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Salesforce Flow Tests
25Oct

Salesforce Flow Tests

Deploying Salesforce Flow tests is not just about hitting “go” and hoping for the best. It requires more than simply moving automations from a Sandbox environment to production. Successful deployment demands thoughtful planning and attention to detail. In this post, we’ll dive deeper into deploying Flow tests effectively, covering key factors like independent testing and ensuring environment consistency. Building on our ongoing series, we’ll provide practical insights to help you achieve smooth deployments and reliable test execution. Key Considerations for Deploying Flow Tests Steps to Deploy Flow Tests Using Change Sets Final Thoughts Deploying Flow tests effectively is critical for maintaining the integrity of your automations across environments. Skipping the testing phase is like driving with a blindfold—one mistake could disrupt your workflows and cause chaos in critical processes. By following these guidelines, particularly focusing on independent testing and post-deployment checks, you can help ensure your Salesforce Flows continue to operate smoothly. Stay tuned for future insights for Flownatics where we’ll dive into more advanced aspects of Flow tests, helping you further optimize your Salesforce automation processes. Need more advice on testing your automations in Salesforce? Let’s chat! Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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October 25, 2024in Data
TrueDialog Adds SMS Application for Salesforce Marketing Cloud Engagement
25Oct

TrueDialog Adds SMS Application for Salesforce Marketing Cloud Engagement

TrueDialog Unveils SMS Integration for Salesforce Marketing Cloud

TrueDialog, a leader in SMS texting solutions, has expanded its Salesforce offerings with the launch of its SMS integration for Salesforce Marketing Cloud Engagement, complementing its existing Sales Cloud application. Now available on Salesforce AppExchange, this addition enables seamless documentation of SMS activities across the Salesforce Cloud ecosystem.

With TrueDialog’s integration for Salesforce Marketing Cloud, companies can incorporate SMS into customized, targeted marketing journeys. This includes sending promotional messages, geo-targeted offers, triggered alerts, order confirmations, account updates, and more—all as part of a cohesive customer engagement strategy.

TrueDialog’s solution uniquely enables SMS message flow across Salesforce Marketing Cloud, Sales Cloud, Service Cloud, and Education Cloud, ensuring communication continuity across platforms. “TrueDialog is the only provider offering bidirectional SMS integration between Salesforce Marketing Cloud and other Salesforce Clouds, including Sales, Service, Commerce, and Education Clouds,” said John Wright, CEO of TrueDialog. “Our solution records text messages on all relevant Salesforce Clouds, maintaining communication continuity between companies and their customers—something no other provider offers.”

The TrueDialog SMS application is fully native to Salesforce Marketing Cloud, allowing users to work within their regular workflow without switching applications to integrate SMS steps. TrueDialog also offers flexible options for short and long codes, automated 10DLC registration for long codes, and TrueDelivery, a tool for assessing SMS deliverability.

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October 25, 2024in Salesforce Marketing Cloud
Transform Customer Experience
25Oct

