Are your AI initiatives stalling at proof-of-concept? Up to 95% of AI pilots fail to deliver measurable profit impact, often due to fragmentation, lack of governance, and absence of strategic alignment. In this episode, we explore how Enterprise Architecture (EA) becomes the essential backbone for turning isolated AI experiments into scalable, sustainable business capabilities.

Join us as we dive into how EA acts as a dynamic capability that enables organizations to sense, seize, and transform around GenAI—all while forging real business value. We unpack the Architecture of AI Transformation framework, highlighting how to move beyond incremental automation toward a new frontier of Collaborative Intelligence, where human judgment and AI scale merge effectively.

You’ll learn how EA operationalizes scalable AI across four pillars: Business Alignment, System Integration, Process Awareness, and Governance & Accountability. We’ll also unpack how composable AI architectures and “glass-box” governance prepare you for regulatory demands like the upcoming EU AI Act (August 2026).

If you’re responsible for AI strategy, digital transformation, or enterprise architecture, this episode gives you practical insights and research-based models to embed AI not just as an experiment—but as a core, governed, and high-impact capability.

What you’ll get:

• Why AI pilots so often fail to scale — and how EA solves that gap.

• How to treat EA as a dynamic capability: sensing opportunities, seizing demand, transforming operations.

• How to think beyond process automation toward collaborative intelligence (human + machine).

• The four pillars of scalable, governed AI: business alignment, system integration, process awareness, and governance.

• Real-world implications for reuse, composable architecture, workflow redesign and regulatory readiness (EU AI Act).

Credits & References:
Based on foundational research from:

• Ettinger, A. (2025). Enterprise Architecture as a Dynamic Capability for Scalable and Sustainable Generative AI Adoption. Warwick Business School.

• Wolfe, D. A., Choe, A., & Kidd, F. (2025). The Architecture of AI Transformation: Four Strategic Patterns and an Emerging Frontier.

• Zeman, B. (2025). Why Enterprise Architecture Is the Missing Link in Scalable AI. Built In.

• Built In. Enterprise Architecture for Scalable AI Implementation.

In this episode of State of AI, we explore how artificial intelligence is reshaping the foundations of the software industry. Drawing on insights from McKinsey’s 2025 report Upgrading Software Business Models to Thrive in the AI Era, we unpack how AI is transforming SaaS from a tool that enables work to a platform that performs it.

Learn why traditional subscription models are evolving toward consumption-based pricing, how companies like Salesforce, Adobe, and ServiceNow are experimenting with AI-driven monetization, and what it takes to align pricing, GTM strategy, and customer value in the new AI economy.

We’ll also dive into:

• The $4.4 trillion productivity potential of AI in enterprise software

• Real-world examples of AI monetization success and failure

• Why change management now costs 3x more than model development

• How CFOs and GTM teams can prepare for AI-driven revenue models

• The new role of AI agents in redefining customer value and pricing

If you’re a tech executive, SaaS founder, or digital strategist, this episode will help you understand how to adapt your business model to capture the next software supercycle.

Join us for an insightful exploration into the world of Reasoning LLMs, drawing on the expertise of Sebastian Raschka, PhD. This episode demystifies how Large Language Models (LLMs) are being refined to excel at complex tasks that require intermediate steps, such as solving puzzles, advanced mathematics, and challenging coding problems, moving beyond simple factual question-answering.

We'll uncover the four main approaches currently used to build and improve these specialised reasoning capabilities:

• Inference-time scaling: Discover how techniques like Chain-of-Thought (CoT) prompting encourage LLMs to generate intermediate reasoning steps, mimicking a 'thought process' and often leading to more accurate results on more complex problems. This approach increases computational resources during inference, making it more expensive.
• Pure Reinforcement Learning (RL): Learn about the surprising emergence of reasoning behaviour from pure reinforcement learning, as demonstrated by DeepSeek-R1-Zero. This model was trained exclusively with RL, without an initial supervised fine-tuning (SFT) stage, using accuracy and format rewards to develop basic reasoning skills.
• Supervised Fine-tuning (SFT) + Reinforcement Learning (RL): Understand this key approach for building high-performance reasoning models, exemplified by DeepSeek's flagship R1 model. This method refines models with additional SFT stages and further RL training, building upon "cold-started" pure RL models.
• Pure SFT and Distillation: Explore how smaller, more efficient reasoning models can be created by instruction fine-tuning them on high-quality SFT data generated by larger, stronger LLMs. This approach is particularly attractive for creating models that are cheaper to run and can operate on lower-end hardware.

