A candid look at turning AI hype into production results, told through the lens of Prakhar Srivastava, our newest recruit on the Enterprise Architecture team at SnapLogic. Over the years, Prakhar has been a practitioner, a consultant, and a vendor, and shares perspectives from each of those roles. We map lessons from SOA and APIs to agentic AI, and show how governance, data fabric, and empathy drive real outcomes in complex, regulated environments, using Prakhar's experience in the airline industry as a guide.

• three lenses on enterprise architecture and value
• composable enterprise as an AI readiness strategy
• agents as APIs with memory and similar pitfalls
• need for gateways, meshes, and security guardrails
• four risks to manage: governance, interoperability, trust, security
• data as water and the role of a fabric
• crawl‑walk‑run roadmap from use case to production
• outsourcing lessons and knowledge repatriation
• retraining, drift, and resilient deployments
• empathy and partnering over hard selling

We explore how embedded AI in SaaS tools amplifies sprawl and risk, and outline a practical path to governed, composable, cross‑platform agents. Chris Ward shares real use cases for Customer 360 and finance reconciliation, plus metrics, onboarding and versioning that keep AI accountable.

The LinkedIn post that kicked everything off

More details on the finance use case Chris discussed

SnapLogic's own support for MCP

Composable architecture isn’t a buzzword; it’s the overdue upgrade to lessons we learned the hard way in the SOA era. We share a pragmatic path from heavyweight standards and ESB monocultures to API-first, domain-driven systems that actually deliver reuse, speed, and resilience across cloud and on-prem. With guest Brad Drysdale, we map the shift from monoliths to distributed services, the rise of REST and gateways, and why a discovery-led mindset matters more than any protocol.

We dig into the techniques that make composability real: treat API contracts as products in their own right, with owners, roadmaps, and strong versioning; build a living catalogue that developers can trust; and use domain-driven design to create bounded contexts that align services to business language. We talk openly about governance debt, API sprawl, and the trap of point-to-point integrations disguised as microservices. Then we connect the dots to modern DevOps — Kubernetes, Terraform, and infrastructure as code — showing how to run heterogeneous, multi-cloud estates without drowning in complexity.

Now AI raises the stakes. Agents need secure, reliable access to knowledge and tools; contracts machines can interpret; and guardrails that earn trust. We compare REST and OpenAPI to emerging agent-to-agent standards like MCP, and explain why the future likely builds on today’s contracts rather than replacing them. Finally, we explore vibe coding’s next act: vibe orchestration, mapping intent to capabilities letting AI assemble outcomes from a curated service catalogue. The takeaway is simple: composability scales when you fund shared capabilities, measure adoption, and make reuse the default.

If this sparked ideas for your stack or strategy, follow the show, share it with a colleague, and get in touch with your questions and suggestions. Your stories and challenges shape what we explore next.

Pressure to “do something with AI” is loud, but the stakes are higher when patient data, regulators, and legacy systems meet non‑deterministic models. We sat down with the hosts of the Enterprise Architecture Experience podcast — Hassan Abba from AstraZeneca and Jon Hill from Alvotech — to compare how a global R&D giant and a thousand‑person biopharma scale-up are making AI useful without trading away trust. The conversation gets practical fast: where AI speeds discovery, where it should never touch regulated data, and how to draw clean lines that everyone can work with.

Welcome to Season Three of the Enterprise Alchemists podcasts!

We start the season with a special guest: Gene Linetsky, CTO of Embroker.

Gene talks to Guy and Dominic about his need to integrate bettter with existing systems and processes to avoid wasting the time of over-qualified human users. AgentCreator from SnapLogic solved the technical problem, thanks to what Gene describes as "semantic ETL", but that leads to more philosophical questions.

Over the course of the episode, Gene describes how agentic flows are ultimately a management question: humans will still be a lot better positioned to organize the work, whether that is carried out by humans or by AI agents. The goal is to facilitate the work solving business problems with code, not just solving coding problems.

Can outdated systems silently threaten the very core of your business? This episode, Guy and Dominic welcome the expert insights of Simona Todoroska from IWConnect to discuss the pressing issues surrounding legacy system integration and migration. Simona sheds light on how the historical reluctance to engage with legacy systems has created significant challenges for modern enterprises. We dive into the critical need for businesses to reevaluate their existing technologies to ensure they are future-ready, scalable, and secure. The conversation also delves into the risks of neglecting modernization, emphasizing how catastrophic failures in outdated systems could lead to dire consequences.

The discussion dives into the complexities of migrating from legacy systems to modern integration platforms, highlighting the challenges enterprises face when clinging to outdated technologies. Through real-world examples and a discussion on the importance of automation and AI in the migration process, we present practical strategies for successful transformation.

• Exploring the tension around updating legacy systems
• Understanding the risks of relying on outdated technology
• Discussing the role of automation in migrations
• Demonstrating the significance of the analysis phase
• Introducing AI agents Pete and Alex for improving documentation
• Highlighting the NL2SQL functionality for user empowerment
• Emphasising the importance of upfront analysis for success

Pete: https://iwconnect.com/virtual-assistant-pete/

Alex: https://iwconnect.com/alex-virtual-storytelling-agent/

NL to SQL: https://iwconnect.com/natural-language-to-sql-generator/

Matthew Holloway, Head of Global Design at SnapLogic, joins Guy and Dominic to unravel the complexities of designing user-centered enterprise integration platforms. Matthew shares strategies for presenting complex data to diverse user expertise levels, and some of what he has learned from how SnapLogic's groundbreaking tools, Iris and SnapGPT, are redefining data pipeline creation.

In design as in tech, it turns out to be critical to pinpoint the right problems before rushing to “solutioneering.” With the buzz around generative AI and its often-misaligned expectations, the discussion sheds light on managing these through the design hypercycle. Matthew emphasizes fostering collaboration through rapid prototyping, involving key stakeholders to ensure solutions are not only creative but also viable and aligned with organizational objectives.

Here are some of the topics discussed in the episode:

• User-centric information architecture and its complexities
• The challenge of designing for varied expertise levels among users
• SnapLogic’s proactive design approach and its unique tools
• Insights on co-innovation and collaborative problem-solving
• The journey through the generative AI hype cycle
• Transition from prototypes to fully realised products
• Emphasis on personalisation and user agency in design decisions
• Understanding the importance of making critical information accessible
• The future of design through generative AI personalization

Resources that were mentioned:

• Generative UX: https://www.linkedin.com/pulse/generative-ux-matthew-holloway-2rvyc/
• Cognitive Architecture: https://www.linkedin.com/pulse/cognitive-architecture-matthew-holloway-zfple

Brian Green, software architect at SnapLogic, joins Dominic and Guy to explore the fascinating convergence of no-code, low-code, and traditional software development strategies. Discover why even the most user-friendly platforms require a solid grasp of software principles to truly excel, especially in large-scale operations. Brian sheds light on how traditional concepts like configuration management, environmental separation, and documentation are essential in optimizing no-code development environments. With a focus on the balance between ease-of-use and the rigor of traditional development practices, this episode promises to equip you with the insights needed to navigate the challenges of scaling in the digital age.

Join us as we uncover how traditional software techniques, such as linting, can revolutionize SnapLogic pipelines for enhanced robustness and efficiency. Learn about the seamless integration of these techniques with source control and how a center of excellence can bridge the gap between traditional and citizen developers. We delve into the potential of low-code/no-code platforms when the right levels of abstraction are understood. From generating test data with tools like SnapGPT to balancing standard engineering practices with unique platform benefits, this episode is packed with insights to elevate your enterprise strategies.