Transform Customer Experience

In today’s AI-driven business environment, customer experience (CX) has evolved from being a buzzword to a critical factor in determining success. It’s no longer enough for businesses to offer high-quality products or excellent service alone—today’s customers are always online, engaged, and seeking the most convenient, relevant, and enjoyable experiences. This is where Salesforce Data Cloud becomes a game-changer, providing the tools needed to meet modern customer expectations. Transforming Customer Experience with Salesforce Data Cloud Salesforce enables businesses to collect, integrate, and leverage critical customer information within its ecosystem, offering an all-encompassing view of each customer. This unified customer data allows organizations to forecast visitor trends, assess marketing impact, and predict customer behavior. As data-driven decision-making becomes increasingly central to business strategy, Salesforce Data Cloud and its Customer Data Platform (CDP) features provide a significant competitive edge—whether in e-commerce, fintech, or B2B industries. Data Cloud is more than just your traditional CDP. It’s the only data platform native to the world’s #1 AI CRM. This means that marketers can quickly access and easily action on unified data – from across the entire business – to drive growth and increase customer lifetime value. Data Cloud’s Role in Enhancing CX By unifying data in one place, Salesforce Data Cloud enables organizations to access real-time customer insights. This empowers them to track customer activity across channels like email, social media, and online sales, facilitating targeted marketing strategies. Businesses can analyze customer behavior and deliver personalized messaging, aligning marketing, sales, and customer service efforts to ensure consistency. With these capabilities, Salesforce customers can elevate the CX by delivering the right content, at the right time, to the right audience, ultimately driving customer satisfaction and growth. New Features of Salesforce Data Cloud Salesforce continues to evolve, introducing cutting-edge features that reshape customer interaction: To fully maximize these features, partnering with a Salesforce Data Cloud consultant can help businesses unlock the platform’s full potential and refine their customer engagement strategies. Agentic AI Set to Supercharge Business Processes Salesforce’s vision extends beyond customer relationship management with the integration of Agentic AI through its Customer 360 platform. According to theCUBE Research analysts, this signals a shift toward using AI agents to automate complex business processes. These AI agents, built on Salesforce’s vast data resources, promise to revolutionize how companies operate, offering customized, AI-driven business tools. “If they can pull this off, where it becomes a more dynamic app platform, more personalized, really focused on those processes all the way back to the data, it’s going to be a clear win for them,” said Strechay. “They’re sitting on cloud; they’re sitting on IaaS. That’s a huge win from that perspective.” AI agents create a network of microservices that think and act independently, involving human intervention only when necessary. This division of labor allows businesses to capture expertise in routine tasks while freeing human workers to focus on more complex decision-making. However, the success of these AI agents depends on access to accurate and reliable data. As Gilbert explained, “Agents can call on other agents, and when they’re not confident of a step in a process or an outcome, they can then bounce up to an inbox for a human to supervise.” The goal isn’t to eliminate humans but to capture their expertise for simpler processes. Empowering Developers and Citizen Creators At the core of this AI-driven transformation is Salesforce’s focus on developers. The platform’s low-code tools allow businesses to easily customize AI agents and automate business processes, empowering both experienced developers and citizen creators. With simple language commands or goal-setting, companies can build and train these AI agents, streamlining operations. “It’s always going to be about good data—that’s the constant,” Bertrand said. “The second challenge is how to train agents and humans to work together effectively. While some entry-level jobs may be replaced, AI will continue to evolve, creating new opportunities in the future.” Is Salesforce Data Cloud the Right Fit for Your Business? Salesforce Data Cloud offers comprehensive capabilities for businesses of all sizes, but it’s essential to assess whether it aligns with your specific needs. The platform is particularly valuable for: For businesses that fit these scenarios, working with Salesforce’s partner ecosystem or a Data Cloud consultant can help ensure successful integration and optimization. What’s New in Salesforce’s Latest Release? The latest Salesforce Spring Release introduced several exciting features, further enhancing Salesforce Data Cloud: These updates reflect Salesforce’s commitment to providing innovative, data-driven solutions that enhance customer experiences and drive business success. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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October 25, 2024in AI Tools, Data, Generative AI, Salesforce, Salesforce Data Cloud
What Should Enterprises Build with Agentic AI?
25Oct

What Should Enterprises Build with Agentic AI?

