Douglas Chrystall

Hive CPQ is introducing a new term: "CPQ vibing" CPQ vibing, derived from the term 'code vibing', is a term for AI-assisted CPQ development where a CPQ model builder provides high-level, natural language instructions to an AI, and the AI generates the CPQ model. The model builder then interacts with the AI to refine and iterate on the code, often focusing on the overall goal rather than writing or debugging each line/rule/constraint themselves. Coined by Hive CPQ in early 2025, the practice represents a shift from traditional, line-by-line modelling to a more conversational and high-level workflow with an AI "model building buddy". 

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Agentforce leverages metadata - Flow, Apex, Prompt Templates. But the Agent is also metadata. And reuseability is an accelerator, so the dependencies get complex quickly. And we will see orgs with 100's or 1,000s of agents. Marc Benioff in the Bloomberg interview that he wants 1 BILLION Agents by end of 2025. https://lnkd.in/gGip_dC3 Luckily all the org, Data Cloud and Agentforce metadata and dependencies are in Elements.cloud metadata dictionary so that you can see the impact of changes to metadata on the different agents. And you can get started with the free tier called Agent Designer. As Vala Afshar, Salesforce Chief Digital Evangelist, said in a recent webinar, how are you going to manage all this without a tool like Elements? https://lnkd.in/gJ_hdJbW

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New release from Packt Publishing… “Building Business-Ready Generative #AI Systems — Build Human-Centered Generative AI Systems with Context-Aware Agents, Memory, and LLMs for the Enterprise” See it at https://amzn.to/3Jdcio5 𝓚𝓮𝔂 𝓕𝓮𝓪𝓽𝓾𝓻𝓮𝓼: 🔵Build an adaptive, context-aware AI controller with advanced memory strategies 🟢Enhance GenAISys with multi-domain, multimodal reasoning capabilities and Chain of Thought (CoT) 🟠Seamlessly integrate cutting-edge OpenAI and DeepSeek models as you see fit

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Why should Active Metadata Tags be the backbone of your AI strategy? Active Metadata Tags (AMTs) are used for automatic enrichment of metadata. Euno supports two types of custom metadata enrichment capabilities, both of which generate AMTs: #1 Extract structured metadata from unstructured metadata. This involved parsing metadata from elements like code and descriptions. A common application would be to enforce data modeling guardrails. Examples: → Implicit columns schema: Analyze dbt model code to determine whether the resulting schema includes implicit or explicit columns. → Verification checks: Assess naming conventions, detect use of approximate count distinct when querying large tables, evaluate documentation agility, flag full outer joins, and more. #2 Compose new AMTs. This approach combines metadata of a resource, and of any related resources, to set a new property on a resource. Examples: → Non-trivial custom SQL: Tag Tableau Custom SQL nodes that do not add logic. → Certified data source: Tag Tableau data sources as ‘certified’ if they don’t contain non-trivial custom SQL. → Certified dashboard: Tag Tableau dashboards as ‘certified’ if they only depend on certified data sources.   This capability is essential for governance workflows in large organizations where different teams maintain different parts of the stack. So team AI can build on something that team B created. Consider this scenario: → The team maintaining dbt can create a custom property to flag models for deprecation (e.g., models lacking both ‘prod’ and ‘prod_ready’ tags). → Analytics teams can then use this signal to create custom properties for their BI assets to drive workflows to migrate away from those models. Why does this also matter for AI agents? By implementing AMTs to surface trust signals, AI agents can actually tell the difference between exploratory work and official definitions. Example: → Euno’s MCP server surfaces to AI agents only Tableau logic that meets your trust standard and is considered certified such as: ‘depends only on dbt models from the gold layer and was in use in the past 60 days.’ *** Expect to hear much more about Active Metadata Tags! They’re quickly becoming the key to scale AI beyond the sandbox in your organization. #ActiveMetadata

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Great testing & development starts with great sandboxes - Those are golden words from Emily Call, MBA on Salesforce development and I wholeheartedly agree and support that theory. In this video, Emily demonstrates how Rubrik sandbox seeding transforms this painful process with automated sandbox seeding that’s: ✅ Fast and repeatable ✅ GDPR & CCPA compliant (thanks to built-in data masking) ✅ Uses smart analysis to ensure ample storage If sandbox seeding is a pain point that you’ve been struggling with, I strongly recommend watching the full video and checking out Rubrix sandbox seeding solution. Request your demo - find the link in the comments. Original video from Emily here - https://lnkd.in/g9E6fmYE #salesforce #sandbox #sandboxseeding #Rubrik #ad

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Salesforce Research releases an interesting benchmark, CRMArena-Pro, that focuses on sales and service activities. This paper shows that all commercial LLMs have some major flaws when it comes to conducting standard sales and service tasks. Charles Araujo and I are quite interested in this new custom benchmark as it’s a step towards better measuring the true business performance of AI. https://lnkd.in/gDhtPygv

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Thrilled to see Seismic's AI-powered integration with Salesforce Agentforce featured in Salesforce's latest blog post. This collaboration exemplifies our commitment to empowering sellers with intelligent tools right within their workflow. It’s even more exciting to know that this is just the beginning – much more to come on the frontier of AI-powered enablement. Onward! https://lnkd.in/ga-pnmc4

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Modernizing in regulated environments requires more than speed; it requires control. Today, we announced Nintex K2 (5.9), strengthening customization, accessibility, and integration capabilities for organizations running complex, on-premises workflows. As data sovereignty and compliance demands grow, automation platforms must adapt to enterprise requirements, not the other way around. K2 (5.9) continues our commitment to secure, flexible, enterprise-grade orchestration. Read the full announcement: https://lnkd.in/gyuExeNA #Nintex #K2 #ProcessAutomation #AI

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Since Salesforce removed its CPQ solution, our amazing client DealHub.io has been all over the news as the "go-to CPQ solution"! From this wonderful The Enterprise World article: "DealHub is recognized as one of the most agile and scalable enterprise CPQ solutions, particularly for SaaS and service-based organizations. At its core, DealHub delivers best-in-class CPQ functionality that supports complex product configurations, pricing models, and guided selling flows. It expands naturally into adjacent revenue workflows such as contract management, billing, subscription management, and digital deal rooms." Full article in the comments.

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The Internet of Things (IoT) has revolutionized data practices for businesses, enabling enhanced data collection, analysis, and utilization. Organizations utilizing advanced CRM platforms such as #Salesforce and #Microsoft Dynamics 365 now leverage real-time #IoT data to enhance customer service. At OMI, our extensive experience in integrating and customizing Salesforce and Dynamics over the years has shown us the power of bridging operational technology with customer-centric platforms to drive significant value. Check out how IoT data is leveraged in Salesforce and Dynamics 365 for proactive service: (https://lnkd.in/e7tF-GhX)

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