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Community Posts

What level of visibility into the business is needed for you to make quick strategy changes for the IT department? Do you feel like you currently have enough data and insights to pivot quickly?

Which tech conference do you intend to attend in person next year or have already participated in this year, and what motivated your choice?

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Is anyone working on automation of EA Practice activities such as design and/or roadmap development through the use of AI tools? This could include but not be limited to strategy, analysis, solution development, governance submissions, standards review, white papers etc. We are using ARIS as an EA repository and are considering the use of the AI companion or perhaps even standalone AI tools to import, process, analyses & publish. Happy to discuss ideas for future implementation.

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How do you think AI will disrupt business across industries? Add to my list: 1. Content creation 2. Photos and video production 3. Basic coding and debugging 4. Strategic analysis to be highly complimented

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Why do you think there are so few mature AI-driven autonomous pentesting solutions on the market, and why does this topic seem to generate more hype than in-depth technical discussion?

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We are in a world obsessed with the latest technologies, where it seems everything even working should be updated or upgraded to avoid the "imposed" in my opinion "digital obsolescence myth". How inclined are you towards innovation and change when the existing systems are certainly working effectively?

Very inclined: I believe in constantly pushing for innovation and improvement, even if the current systems are effective46%

Moderately inclined: I'm open to innovation and change, but only if it clearly enhances or adds value to the existing systems47%

Not inclined: If the current systems are working effectively, I prefer to maintain stability and avoid unnecessary changes5%

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Whilst there are high-quality, paid-for enterprise architecture applications in the market, with the increasing move to SaaS and dangers of vendor lock-in, it's prudent to have an alternative. Does anyone have experiences (good or bad) to share after moving from one of the market leaders to open source alternatives Essentials and/or Archi?

https://enterprise-architecture.org/products/essential-open-source/
https://www.archimatetool.com/

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Our organization is subject to data retention requirements over very long periods (50 years or more). Do your organizations face similar constraints? If so, what long-term retention strategy have you implemented for these regulated data, and what technologies or solutions do you use to ensure their durability and compliance?

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What are your thoughts on the balance between technological advancements and traditional methods?

Traditional methods can sometimes be just as effective as cutting-edge innovations?34%

Technology can lead to a depreciation of fundamental skills?42%

Technological innovations often introduce unnecessary complexity, making processes less accessible and more expensive?40%

Stressed or overwhelmed by the pressure to constantly adapt to new technologies and methods?21%

Technological progress is driven by human needs and experiences rather than just what is technologically possible?7%

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Looking at adopting Blazor for small to mid-sized projects (primarily the Server-Side Interactive mode). Any thoughts on Blazor Server-Side in production - whether development experience, user experience, support, etc? Have you had to support a user base that has less-than-ideal network conditions?

Has anyone successfully negotiated with a big hyperscaler partner to introduce a term into the contract that establishes service prices as public price at time of contract execution and holds those prices flat for the entire contract term? We're trying to think of ways to mitigate potential future cost increases if public prices change (due to tariffs or other unknown conditions) and dilute the impact of negotiated discounts.

What's in your FinOps tool kit?

AWS Cost Explorer25%

Azure Cost Management44%

GCP Cost Tools16%

CloudHealth (VMware)5%

Cloudability (Apptio)3%

Other (Please share below!)5%

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We have a servicing organization within IT segmented by applications and has 3 different director teams supporting overall pieces which is creating confusion, misalignment and becoming harder to support one business area. Components considered within this org are: PEGA products (NCompass, G&A), Genesys Cloud, Google, Member Portal and Member Mobile. How should i look at proposing a new target state Org considering all these aspects/products? Any ideas?

Our organization is implementing an Internal Developer Platform (IDP) to enable self-service infrastructure provisioning, and we're evaluating Terraform Cloud workspace management strategies. We're debating between: - VCS-driven approach: Repository-based workspace management with GitOps workflows - API-driven approach: Programmatic workspace creation and management via Terraform Cloud APIs Specific Questions: - Which approach have you found more effective for true self-service at scale? - How do these approaches handle multi-tenancy and isolation requirements? - What integration challenges did you encounter with developer portals/service catalogs? - How did your choice impact developer adoption and platform team operational overhead? Would love to hear about your real-world experiences, particularly around the trade-offs you discovered post-implementation.

What advice do you have for technology leaders that need help navigating the US administration's executive order to recalibrate the nation's AI strategy? Where do I begin?

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AI and Research in Marketing and Communications: How Are You Ensuring Quality and Truth Over Speed? As AI becomes embedded in our day-to-day marketing operations, from customer insight to content strategy, it’s clear we’re gaining speed and scale. But are we sacrificing veracity and quality of output in the process? One of the biggest challenges I'm seeing is the rise of hallucinated content in AI-generated research. - How do we ensure AI systems are surfacing trustworthy, contextually accurate, and well-sourced information? - Are we building enough verification layers into our AI-driven content and research workflows? - And how are you educating teams (and execs) to challenge AI outputs, rather than accept them at face value? - What frameworks, tools, or governance models have you adopted to maintain integrity and depth in AI-led research and insight creation? - Have you had success (or struggles) balancing speed vs. substance in AI-powered strategies? Your thoughts, examples, and recommendations would be incredibly valuable in helping others try to navigate this shift responsibly.