The rise of agentic AI has dominated recent discussions in enterprise technology, sparking debates over its transformative potential and practical applications. Just weeks ago, few had heard of the term. Now, every tech vendor is racing to stake their claim in this emerging space, positioning agentic AI as the successor to AI co-pilots. While co-pilots assist users with tasks, agentic AI represents the next step: delegating tasks to intelligent agents capable of independent execution, akin to assigning work to a junior colleague. But beyond the buzz, the pressing questions remain: Cutting Through the Hype Recent launches provide a snapshot of how enterprises are beginning to deploy agentic AI. Salesforce’s Agentforce, Asana’s AI Studio, and Atlassian’s Rovo AI Assistant all emphasize the ability of these agents to streamline workflows by interpreting unstructured data and automating complex tasks. These tools promise flexibility over previous rigid, rule-based systems. For example, instead of painstakingly scripting every step, users can instruct an agent to “follow documented policies, analyze data, and propose actions,” reserving human approval for final execution. However, the performance of these agents hinges on data quality and system robustness. Salesforce’s Marc Benioff, for instance, critiques Microsoft’s Copilot for lacking a robust data model, emphasizing Salesforce’s own structured approach as a competitive edge. Similarly, Asana and Atlassian highlight the structured work graphs underpinning their platforms as critical for accurate and reliable outputs. Key Challenges Despite the promise, there are significant challenges to deploying agentic AI effectively: Early Wins and Future Potential Early adopters are seeing value in high-volume, repetitive scenarios such as customer service. For example: However, these successes represent low-hanging fruit. The true promise lies in rethinking how enterprises work. As one panelist at Atlassian’s event noted: “We shouldn’t just use this AI to enhance existing processes. We should ask whether these are the processes we want for the future.” The Path Forward The transformative potential of agentic AI will depend on broader process standardization. Just as standardized shipping containers revolutionized logistics, and virtual containers transformed IT operations, similar breakthroughs in process design could unlock exponential gains for AI-driven workflows. For now, enterprises should: Conclusion Agentic AI holds immense potential, but its real power lies in enabling enterprises to question and redesign how work gets done. While it may still be in its early days, businesses that align their AI investments with strategic goals—and not just immediate fixes—will be best positioned to thrive in this new era of intelligent automation. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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October 25, 2024in Agentforce Platform, Data, Enterprise, Generative AI, Salesforce, Technology
Slack User Personas
25Oct

Slack User Personas

A research team at Slack recently surveyed 5,000 full-time desk workers to understand what drives their use of AI-enhanced workplace tools. They found that people typically fall into one of five distinct personas, as identified by Slack’s Workforce Lab: What’s fascinating about this approach is how it aligns with the concept of managing people through “employee personas.” If you’re unfamiliar, workforce platform Envoy defines employee personas as “semi-fictional characters that represent the behaviors, needs, and preferences of a group of employees,” based on data and interviews. These personas help organizations tailor communications, plan training, and develop career paths, offering a data-driven approach to workforce management. Slack has extended this framework to AI adoption strategies. As reported by HR Dive, Christina Janzer, Slack’s SVP of research and analytics, noted during a press call that AI adoption is complex, with individuals experiencing it differently. She suggested that understanding employees’ emotional responses to AI could help predict whether they’ll experiment with or avoid the technology. This research mirrors the approach of the Slack-backed Future Forum, which surveyed 10,000 global workers each quarter on topics like flexibility, burnout, and hybrid work. Slack’s Workforce Lab takes a similar approach but focuses on productivity and employee experience across desk workers globally, including those at Slack, Salesforce, and beyond. The release of this report on AI personas—complete with a quiz—continues this work by asking how management can foster effective AI adoption. It’s crucial to note that personas aren’t fixed; people’s attitudes and enthusiasm for AI can evolve with experience. If Slack’s findings reflect broader trends, only a third of employees are truly excited about AI, with the rest hesitant or disengaged. A future challenge for Slack Workforce Lab may be uncovering what can motivate the remaining personas to embrace AI. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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October 25, 2024in Salesforce Slack
AI Agent Workflows
24Oct

