nilesh Gule explore the complexities and evolution of DevOps, emphasizing its role in enhancing collaboration between development and operations teams. They discuss the importance of agility, automation, and the integration of testing and security within the development lifecycle. The conversation also touches on organizational structures and how they impact the implementation of DevOps practices, as well as the evolution of DevOps into platform engineering.TakeawaysDevOps aims to promote collaboration between developers and operations.The complexity of implementing DevOps varies by organization size.Agility is a key reason for adopting DevOps practices.Continuous integration has become a standard practice.Shifting left integrates testing and security earlier in development.Organizational structure influences DevOps implementation.Mature tools have simplified DevOps practices.DevSecOps has shifted security considerations earlier in the cycle.Platform engineering is the next evolution of DevOps.Automation is essential for achieving agile development.Sound Bites"DevOps is a set of principles.""The aim of DevOps is to increase collaboration.""Agile is more about doing iterative development."Chapters00:00 Understanding DevOps: Origins and Objectives04:10 The Complexity of Implementing DevOps09:22 Agility and Automation in DevOps14:18 The Evolution of DevOps PracticesKeywordsDevOps, Agile, Automation, Continuous Integration, Continuous Deployment, Shift Left, Security, Organizational Structure, Platform Engineering, Software Development

In this episode of the API Connections Podcast, Jon Scheele continues his deep dive into the complexities of AI governance with data scientist Koo Ping Shung. Following their discussion on AI bias and transparency, they explore the challenges organizations face in implementing robust data practices and the pivotal role of documentation in AI governance. Koo emphasizes the need for building trustable AI, arguing that trust, rather than strict adherence to governance or ethics alone, is the key to successful AI deployment. Together, they delve into the nuances of documentation, knowledge management, and the human element in AI, offering insights into creating AI systems that are both reliable and aligned with human values.Sections:Challenges in Using Data and AIThe Importance of Documentation for AI GovernanceTesting Models and Creating ModelsThe Challenge of DocumentationUsing AI for Documentation and Knowledge ManagementContinuous Improvement and Data QualityBuilding Trustable AICommunication and Decision-Making in AI GovernanceThe Limitations of AI Ethics

This conversation between Jon Scheele and data scientist Koo Ping Shung is broken into two parts. In part one, we discuss the complexities of AI governance and the need for expertise across several disciplines to make it effective. We discuss bias in AI and the importance of transparency and a review mechanism to address that bias. And we discuss how it's up to all of us to gain AI literacy, so that we can ensure that AI works for us rather than against us. So enjoy part one.The conversation explores the topic of AI governance and how to build trustable AI. Koo Ping Shung discusses the evolution of the data science industry and the increasing focus on AI governance. He emphasizes that bias in AI cannot be completely eliminated but can be reduced through awareness and transparency. Koo suggests that AI governance committees should include individuals with technical, legal, policy-making, economics, and audit backgrounds. He also highlights the importance of AI literacy for consumers and the need for dedicated channels to address concerns and appeals.KeywordsAI governance, trustable AI, bias, data science, evolution, transparency, awareness, AI literacy, consumer concerns, appeals, data, reporting, performance metrics, visualization, AI, governanceTakeawaysAI governance is essential to ensure the responsible and ethical use of AI.Bias in AI cannot be completely eliminated but can be reduced through awareness and transparency.AI governance committees should include individuals with diverse backgrounds, including technical, legal, policy-making, economics, and audit.AI literacy is crucial for consumers to understand and protect themselves from potential abuses.Dedicated channels should be established for consumers to raise concerns and appeals regarding AI decisions.01:22 The Evolution of the Data Science Industry and the Rise of AI08:06 The Role of Committees in AI Governance09:37 Addressing Bias in AI23:16 Creating Effective AI Governance Committees26:47 Establishing Dedicated Channels for Consumer Concerns in AI

The conversation discusses the Open Gateway Initiative by GSMA, which aims to enhance interoperability between telecommunications carriers through the use of APIs. Alex Szomora, the Senior Go-To-Market Project Manager for GSMA's Open Gateway Initiative, shares her career path and how she came to be in her current position. The conversation also covers the objectives of the Open Gateway Initiative and the related Camara project under the Linux Foundation. The challenges and opportunities in adopting the APIs are discussed, along with the future of the initiative and the potential for new services and APIs.KeywordsAPIs, Open Gateway Initiative, telecommunications, interoperability, carriers, Camara project, GSMA, career path, cybersecurity, digital identity, services, adoption, futureTakeawaysThe Open Gateway Initiative by GSMA aims to enhance interoperability between telecommunications carriers through the use of APIs.The initiative has attracted membership from telecommunications carriers and solution vendors, with a focus on creating an ecosystem.The adoption of the Open Gateway APIs starts with core APIs such as anti-fraud and authentication, and then expands to other services.Challenges in adopting the APIs include cultural and historical mind shifts, legal questions, and pricing and revenue discussions.The future of the initiative involves the rollout of newer technologies like 5G and the development of new services and APIs.TitlesThe Journey to the Open Gateway InitiativeAdopting the Open Gateway APIs: Challenges and OpportunitiesSound Bites"APIs are pervasive across all industries, including telecommunications.""Being able to cross over between specializations is really powerful.""The Open Gateway Initiative has the potential to be one of the next big achievements in the mobile phone industry."Chapters00:00 Introduction to the Open Gateway Initiative05:02 Career Path and Specializations in API Program Management09:09 Objectives and Membership of the Open Gateway Initiative12:35 The Open Gateway Ecosystem and Partnerships23:39 The Future of the Open Gateway Initiative