We'll also discuss when to use reasoning models – they are ideal for complex challenges but can be inefficient, more verbose, and expensive for simpler tasks, sometimes even being "prone to errors due to 'overthinking'". The episode provides valuable insights from the DeepSeek R1 pipeline as a detailed case study and touches upon comparisons with models like OpenAI's o1. Plus, get tips for developing reasoning models on a limited budget, including the promise of distillation and innovative methods like 'journey learning', which includes incorrect solution paths to teach models from mistakes. Tune in to navigate the rapidly evolving landscape of reasoning LLMs!

Join us for an insightful exploration into the cutting-edge design of today's Large Language Models. Seven years on from the original GPT architecture, have we truly seen groundbreaking changes, or are we simply refining existing foundations? This podcast focuses on the architectural developments that define flagship open models in 2025, moving beyond benchmark performance or training algorithms.

In this episode, we'll unpack the key ingredients contributing to LLM performance, examining how developers are pushing the boundaries of efficiency, memory management, and training stability. Discover the evolution and intricacies of:

• Attention Mechanisms: From Multi-Head Attention (MHA) to the more efficient Grouped-Query Attention (GQA), and innovative approaches like Multi-Head Latent Attention (MLA) used in DeepSeek-V3, which compresses key and value tensors for memory savings. We also delve into Sliding Window Attention from Gemma 3, which restricts context size for local efficiency.
• Normalization Layers: Explore the shift from LayerNorm to RMSNorm and the crucial placement of these layers (Pre-Norm, Post-Norm) as seen in OLMo 2 and Gemma 3, including the addition of QK-Norm for enhanced training stability.
• Mixture-of-Experts (MoE): Understand why this approach has seen a significant resurgence in 2025. Learn how MoE, as implemented in models like DeepSeek-V3, Llama 4, and Qwen3's sparse variants, allows for massive total parameter counts (e.g., DeepSeek-V3's 671 billion parameters) while activating only a small subset (e.g., 37 billion) per inference step for remarkable efficiency.
• Positional Embeddings: Discover how positional information is handled, from rotational positional embeddings (RoPE) to the radical concept of No Positional Embeddings (NoPE) in SmolLM3, which aims for better length generalization.

We'll compare the structural nuances of leading models such as:

• DeepSeek-V3: A massive 671-billion-parameter model known for MLA and MoE with a shared expert.
• OLMo 2: Notable for its transparency and specific RMSNorm placements for training stability.
• Gemma 3 & 3n: Featuring sliding window attention for KV cache memory savings and unique normalization layer placements; Gemma 3n also introduces Per-Layer Embedding and MatFormer concepts.
• Mistral Small 3.1: Prioritizing lower inference latency through custom tokenizers and specific architectural choices.
• Llama 4: Adopting an MoE approach similar to DeepSeek-V3 but with its own distinct expert configuration.
• Qwen3: Available in both dense and MoE variants, offering flexibility for various use cases and moving away from shared experts in some MoE configurations.
• SmolLM3: A compact 3-billion-parameter model exploring the effectiveness of NoPE.
• Kimi K2: An impressive 1 trillion parameter model, building on the DeepSeek-V3 architecture with more experts and fewer MLA heads, setting new standards for open-weight performance.

Tune in to understand the intricate design decisions driving the next generation of large language models.

Are you ready for the exponential pace of change driven by Artificial Intelligence? This podcast delves into the critical insights from the 'AI & Enterprise Architecture: Maximizing Business Benefits 2025' report, exploring how AI is reshaping the modern business environment.

We discuss how AI is not merely enabling incremental improvements, but rather pushing the boundaries of what companies can do by enabling exponential change in processes, outcomes, and even entire business models. You'll discover how AI is moving beyond optimizing human productivity to automating entire systems and tasks that previously required manual intervention, with the capacity for continuous self-improvement without human involvement.

Learn about the profound impact AI will have on your organization and workforce, where some existing roles will become redundant and new ones will become essential. The future workforce will increasingly focus on creative, strategic, and design endeavors that cannot be easily automated, as operational and even development tasks become largely automated by AI. We highlight the significant first-mover advantage for companies that adopt AI early, as they can achieve scalability and efficiency at speeds competitors cannot match, potentially redefining their industries.