AI Agent Workflows

AI Agent Workflows: The Ultimate Guide to Choosing Between LangChain and LangGraph Explore two transformative libraries—LangChain and LangGraph—both created by the same developer, designed to build Agentic AI applications. This guide dives into their foundational components, differences in handling functionality, and how to choose the right tool for your use case. Language Models as the Bridge Modern language models have unlocked revolutionary ways to connect users with AI systems and enable AI-to-AI communication via natural language. Enterprises aiming to harness Agentic AI capabilities often face the pivotal question: “Which tools should we use?” For those eager to begin, this question can become a roadblock. Why LangChain and LangGraph? LangChain and LangGraph are among the leading frameworks for crafting Agentic AI applications. By understanding their core building blocks and approaches to functionality, you’ll gain clarity on how each aligns with your needs. Keep in mind that the rapid evolution of generative AI tools means today’s truths might shift tomorrow. Note: Initially, this guide intended to compare AutoGen, LangChain, and LangGraph. However, AutoGen’s upcoming 0.4 release introduces a foundational redesign. Stay tuned for insights post-launch! Understanding the Basics LangChain LangChain offers two primary methods: Key components include: LangGraph LangGraph is tailored for graph-based workflows, enabling flexibility in non-linear, conditional, or feedback-loop processes. It’s ideal for cases where LangChain’s predefined structure might not suffice. Key components include: Comparing Functionality Tool Calling Conversation History and Memory Retrieval-Augmented Generation (RAG) Parallelism and Error Handling When to Choose LangChain, LangGraph, or Both LangChain Only LangGraph Only Using LangChain + LangGraph Together Final Thoughts Whether you choose LangChain, LangGraph, or a combination, the decision depends on your project’s complexity and specific needs. By understanding their unique capabilities, you can confidently design robust Agentic AI workflows. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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October 24, 2024in Agentforce Platform, AI Tools, Artificial Intelligence, Data, Enterprise, Generative AI, Salesforce
AI Innovation at Salesforce
24Oct

AI Innovation at Salesforce

AI innovation is advancing at an unprecedented pace, unlike anything I’ve seen in nearly 25 years at Salesforce. It’s now a top priority for every CEO, CTO, and CIO I speak with. As a trusted partner, we help customers innovate, iterate, and navigate the evolving AI landscape. They recognize AI’s immense potential to revolutionize every aspect of business, across all industries. While they’re already seeing significant advancements, we are still just scratching the surface of AI’s full transformational promise. They seek AI technologies that will enhance productivity, augment employee performance at scale, improve customer relationships, and ultimately drive rapid time to value and higher margins. That’s where our new Agentforce Platform comes in. Agentforce represents a breakthrough in AI, delivering on the promise of autonomous AI agents. These agents perform advanced planning and decision-making with minimal human input, automating entire workflows, making real-time decisions, and adapting to new information—all without requiring human intervention. Salesforce customers are embracing Agentforce and integrating it with other products, including Einstein AI, Data Cloud, Sales Cloud, and Service Cloud. Here are some exciting ways our customers are utilizing these tools: Strengthening Customer Relationships with AI Agents OpenTable is leveraging autonomous AI agents to handle the massive scale of its operations, supporting 60,000 restaurants and millions of diners. By piloting Agentforce for Service, they’ve automated common tasks like account reactivations, reservation management, and loyalty point expiration. The AI agents even answer complex follow-up questions, such as “when do my points expire in Mexico?”—a real “wow” moment for OpenTable. These agents are redefining how customers engage with companies. Wiley, an educational publisher, faces a seasonal surge in service requests each school year. By piloting Agentforce Service Agent, they increased case resolution by 40-50% and sped up new agent onboarding by 50%, outperforming their previous systems. Harnessing Data Insights The Adecco Group, a global leader in talent solutions, wanted to unlock insights from its vast data reserves. Using Data Cloud, they’re connecting multiple Salesforce instances to give 27,000 recruiters and sales staff real-time, 360-degree views of their operations. This empowers Adecco to improve job fill rates and streamline operations for some of the world’s largest companies. Workday, a Salesforce customer for nearly two decades, uses Service Cloud to power customer service and Slack for internal collaboration. Our new partnership with Workday will integrate Agentforce with their platform, creating a seamless employee experience across Salesforce, Slack, and Workday. This includes AI-powered employee service agents accessible across all platforms. Wyndham Resorts is transforming its guest experience by using Data Cloud to harmonize CRM data across Sales Cloud, Marketing Cloud, and Service Cloud. By consolidating their systems, Wyndham anticipates a 30% reduction in call resolution time and an overall enhanced customer experience through better access to accurate guest and property data. Empowering Employees Air India, with ambitions to capture 30% of India’s airline market, is using Data Cloud, Service Cloud, and Einstein AI to unify data across merged airlines and enhance customer service. Now, human agents spend more time with customers while AI handles routine tasks, resulting in faster resolution of 550,000 monthly service calls. Heathrow Airport is focused on improving employee efficiency and personalizing passenger experiences. Service Cloud and Einstein chatbots have significantly reduced call volumes, with chatbots answering 4,000 questions monthly. Since launching, live chat usage has surged 450%, and average call times have dropped 27%. These improvements have boosted Heathrow’s digital revenue by 30% since 2019. Driving Productivity and Margins Aston Martin sought to improve customer understanding and dealer collaboration. By adopting Data Cloud, they unified their customer data, reducing redundancy by 52% and transitioning from six data systems to one, streamlining operations. Autodesk, a leader in 3D design and engineering software, uses Einstein for Service to generate AI-driven case summaries, cutting the time spent summarizing customer chats by 63%. They also use Salesforce to enhance data security, reducing ongoing maintenance by 30%. Creating a Bright Future for Our Customers For over 25 years, Salesforce has guided customers through transformative technological shifts. The fusion of AI and human intelligence is the most profound shift we’ve seen, unlocking limitless potential for business success. Join them at Dreamforce next month, where we’ll celebrate customer achievements and share the latest innovations. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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October 24, 2024in Agentforce Platform
$15 Million to AI Training for U.S. Government Workforce
24Oct

