We discuss Prompt Declaration Language (PDL), a revolutionary approach to AI infrastructure that addresses the current "black-box" nature of prompt engineering. It argues that traditional methods, relying on unpredictable "magic prompts", are unsustainable and lead to a scalability crisis in enterprise AI. PDL, developed by IBM and open-sourced, utilizes a transparent, YAML-based declarative language to define AI interactions and workflows, transforming opaque prompts into version-controlled, debuggable, and optimizable components. This shift promises to make AI development more akin to traditional software engineering, enabling collaboration, reliability, and improved performance through explicit, reviewable, and testable AI logic. The text emphasizes that embracing such transparent and accountable AI practices is crucial for future innovation and trustworthiness in AI systems.

Bit & Being - PDL is to Prompts as git was to Code

Fresh out of the studio, David Hardoon, Global Head of AI Enablement at Standard Chartered Bank, joins us in a conversation to explore how financial institutions can adopt AI responsibly at scale. He shares his unique journey from academia to government to global banking, reflecting on his fascination with human behavior that originally drew him to artificial intelligence. David explains how his time at Singapore's Monetary Authority shaped the groundbreaking FAIR principles, emphasizing how proper AI governance actually accelerates rather than inhibits innovation. He highlights real-world implementations from autonomous cash reconciliation agents to transaction monitoring systems, showcasing how banks are transforming operations while maintaining strict regulatory compliance. Addressing the biggest misconceptions about AI governance, he emphasizes the importance of integrating AI frameworks into existing structures rather than creating entirely new bureaucracies, while advocating for use-case-based approaches that build essential trust. Closing the conversation, David shares his philosophy that AI success ultimately depends on understanding human behavior and asks the fundamental question every organization should consider: "Why are we doing this?"

"[Question: So what was the biggest misconception for most business leaders usually when it comes to operationalizing AI governance?]
Based on my interactions and conversations, now suddenly they think they have to erect a whole set of new committees, that they have to have these new programs. You almost hear a sigh from the room. Like, oh, we have now this whole additional compliance cost because we have to do all these new things. The reason I see that as a bit of a misconception, because building on everything that was just said earlier, you already have compliance, you already have committees, you already have governance. It's an integration of that because otherwise guess what's gonna happen? We all know that this is the next thing around the corner that's gonna pop up, whatever it's gonna be called. Are you gonna have to set up a whole new committee just because of that? Then the next thing, another one." - David Hardoon

Episode Highlights: 
[00:00] Quote of the Day by David Hardoon #QOTD - "AI governance isn't new bureaucracy."
[00:46] Introduction: David Hardoon from Standard Chartered Bank.
[02:02] How David's AI journey started with human behavior curiosity.
[07:26] Governance accelerates innovation, like traffic rules enable fast driving.
[10:31] FAIR principles in MAS Singapore born from lunches with compliance officers.
[14:23] Don't reinvent governance wheel for AI implementations.
[24:17] Banks already manage risk; apply same discipline to AI.
[28:40] AI adoption problem is trust, not technology.
[34:21] Autonomous AI agents handle cash reconciliation with bank IDs.
[36:00] AI reduces transaction monitoring false positives by 50%.
[39:54] AI requires full supply chain from infrastructure to translators.
[41:52] Organizations must reward intelligent failure in AI innovation.
[44:47] AI hallucination is a feature, not bug for innovation.
[47:35] Measure AI ROI differently for innovation versus implementation teams.
[56:27] Final wisdom: People always ask "why" about AI initiatives.

Profile: David Hardoon, Global Head of AI Enablement, Standard Chartered Bank 
Personal Site: https://davidroihardoon.com/
LinkedIn: https://www.linkedin.com/in/davidrh/

Enabling AI at Scale: Governance as Competitive Advantage with David Hardoon

Join us on this episode as we unpack the rise of GUI-native AI agents, - the screen-savvy digital collaborators rewriting automation rules. We explore how ByteDance’s UI-TARS and other pioneers teach machines to click, type, and adapt like humans, slashing development time and future-proofing workflows. Discover why traditional RPA scripts crumble at the slightest UI tweak, what this shift means for enterprise agility, and how leaders can leverage on-screen AI while navigating trust, governance, and accessibility challenges.