The episode emphasizes why strategic planning and solution design will become your number one differentiators and competitive factors for company success. Enterprise Architecture (EA), traditionally focused on IT blueprints, is now key in facilitating and orchestrating business transformation, defining the future of organizations. We'll explore how EA plays a major role in both strategic planning—identifying and prioritizing innovation projects—and solution design—articulating and guiding AI in building necessary improvements, recognizing that the quality of AI-generated programs depends on the quality of their designs. EA is positioned to be at the heart of this new ecosystem, enabling "super agile" sprints in hours with prompt-based AI programming.

Finally, we offer practical steps and recommendations for how organizations can prepare for these big changes ahead. This includes:

• Aiming for a "just-enough" understanding of the current state and shifting focus to business transformation rather than just application portfolio management or cost-cutting.
• Lowering the barriers to access and democratizing EA, empowering non-architects and enabling solution design and strategy teams to leverage EA principles.
• Becoming an orchestrating function for business transformation by getting involved in strategy, prioritizing projects, and crafting future-state business models.

Tune in to understand how adapting your Enterprise Architecture now is essential to remain competitive and thrive in an AI-powered future, as those who wait may struggle to keep pace with the inevitable shifts.

Are organizations truly prepared for the demands of constant change, rapid AI adoption, and escalating energy costs? Drawing insights from a survey of over 500 enterprise architecture professionals, this podcast dives deep into the 2025 State of Enterprise Architecture to reveal how leading organizations are driving success.

What you'll discover:

• Master Business Transformation: Learn how Enterprise Architecture (EA) helps align capabilities with strategy, despite common challenges in driving change. We'll explore why only 20% of organizations fully agree their EA deliverables support transformation, and what leaders do differently.
• Strategic Investment & Prioritization: Understand how EA leaders prioritize projects that contribute most to strategic goals, ensuring limited funds deliver the best return. Discover the biggest barriers to executing strategy, including budgets, culture, and leadership.
• Embrace IT Sustainability: Explore the role of EA in integrating sustainability metrics and understanding the environmental impact of IT assets, a growing priority for leaders.
• Gain Unprecedented Visibility: See how EA leaders achieve superior visibility into people, processes, information, technology, and transformation projects, enabling quicker adaptation and competitive advantage.
• Optimize EA Functions: Get insights into EA maturity, the importance of tool integration with systems like IT service management tools and CMDBs, and how centralized EA data can enhance accuracy and collaboration.
• Boost Leadership Engagement: Learn why EA teams often feel misunderstood and how leaders are increasing engagement with C-level executives and board members to communicate EA's strategic value.

Whether you're an Enterprise Architect, CIO, CTO, Business Architect, Solution Architect, or a leader focused on strategic planning and digital transformation, this podcast provides actionable insights to gain the Enterprise Architecture Advantage. Tune in to understand your starting point, define your destination, and navigate your journey through continuous change.

Dive deep into the world of Enterprise Resource Planning (ERP) software, a technology that has become indispensable for businesses in today's competitive landscape. This podcast, inspired by the latest ERP Software Statistics, explores how ERP simplifies complex operations and supports data-driven decision-making by integrating functions such as finance, HR, and inventory management into a single platform.

Join us as we uncover key insights and trends shaping the global ERP market:

• Market Momentum: Discover how the global ERP software market is steadily growing, fueled by the demand for digitization, automation, and scalability. Projections show the market reaching $70 billion in 2025 and an impressive $136 billion by 2032, growing at a CAGR of 10.5% from 2022-2032.
• Widespread Adoption: Learn why ERP is no longer just for large enterprises. More than 80% of small and medium-sized enterprises (SMEs) with annual revenue under $50 million rely on ERP systems. Manufacturing companies (21%), banking/financial services/insurance firms (16%), and telecoms (13%) particularly favor ERP software.
• Benefits and ROI: Understand the tangible advantages. 67% of organizations describe their ERP implementation as "very successful" or "successful". A significant 80% of organizations achieve a return on investment (ROI) from their ERP implementation, typically within an average of 2.5 years. ERP solutions help organizations achieve goals like operational efficiency (96.6%) and lead to significant improvements in business processes for 50% of organizations.
• Features and Customization: Explore what buyers prioritize. 89% of buyers consider accounting the primary feature they seek, with interest also in inventory and distribution (67%) and CRM (33%). You'll also learn that while only 3% of companies rely on out-of-the-box functionality, a vast majority opt for customization, with 33% to 48% requesting moderate levels.
• Deployment Trends: Get clarity on deployment options. 53.1% of companies have embraced cloud-based ERP solutions, with the majority (76.5%) preferring hosted ERP solutions within cloud deployment. For SMBs, convenience (29%) and adaptability (27%) are key reasons for choosing cloud-based systems.
• Challenges and Success Factors: Confront the realities of implementation. While technical aspects are least challenging (8%), managing organizational change is the most formidable hurdle (33.3%). We'll discuss barriers like resistance to change (82%) and ineffective project management (54%).
• The Future of ERP: Look ahead at the exciting trends. AI, machine learning, IoT, and cloud-based ERP solutions are gaining significant traction. 65% of Chief Information Officers (CIOs) foresaw AI integration into ERP by 2022. Recent developments include Microsoft acquiring Suplari to enhance Dynamics 365, SAP acquiring Signavio to strengthen its ERP suite, and new product launches like Oracle Fusion Cloud ERP and Infor CloudSuite 2024 with enhanced AI capabilities.

Whether you're a business leader considering ERP, an IT professional involved in implementation, or simply curious about the backbone of modern enterprise operations, this podcast offers essential insights and data-driven perspectives from the latest statistics.

Unlock the power of TOGAF Business Architecture! This podcast draws on expert insights to guide you through defining an organization's 'what' – its business strategy, governance, organization, and key processes. Discover essential techniques like Business Capability Mapping, Value Stream Mapping, Information Mapping, and Organization Mapping. Learn how Business Architecture (Phase B of the ADM) helps identify gaps between current and target states, ensuring IT investments align with business goals and strategy. Get ready to gain a comprehensive understanding of how to build robust, aligned enterprises.

Join us as we explore the SAP Integrated Toolchain, a powerful ecosystem designed for Enterprise Architects and transformation stakeholders. This podcast delves into how key solutions like SAP Signavio for process excellence, SAP LeanIX for application portfolio clarity, SAP WalkMe for enhanced user adoption, and SAP Cloud ALM for implementation governance, unite to support your organization's digital transformation. Discover how their seamless integration provides unprecedented visibility across traditionally siloed domains, enabling you to tackle challenges like business-IT alignment gaps, application portfolio complexity, and user adoption issues in SAP environments. Learn how this connected approach equips you with the capabilities needed to drive successful SAP implementations and optimize technology landscapes.

Get ready to test your knowledge! In this episode, we walk through 40 multiple-choice questions from the TOGAF 10 Foundation exam. Each question is followed by a clear answer and explanation, helping you learn core TOGAF concepts like the ADM cycle, stakeholder management, gap analysis, and architecture governance.

Get ready to test your knowledge! In this episode, we walk through 40 multiple-choice questions from the TOGAF 10 Foundation exam. Each question is followed by a clear answer and explanation, helping you learn core TOGAF concepts like the ADM cycle, stakeholder management, gap analysis, and architecture governance.

Get ready to test your knowledge! In this episode, we walk through 40 multiple-choice questions from the TOGAF 10 Foundation exam. Each question is followed by a clear answer and explanation, helping you learn core TOGAF concepts like the ADM cycle, stakeholder management, gap analysis, and architecture governance. This is your audio study guide for acing the Part 1 exam.

In this kickoff episode of our TOGAF 10 Certification Prep Series, we break down what TOGAF 10 is, why it matters in today’s enterprise architecture landscape, and how you can approach the framework with confidence. Whether you're a beginner or brushing up for certification, you'll learn the structure of the ADM (Architecture Development Method), key updates in TOGAF 10, and what roles architects play in modern organizations. Start here to build your foundation.

Unlock the power of LLM-powered systems with our practical guide to building intelligent agents. This podcast delves into the foundations of agent design, exploring what exactly an agent is – a system that independently accomplishes tasks on your behalf. We examine when building an agent is the right choice, focusing on workflows with complex decision-making, difficult-to-maintain rules, and heavy reliance on unstructured data.