$15 Million to AI Training for U.S. Government Workforce

Google.org Commits $15 Million to AI Training for U.S. Government Workforce Google.org has announced $15 million in grants to support the development of AI skills in the U.S. government workforce, aiming to promote responsible AI use across federal, state, and local levels. These grants, part of Google.org’s broader $75 million AI Opportunity Fund, include $10 million to the Partnership for Public Service and $5 million to InnovateUS. The $10 million grant to the Partnership for Public Service will fund the establishment of the Center for Federal AI, a new hub focused on building AI expertise within the federal government. Set to open in spring 2025, the center will provide a federal AI leadership program, internships, and other initiatives designed to cultivate AI talent in the public sector. InnovateUS will use the $5 million grant to expand AI education for state and local government employees, aiming to train 100,000 workers through specialized courses, workshops, and coaching sessions. “AI is today’s electricity—a transformative technology fundamental to the public sector and society,” said Max Stier, president and CEO of the Partnership for Public Service. “Google.org’s generous support allows us to expand our programming and launch the new Center for Federal AI, empowering agencies to harness AI to better serve the public.” These grants clearly underscore Google.org’s commitment to equipping government agencies with the tools and talent necessary to navigate the evolving AI landscape responsibly. With these tools in place, Tectonic looks forward to assist you in becoming an ai-driven public sector service. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

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October 24, 2024in Google, Technology
Rise of Agentforce
24Oct

