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Anthropic's skill standard packages include instructions, scripts, and resources as folder-based Markdown modules for progressive disclosure and dynamic loading by agents. OpenAI's integration of skills into ChatGPT and Codex signals fast cross-platform standardization and a shift toward composable agent capabilities. Benefits include lower token costs, easier sharing and customization, deterministic code execution for reliability, and portable institutional knowledge.
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In this episode, Benjamin Brial, CEO and co-founder of Cycloid, speaks with host Sriram Panyam about internal developer platforms (IDPs) and internal developer portals. The conversation explores how these platforms address the growing challenges of DevOps scalability, multi-cloud complexity, and cloud waste, all of which organizations face as they grow.
Benjamin begins by framing the core problems that IDPs solve: DevOps struggling to scale beyond small teams, the complexity of managing hybrid environments across on-premises, public cloud, and private cloud infrastructure, and the significant issue of cloud waste (averaging 35-45% according to major analysts). IDPs can serve as a bridge between DevOps teams and developers, providing access to tools, cloud resources, and automation for users who aren't DevOps or cloud experts. The technical discussion covers essential IDP components including service catalogs, versioning engines, platform orchestration, asset inventory, and FinOps/GreenOps modules. The episode concludes with Benjamin's practical advice: organizations should focus on understanding their specific pain points rather than following market trends, starting with simple use cases such as landing zones before building complex solutions, and adopt a GitOps-first approach as the foundation for any IDP implementation.
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In this on-demand Live! 360 session, you’ll learn what it really means to be a data architect—far beyond just picking databases or tuning queries. Buck Woody walks through the mindset, frameworks, diagrams, and communication skills you need to design data systems that actually match how your business works.
You’ll see how to translate fuzzy business requests into clear requirements and constraints, use architecture frameworks (like TOGAF, NIST, and the Microsoft Data Architecture Guide) as guardrails, and design data pipelines that cover storage, compute, movement, security, and business continuity. Along the way, Buck shows how visual tools (BPMN, ER diagrams, UML, architecture diagrams) help you align executives, developers, and ops on the same picture.
Whether you’re a DBA, developer, or analytics engineer looking to level up, this session gives you a practical roadmap for growing into a data architect role.
🔑 What You’ll Learn
• How a data architect thinks about requirements, constraints, and business continuity
• Why defining business terms (like “inventory”) is critical before designing systems
• How to work with executives using T-charts (requirements vs. constraints) and clear recap docs
• The differences between IT, software, enterprise, cloud, solution, and data architects
• How to use architecture frameworks (ISO/NIST, TOGAF, Microsoft frameworks, Azure Well-Architected) as guides
• Visual “symbolics” every architect should know: ER diagrams, BPMN, UML, network and architecture diagrams
• How to design around storage, compute, and data pipelines (comes-out-of → goes-into → goes-out-of)
• Ways to reason about streaming vs. batch, and how to think in terms of data movement
• A simple three-step improvement loop: codify → standardize → optimize
• Practical career advice for aspiring data architects (from DBA or non-data backgrounds), including using LLMs to build a self-study syllabus
⏱️ Chapters
00:00 Becoming a data architect: role, definition & business continuity
01:39 Core capabilities: requirements, communication & understanding the business
06:53 Constraints, T-charts & working with executives
09:16 Certifications, self-learning & motivation
10:04 Types of architects: IT, software, enterprise, cloud, solution & data
11:24 IT architects, frameworks & why frameworks matter
12:32 Architecture frameworks tour: ISO/NIST, MOF, TOGAF & more
17:31 Using LLMs to build your own data-architect learning plan
20:10 Symbolics & tools: ER diagrams, BPMN, UML & architecture views
25:59 House-building analogy: why architects start with pictures
29:23 Data architecture focus: storage, compute & data pipelines
33:40 Azure Architecture Center, Well-Architected & the Data Architecture Guide (DAG)
38:31 Thinking in pipelines: comes-out-of / goes-into / goes-out-of & security passes
42:24 How to grow into a data architect from DBA or other roles
🔗 Links
• Data Architecture Guide: aka.ms/DAG
• Explore more Live! 360 sessions: https://aka.ms/L360Orlando25
• Check out upcoming VS Live! events: https://aka.ms/VSLiveEvents
👤 Speaker: Buck Woody
Chief Data Officer, Straight Path Solutions
#dataarchitecture #dataarchitect #sqlserver #azuremachinelearning