Discover the core components of an agent: the Large Language Model (LLM) for reasoning and decision-making, the various tools for interacting with external systems, and the crucial instructions and guardrails that define agent behaviour. We explore strategies for selecting the right models and defining effective tools. Learn best practices for configuring clear and concise instructions to ensure smooth workflow execution.

We also guide you through different orchestration patterns, from single-agent systems to more complex multi-agent systems, including the manager pattern and the decentralized pattern. Understand the importance of an incremental approach to building agents. Finally, we discuss the critical role of guardrails in ensuring your agents operate safely and predictably by addressing data privacy and reputational risks. We cover various types of guardrails, including relevance classifiers, safety classifiers, PII filters, and rules-based protections. We also highlight the importance of planning for human intervention as a crucial safeguard.

Whether you're part of a product or engineering team exploring the world of autonomous systems, this podcast provides the foundational knowledge and actionable best practices to confidently start building your first agent.

This comprehensive guide, "Gemini for Google Workspace Prompting 101," provides users with practical instructions and examples for crafting effective prompts to leverage Gemini's AI capabilities within their familiar Google Workspace applications. It underscores how Gemini can enhance productivity and creativity across various tasks, from writing and organising to communication and planning. The document outlines key elements of successful prompting, such as persona, task, context, and format, and offers role-specific scenarios and tips to help individuals across different professional functions integrate AI into their workflows. Emphasising iterative refinement and user review, the guide aims to empower everyone to collaborate more effectively with AI while maintaining data privacy and security within the Workspace environment.

This podcast provides a comprehensive guide for Chief Technology Officers (CTOs) on how to define a clear and effective digital transformation strategy. It delves into popular frameworks such as OKRs, Lean Methodology, ESAD, TIME, and 4DX, offering practical steps, real-world examples from companies like Slack, Shopify, GE, Netflix, Salesforce, and Dell, and supporting statistics. The article outlines a six-step approach for CTOs to set a vision, eliminate waste, optimise core systems, automate and innovate, execute with precision, and iterate for continuous improvement. It emphasises the mission-critical nature of a clear strategy for CTOs to drive value and keep their companies competitive in the face of accelerating digital change.

Ever been in a meeting to set a launch date, only to hear, “The warehouse is a mess!”? You’re not alone—studies show up to 50% of meeting time gets lost to off-topic detours, even the “urgent” ones. In this episode, we dive into how to keep your meetings focused, productive, and laser-locked on their goals—no matter what else is burning. From setting a single, clear purpose to silencing unrelated project noise, we’ll unpack proven strategies from Harvard research, industry leaders, and real-world wins. Expect practical tips—like the 25-minute agenda trick and the “parking lot” fix—plus stories from the trenches. Whether you’re leading a team or just tired of wasted time, this is your guide to meetings that actually deliver. Tune in and take back your calendar!

This podcast delves into the history and evolution of industry standards in the realm of business operations, highlighting the significant contributions of the American Productivity & Quality Center (APQC). It explores the genesis of these standards, which emerged to address inefficiencies caused by highly customised processes and the lack of interoperability. A key focus is on APQC's Process Classification Framework (PCF) and its role in standardising definitions, facilitating benchmarking, and enhancing communication. The article further examines the impact of these standards on the implementation of early Enterprise Resource Planning (ERP) systems and their continued relevance in the context of cloud computing and artificial intelligence (AI) transformations, emphasising their necessity for interoperability, scalability, and cost efficiency. Quotes from industry leaders like Jack Grayson and EJ Tromp underscore the importance of standardisation. Ultimately, the article concludes that industry standards, exemplified by APQC's work, have been instrumental in driving efficiency, interoperability, and innovation in business practices.

CIOs and tech leaders are at the forefront of digital transformation, facing challenges in ERP modernization, AI adoption, and business process automation. Based on the latest SAPinsider Benchmark Report, this episode explores how CIOs are driving SAP S/4HANA migrations, overcoming skill shortages, and balancing IT innovation with business impact. Tune in for data-driven insights, real-world examples, and strategies to future-proof enterprise technology.

Explore the limitations of Large Language Models (LLMs) and Transformer architectures, from hallucinations and function composition challenges to ethical concerns and computational demands. Learn about cutting-edge solutions like Feedback Transformers and GPT-plugins, and discover how AI is shaping industries like medicine, finance, and engineering. Tailored for Enterprise Architects, this deep dive balances technical insights with real-world business impact.