Chris Birrell, an investor specializing in API startups, shares his insights on what he looks for before investing in API-enabled services. He discusses his background in computer science and his experience in the tech industry, which led him to become an investor. Chris introduces the 'SUPERIOR' Framework that he uses to evaluate API startups, focusing on attributes such as solving difficult problems, uncovering unique solutions, and pathways to profitability and exit. He also highlights the opportunities and challenges in the API space, particularly in the context of AI and globalizing businesses.KeywordsAPI startups, investing, API-enabled services, Superior Framework, solving difficult problems, unique solutions, pathways to profitability, AI, globalizing businessesTakeawaysInvestors in API startups look for companies that solve difficult problems in a scalable and economically viable way.The 'Superior Framework' is a matrix that evaluates attributes such as problem-solving, uniqueness, profitability, ecosystem, regional focus, impact, ownership, and regulatory tailwinds.APIs play a crucial role in the future of software development, particularly in the context of AI, blockchain, and IoT ecosystems.API startups need to consider the challenges of being substituted by competitors and focus on creating a compelling product and having outstanding founders.APIs that facilitate globalizing businesses and address specific regional challenges can provide unique opportunities.API startups should aim to be essential to the priorities and budgets of CIOs, especially in the context of increasing investments in AI.Sound Bites"The API or the API platform needs to be solving a difficult problem in a very narrow and deep way.""Uncovering unique and novel solutions is a leading indicator of something important.""You've got to have a compelling enough product that doesn't stop those guys from spending money."Chapters00:00 Introduction: Investing in API Startups07:08 The Role of APIs in the Future of Software Development12:30 The 'SUPERIOR' Framework for Evaluating API Startups20:47 Mitigating the Risk of Substitution in API Business Models22:36 Insights from the apidays Singapore Conference24:02 The Importance of Being Essential to CIO Priorities and Budgets25:24 Conclusion and Contact Information

In this conversation, Jon Scheele interviews Abhijit Dey, VP of API Banking at Axis Bank, about Open Banking and Embedded Finance in India. They discuss the growth of Open Banking in India, the role of APIs in the banking industry, and the impact of digital transformation on customer experience. Abhijit shares his insights on the future of Open Banking, the importance of API governance, and the skills required to be an API Product Manager.Keywordsopen banking, embedded finance, India, APIs, digital transformation, customer experience, API product managerTakeawaysOpen banking is growing in India, with banks becoming API-first and adopting digital public infrastructure to increase financial inclusion.APIs are becoming a revenue stream and a way to offer hyper-personalized customer experiences.API product managers need to have a technical understanding of APIs and a design thinking mindset to identify and solve customer problems.Success metrics for API product managers include adoption, revenue generation, and customer engagement.The future of open banking depends on API governance and the ability to build APIs that address specific use cases.Aspiring API product managers should learn how APIs work and focus on customer-oriented innovation.Sound Bites"APIs will be created or technologies will be built in the blink of an eye.""API Sprawl: The more digitized our ecosystems are getting, the more we are building APIs.""The future of open API banking is very bright."Chapters00:00 Introduction: Open Banking and API Banking in India04:08 Setting up the API Function at Axis Bank07:01 The India Digital Stack and its Impact on the Indian Economy12:43 The Future of Open Banking and API Banking26:51 The Importance of Governance and Framework in API Banking30:35 Building a Career as an API Product ManagerLink to Abhijit’s presentation at apidays Singapore 2024:API Productisation: Shift RIGHT to better product resiliencehttps://www.youtube.com/watch?v=wOy5vCS7kAYLinks to Abhijit’s articles:Roles of API product managers beyond the conventional product management responsibilitieshttps://www.linkedin.com/pulse/roles-api-product-managers-beyond-conventional-management-abhijit-dey/The Red Flags of API Sprawl: What to Watch Forhttps://www.linkedin.com/pulse/red-flags-api-sprawl-what-watch-abhijit-dey-o5hxf/Untangling API Sprawl: Understanding the Causes of Integration Chaoshttps://www.linkedin.com/pulse/untangling-api-sprawl-understanding-causes-integration-abhijit-dey-ytoaf/

Aki Ranin, co-founder of Bambu, and currently CTO of Goldberry Wealth, discusses the interconnection between AI and APIs. He shares his journey in the AI data science space and explains how AI and APIs are intricately linked. Aki highlights the potential of large language models and AI agents in transforming industries and making AI-assisted tasks more efficient. He also discusses the challenges of discoverability and the importance of metadata in making information accessible to AI agents. Aki provides recommendations for individuals looking to understand the trajectory of AI and APIs.KeywordsAI, APIs, data science, large language models, AI agents, discoverability, metadataSound Bites"AI and APIs are intricately interwoven""Moving from small chat bots to embodied AI systems""Building for consumption by AI agents"Chapters00:00 The Interconnection of AI and APIs07:22 The Potential of AI-Assisted Financial Planning13:50 Integrating Large Language Models and AI Agents26:14 Staying Ahead in the AI and API Space