Bit and Being - The Screen Is Alive: The Promise of GUI‑Native AI Agents

What happens when your AI systems stop working in silos and start learning from each other? In this episode, we unpack the revolutionary shift toward cross-agent learning, - where autonomous AI agents share insights, build institutional memory, and turbocharge enterprise intelligence. Join us as we explore real-world applications, uncover hidden inefficiencies in today’s AI strategies, and ask: are your digital teammates as collaborative as your human ones? Whether you're leading AI transformation or just trying to stay ahead of the curve, this is one conversation you won’t want to miss.

Bit & Being - Cross Agent Knowledge Inheritance

Fresh out of the studio, Doug Burger, Technical Fellow and Corporate Vice President at Microsoft Research, joins us to explore Microsoft's bold expansion into Southeast Asia with the recent launch of the Microsoft Research Asia lab in Singapore. From there, Doug shares his accidental journey from academia to leading global research operations, reflecting on how Microsoft Research's open collaboration model empowers over thousands of researchers worldwide to tackle humanity's biggest challenges. Addressing the intersection of three computing paradigms: logic, probability, and quantum, he emphasizes that geographic diversity in research labs enables Microsoft to build AI that works for everyone. Closing the conversation, Doug shares his vision of what great looks like for Microsoft Research with researchers driven by purpose and passion to create breakthroughs that advance both science and society.

"If you're going to be running a very elite research institution, you have to have the best people. To have the best people, you have to trust them and empower them. You can't hire a world expert in some area and then tell them what to do. They know more than you do. They're smarter than you are in their area. So you've got to trust your people. One of our really foundational commitments to our people is: we trust you. We're going to work to empower you. Go do the thing that you need to do. If somebody in the labs wants to spend 5, 10, 15 years working on something they think is really important, they're empowered to do that."

Episode Highlights:
[00:00] Quote of the Day by Doug Burger 
[01:08] Doug Burger's journey from academia to Microsoft Research
[03:07] Launch of Microsoft Research Asia in Singapore: Tapping local talent and culture for inclusive AI development
[04:13] Singapore lab focuses on foundational AI, embodied AI, and healthcare applications
[06:19] AI detecting seizures in children and assessing Parkinson's motor function
[08:24] Embedding Southeast Asian societal norms & values into Foundational AI research
[10:26] Microsoft Research's open collaboration model 
[12:42] Generative AI's rapid pace accelerating technological innovation and research tools
[16:24] Open versus closed source AI models debate and Microsoft's platform approach
[19:35] Multiple scaling dimensions in AI beyond traditional data scaling laws
[26:26] Balancing blue-sky foundational research with application-driven initiatives at scale
[35:26] Research leadership secret: Curiosity across fields enables unexpected connections
[40:04] Microsoft Research's vision: Becoming Bell Labs for AI era
[42:22] Steering AI models for mental health and critical thinking conversations

How Microsoft Research Balances Exploration and Impact Globally with Doug Burger

The article "Cognitive Enterprise: Brain-Inspired AI for Business Advantage," by Dr. Jerry A. Smith, argues for a paradigm shift in enterprise AI from traditional, siloed systems to brain-inspired AI agents powered by knowledge graphs. It explains that, unlike current AI that processes data like "sophisticated spreadsheets," this new approach enables machines to reason with interconnected information through networks of meaning, mimicking how the human brain functions. The author highlights the competitive imperative for businesses to adopt this "neurosymbolic" AI, which combines neural networks' pattern recognition with symbolic reasoning, offering advantages in speed, insight quality, scalability, and transparency. The text further outlines a four-stage roadmap for organizations to transition to a "cognitive enterprise," emphasizing the construction of knowledge graphs, modular agent development, intelligent scaling, and ultimately, enterprise-wide transformation for sustained competitive advantage.

Your Enterprise AI Has No Brain. Here's How to Give It One

OpenAI’s two-front blitz, - GPT-5 at the frontier and GPT-OSS in the wild, could reset your AI roadmap. In this episode, “The Two-Move Checkmate,” we unpack what the pincer means for budgets, data governance, and developer velocity, and contrast it with moves from Meta, Anthropic, Google, and Mistral. Are open weights a strategic gift or a scorched-earth moat? When should you go local vs. cloud? And what becomes the real edge when models commoditize? Smart, fast, and actionable, - tune in.