Rise of Agentforce

The Rise of Agentforce: How AI Agents Are Shaping the Future of Work Salesforce wrapped up its annual Dreamforce conference this September, leaving attendees with more than just memories of John Mulaney’s quips. As the swarms of Waymos ferried participants across a cleaner-than-usual San Francisco, it became clear that AI-powered agents—dubbed Agentforce—are poised to transform the workplace. These agents, controlled within Salesforce’s ecosystem, could significantly change how work is done and how customer experiences are delivered. Dreamforce has always been known for its bold predictions about the future, but this year’s vision of AI-based agents felt particularly compelling. These agents represent the next frontier in workplace automation, but as exciting as this future is, some important questions remain. Reality Check on the Agentforce Vision During his keynote, Salesforce CEO Marc Benioff raised an interesting point: “Why would our agents be so low-hallucinogenic?” While the agents have access to vast amounts of data, workflows, and services, they currently function best within Salesforce’s own environment. Benioff even made the claim that Salesforce pioneered prompt engineering—a statement that, for some, might have evoked a scene from Austin Powers, with Dr. Evil humorously taking credit for inventing the question mark. But can Salesforce fully realize its vision for Agentforce? If they succeed, it could be transformative for how work gets done. However, as with many AI-driven innovations, the real question lies in interoperability. The Open vs. Closed Debate As powerful as Salesforce’s ecosystem is, not all business data and workflows live within it. If the future of work involves a network of AI agents working together, how far can a closed ecosystem like Salesforce’s really go? Apple, Microsoft, Amazon, and other tech giants also have their sights set on AI-driven agents, and the race is on to own this massive opportunity. As we’ve seen in previous waves of technology, this raises familiar debates about open versus closed systems. Without a standard for agents to work together across platforms, businesses could find themselves limited. Closed ecosystems may help solve some problems, but to unlock the full potential of AI agents, they must be able to operate seamlessly across different platforms and boundaries. Looking to the Open Web for Inspiration The solution may lie in the same principles that guide the open web. Just as mobile apps often require a web view to enable an array of outcomes, the same might be necessary in the multi-agent landscape. Tools like Slack’s Block Kit framework allow for simple agent interactions, but they aren’t enough for more complex use cases. Take Clockwise Prism, for example—a sophisticated scheduling agent designed to find meeting times when there’s no obvious availability. When integrated with other agents to secure that critical meeting, businesses will need a flexible interface to explore multiple scheduling options. A web view for agents could be the key. The Need for an Open Multi-Agent Standard Benioff repeatedly stressed that businesses don’t want “DIY agents.” Enterprises seek controlled, repeatable workflows that deliver consistent value—but they also don’t want to be siloed. This is why the future requires an open standard for agents to collaborate across ecosystems and platforms. Imagine initiating a set of work agents from within an Atlassian Jira ticket that’s connected to a Salesforce customer case—or vice versa. For agents to seamlessly interact regardless of the system they originate from, a standard is needed. This would allow businesses to deploy agents in a way that’s consistent, integrated, and scalable. User Experience and Human-in-the-Loop: Crucial Elements for AI Agents A significant insight from the integration of LangChain with Assistant-UI highlighted a crucial factor: user experience (UX). Whether it’s streaming, generative interfaces, or human-in-the-loop functionality, the UX of AI agents is critical. While agents need to respond quickly and efficiently, businesses must have the ability to involve humans in decision-making when necessary. This principle of human-in-the-loop is key to the agent’s scheduling process. While automation is the goal, involving the user at crucial points—such as confirming scheduling options—ensures that the agent remains reliable and adaptable. Any future standard must prioritize this capability, allowing for user involvement where necessary, while also enabling full automation when confidence levels are high. Generative or Native UI? The discussion about user interfaces for agents often leads to a debate between generative UI and native UI. The latter may be the better approach. A native UI, controlled by the responding service or agent, ensures the interface is tailored to the context and specifics of the agent’s task. Whether this UI is rendered using AI or not is an implementation detail that can vary depending on the service. What matters is that the UI feels native to the agent’s task, making the user experience seamless and intuitive. What’s Next? The Push for an Open Multi-Agent Future As we look ahead to the multi-agent future, the need for an open standard is more pressing than ever. At Clockwise, we’ve drafted something we’re calling the Open Multi-Agent Protocol (OMAP), which we hope will foster collaboration and innovation in this space. The future of work is rapidly approaching, where new roles—like Agent Orchestrators—will emerge, enabling people to leverage AI agents in unprecedented ways. While Salesforce’s vision for Agentforce is ambitious, the key to unlocking its full potential lies in creating a standard that allows agents to work together, across platforms, and beyond the boundaries of closed ecosystems. With the right approach, we can create a future where AI agents transform work in ways we’re only beginning to imagine. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial

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October 24, 2024in Data, Enterprise, Salesforce, Technology
Salesforce Says AI Should Be a Partner
24Oct

