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.

Professor Karin Verspoor, Executive Dean of Computer Science, RMIT University

natural 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 learning

Jon 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.

• Karin’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.

• "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 discipline
• Using Backstage for software catalogs, golden paths, and scaffolding templates
• Managing software supply chain dependencies
• Why contractors and efficiency drove investment in opinionated patterns
• The shift from programmatic to intent-based development
• Agentic AI: boundaries, guardrails, and explainability requirements
• Essential skills for the AI era: storytelling and critical thinkingHow AI can help with documentation without eliminating human responsibility

Notable 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.io

Subscribe & Review:
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Timestamps:
00:00 Introduction
00:30 Welcome and background
01:27 Akhil's background across consulting, customer, and vendor roles
03:00 The Log4j supply chain vulnerability story
03:46 How software catalogs saved the day
05:28 Undifferentiated heavy lifting and contractor efficiency
08:20 The importance of technical hygiene
09:54 AI, governance, and technology estate management
10:56 Generative vs. agentic AI: predictability matters
12:26 Boundaries and explainability in agentic systems
14:24 Intent-based development and documentation
16:50 Essential skills: storytelling and critical thinking
21:01 Closing thoughts

Tags: #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.

Takeaways

• Data 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."

Chapters

00:00 The Challenge of Data Integration

01:48 Understanding E-Invoicing Complexity

08:47 Standards in E-Invoicing: Benefits and Limitations

14:01 Balancing Standardization and Innovation

22:07 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.


Keywords

cybersecurity, home network security, personal cybersecurity, corporate cybersecurity, cyber threats, vulnerabilities, cyber hygiene, smart home security, cybersecurity practices, technology in cybersecurity


Takeaways

Cybersecurity 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."


Chapters

01:30 The Ubiquity of Cybersecurity
04:37 Personal Journey into Cybersecurity
07:19 Understanding Cyber Threats and Vulnerabilities
10:33 The Importance of Home Network Security
13:26 Corporate vs. Personal Cybersecurity Practices
16:32 Establishing Good Cyber Hygiene
19:24 The Role of Technology in Cybersecurity
22:19 Creating a Cybersecurity Workflow
25:18 Scaling Cybersecurity Solutions for Homes
28:35 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 Points

Keith 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.

Chapters

00:00 Navigating the AI Landscape
10:28 AI's Role in Business Strategy
19:52 Adapting Careers in the Age of AI

Keywords

AI, 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.

Takeaways

• The 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.

Keywords
OpenAPI, API standards, innovation, platform thinking, scaling APIs, apidays, Erik Wilde, API governance, API design, technology trends

Chapters

00:00 Setting the Stage: Introduction and Context
00:08 Understanding OpenAPI: Standards and Their Importance
03:36 Innovation Through Standards: The Automotive Analogy
07:07 Building on Platforms: The Role of APIs in Innovation
08:49 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.

Takeaways

• Jed 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.

Chapters

00:00 Introduction to Angel Investing and Networking
02:49 Navigating Market Expansion for Startups
05:22 Challenges of Scaling in Diverse Markets
08:02 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.

Takeaways

• Generative 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."
  
  
  Chapters
  
  00:00 Introduction to Generative AI and Its Impact
  03:12 Uli's Journey into AI and Its Applications
  06:00 Understanding Language Models and Their Usefulness
  09:13 Productivity Tools for Software Development
  11:58 Managing Development Teams and Tool Integration
  14:50 The Role of AI in Software Development Life Cycle
  17:52 Testing and Quality Assurance with AI
  21:01 Deployment and Security Considerations in AI
  24:00 Conclusion and Future of AI in Development
  
  
  Keywords
  
  Generative AI, productivity, software development, language models, coding tools, team management, testing, deployment, security
  
  

More 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.

Takeaways

The 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.

Chapters

00:00 Introduction to Cybersecurity and Observability
02:33 Navigating Multi-Cloud Environments
05:30 The Importance of Ecosystem Collaboration
07:50 Resiliency and Observability in Operations

Keywords

cybersecurity, multi-cloud, ecosystem partnerships, observability, resiliency, DevOps, automation, F5, Govware, technology integration