Bit & Being - The Two-Move Checkmate: Inside OpenAI’s Playbook

In this episode, we dive into Google DeepMind’s groundbreaking Gemini 2.5 “Deep Think”, - the multi-agent AI model reshaping what’s possible in enterprise problem-solving. From achieving gold-medal math scores to delivering 30% gains in code generation, we unpack how parallel reasoning and the “swarm advantage” can transform strategy, R&D, and long-horizon planning. Join us as we compare Deep Think to GPT-4 and Claude, explore its real-world applications, and ask: is the era of the lone genius AI over?

Bit & Being - From Chatbot to Think Tank: The Swarm Advantage and Parallel Reasoning

Fresh out of the studio, Nick Eayrs, Vice President of Field Engineering for Asia Pacific and Japan at Databricks, and Simon Fassot, General Manager and Head of Global Data and Analytics at Hafnia, join us to explore how data intelligence is transforming enterprise AI across diverse industries in Asia. Nick explained the fundamental distinction between general intelligence and data intelligence - emphasizing how enterprises gain competitive advantage by training AI on their proprietary data rather than public knowledge. Nick showcased customer success stories including Standard Chartered Bank and TechComBank and shared his perspectives on how senior executives can take advantage of AI by moving fast rather than wait and see. Last but not least, Nick offered what great would look like for Databricks in Asia Pacific and Japan in serving their customers. Adding the lens of the customer, Simon shared Hafnia's transformation from legacy SQL Server systems to a unified Databricks architecture serving their global shipping operations and elaborated on how the company is breaking down silos with their data supermarket and "Marvis" AI copilot for maritime operations based on retrieval augmented generation. 

"I think the biggest trap to potentially fall into is, "Hey, it's moving so fast, so much is changing. Let's just wait it out." Completely the wrong approach. You just gotta get started." Nick Eayrs from Databricks

"As tech people within the shipping industry, how do we explain, how do we make it accessible to all our users? So that's where we came up with the idea of a data supermarket, with in mind really the target of enabling self-service for our business. So by giving the analogy of a supermarket, it was much easier at the beginning to explain our business." - Simon Fassot from Hafnia

Episode Highlights:
[00:00] QOTD by Nick Eayrs and Simon Fassot
[00:49] Introduction: Nick Eayrs from Databricks
[03:32] Customer obsession means deeply understanding their business context
[05:22] Data intelligence versus artificial general intelligence explanation begins
[06:42] AI trained on your data creates competitive advantage
[08:17] Only 15% of companies have correct AI infrastructure ready
[11:17] Don't wait for AI perfection, just get started now
[12:30] Agent Bricks simplify AI development using natural language
[18:32] Shared responsibility model for ethical AI deployment
[25:24] Asia Pacific psychology focuses on future, not past
[26:28] Most important question: How do you get started?
[30:18] What does great look like for Databricks?
[33:16] Introduction: Simon Fassot from Hafnia
[35:18] How Hafnia transformed to full cloud architecture centralizes data through Databricks
[36:28] Self-service access needed for 300 onshore, 4000 vessel employees
[41:32] Unity catalog controls data quality for AI cases
[42:21] Two-phase Gen AI: ingest unstructured, then consume data
[44:25] How to implement Generative AI: One bad AI answer loses all user trust
[45:31] How reports in Hafnia use RAG embedded in workflows
[46:47] Data supermarket analogy simplifies self-service for business
[48:39] Marvis AI personalizes Gen AI within company context 
[49:46] Neo4j partnership adds graph capabilities to ecosystem
[53:33] DNA Port platform unifies scattered dashboards and applications
[54:22] Databricks enables focus on business value over operations

Profiles:
Nick Eayrs, Vice President of Field Engineering, Asia Pacific & Japan at Databricks
LinkedIn: https://www.linkedin.com/in/nick-eayrs/

Simon Fassot, General Manager and Head of Global Data and Analytics at Hafnia
LinkedIn: https://www.linkedin.com/in/simon-fassot-68b95135/

Podcast Information: Bernard Leong hosts and produces the show. The proper credits for the intro and end music are "Energetic Sports Drive." G. Thomas Craig mixed and edited the episode in both video and audio format. 

#dataaiworldtour #databricks #enterpriseai #retrievalaugmentedgeneration #dataintelligence

The Truth About Enterprise AI & Why Data Matters with Nick Eayrs and Simon Fassot

Fresh out of the studio, Craig Wiley, Senior Director of Product Management at Databricks who leads Mosaic AI, joins us to discuss the forefront of enterprise AI from model development to deployment at scale. Beginning with his career journey in ML operations, Craig explained how he recognized the critical connection between data and AI layers that could deliver order-of-magnitude acceleration in development cycles. Emphasizing the transition from classical ML operations to LLM operations, he showcased how Databricks' unified platform eliminates training-serving skew through data lineage capabilities and supports both fine-tuning and RAG approaches depending on industrial use case requirements. Highlighting compelling customer success stories including Suncorp's employee productivity platform and AstraZeneca's transformation of 400,000 clinical trial documents into queryable insights, Craig revealed a striking reality about enterprise AI evaluation - that 85% of AI use cases are being evaluated only by the engineers who built them, reinforcing that proper evaluation frameworks remain foundational for trustworthy AI implementation. He concluded by introducing Agent Bricks as Databricks' evaluation-centric approach to building production agents, emphasizing that model flexibility and rigorous testing are essential for enterprises moving from experimentation to production, while sharing his vision that the industry must evolve from the "year of agents" to the "year of evaluation and quality."

"85% of AI use cases are being evaluated by the engineer who built it saying, 'yep, seemed to work pretty well.' If you're gonna build a system that's going to be critical to the business, that's going to be important that it gets it right, then you can't do that without evaluations." - Craig Wiley

Episode Highlights: 
[00:00] Quote of the Day by Craig Wiley
[01:21] How Craig Wiley started his work in ML Ops that led him to Databricks
[02:43] Data and AI layer connection creates order-of-magnitude acceleration
[03:47] Mosaic AI acquisition expanded Gen AI solution capabilities
[04:38] Classical ML statistics versus Gen AI evaluation challenges
[05:48] Mosaic AI covers end-to-end from data ingestion
[07:12] Training-serving skew eliminated through unified platform lineage
[08:51] Fine tuning versus RAG depends on use case
[10:49] Industrial agents benefit from fine-tuned smaller models
[13:52] Agent Bricks prioritizes accuracy over simplicity alone
[15:44] Model flexibility crucial for speed and accuracy optimization
[17:59] Suncorp and AstraZeneca demonstrate diverse AI applications
[19:37] Asia Pacific shows aggressive AI adoption strategies
[22:00] 85% of AI cases evaluated only by building engineer
[24:12] Industry terminology evolves rapidly from RAG to agents
[25:39] Customer creativity with governance capabilities inspires product development

Profile: Craig Wiley, Senior Director of Product Management at Databricks and Mosaic AI
LinkedIn: https://www.linkedin.com/in/craigwiley/

Podcast Information: Bernard Leong hosts and produces the show. The proper credits for the intro and end music are "Energetic Sports Drive." G. Thomas Craig mixed and edited the episode in both video and audio format. 

Here are the links to watch or listen to our podcast.
Analyse Asia Main Site: https://analyse.asia
Analyse Asia Spotify: https://open.spotify.com/show/1kkRwzRZa4JCICr2vm0vGl 
Analyse Asia Apple Podcasts: https://podcasts.apple.com/us/podcast/analyse-asia-with-bernard-leong/id914868245 
Analyse Asia LinkedIn: https://www.linkedin.com/company/analyse-asia/


#dataaiworldtour #databricks #enterpriseai #retrievalaugmentedgeneration #agentbricks #evalsAI #evaluationAI #MLOps

Agent Bricks and How Data-AI Integration Changes Everything with Craig Wiley

A weekly podcast dissecting the pulse of business, technology & media in Asia. Hear our host interviewing leading journalists, senior executives, respectable authors & thinkers, entrepreneurs & thought leaders to discuss the most important issues that move and shake the business landscape in the Asia Pacific. The show is originally created and hosted by Bernard Leong.

In-Depth Explorations of Neuroscience-Inspired Architectures Revolutionizing AI.

New tracks tagged #Enterprise AI