Salesforce Says AI Should Be a Partner

Salesforce Says AI Should Be a Partner, Not Just a Tool As AI continues to evolve rapidly, Salesforce’s chief ethical and humane use officer, Paula Goldman, urged businesses to rethink how they integrate AI in the workplace. According to Goldman, we are at a pivotal moment where AI should be seen as a partner rather than merely a tool. Goldman emphasized the concept of agentic AI, which refers to AI systems that can act independently to achieve goals or make decisions on behalf of the company. However, with this autonomy comes the need for proper safeguards to prevent issues like bias and misinformation, especially considering AI’s tendency to generate “hallucinations” or inaccurate outputs. One powerful example Goldman provided was during a company board meeting where AI identified bias in real-time. The AI flagged a pattern that participants either didn’t notice or were hesitant to address, leading to richer discussions and better decision-making. She also cited a healthcare scenario where a nurse used AI during patient intake. The AI collected information through questions and answers, freeing up the nurse to focus on the patient’s body language and emotional cues, enhancing the human element of care. Goldman concluded by saying that the future of AI depends on how businesses choose to leverage it. “To make AI work for our businesses, we have to make sure it works for the people our businesses serve and the people our businesses employ,” she said. In short, AI should act as a collaborative partner, enhancing human judgment and decision-making while staying within ethical boundaries. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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October 24, 2024in Agentforce Platform
Scope of Generative AI
24Oct

Scope of Generative AI

Generative AI has far more to offer your site than simply mimicking a conversational ChatGPT-like experience or providing features like generating cover letters on resume sites. Let’s explore how you can integrate Generative AI with your product in diverse and innovative ways! There are three key perspectives to consider when integrating Generative AI with your features: system scope, spatial relationship, and functional relationship. Each perspective offers a different lens for exploring integration pathways and can spark valuable conversations about melding AI with your product ecosystem. These categories aren’t mutually exclusive; instead, they overlap and provide flexible ways of envisioning AI’s role. 1. System Scope — The Reach of Generative AI in Your System System scope refers to the breadth of integration within your system. By viewing integration from this angle, you can assess the role AI plays in managing your platform’s overall functionality. While these categories may overlap, they are useful in facilitating strategic conversations. 2. Spatial Relationships — Where AI Interacts with Features Spatial relationships describe where AI features sit in relation to your platform’s functionality: 3. Functional Relationships — How AI Interacts with Features Functional relationships determine how AI and platform features work together. This includes how users engage with AI and how AI content updates based on feature interactions: Scope of Generative AI By considering these different perspectives—system scope, spatial, and functional—you can drive more meaningful conversations about how Generative AI can best enhance your product’s capabilities. Each approach offers unique value, and careful thought can help teams choose the integration path that aligns with their needs and goals. Scope of Generative AI conversations with Tectonic can assist in planning the best ROI approach to AI. Contact us today. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

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October 24, 2024in Data, Generative AI, Google
Artificial Intelligence and Sales Cloud
24Oct

Artificial Intelligence and Sales Cloud

Artificial Intelligence and Sales Cloud AI enhances the sales process at every stage, making it more efficient and effective. Salesforce’s AI technology—Einstein—streamlines data entry and offers predictive analysis, empowering sales teams to maximize every opportunity. Artificial Intelligence and Sales Cloud explained. Artificial Intelligence and Sales Cloud Sales Cloud integrates several AI-driven features powered by Einstein and machine learning. To get the most out of these tools, review which features align with your needs and check the licensing requirements for each one. Einstein and Data Usage in Sales Cloud Einstein thrives on data. To fully leverage its capabilities within Sales Cloud, consult the data usage table to understand which types of data Einstein features rely on. Setting Up Einstein Opportunity Scoring in Sales Cloud Einstein Opportunity Scoring, part of the Sales Cloud Einstein suite, is available to eligible customers at no additional cost. Simply activate Einstein, and the system will handle the rest, offering predictive insights to improve your sales pipeline. Managing Access to Einstein Features in Sales Cloud Sales Cloud users can access Einstein Opportunity Scoring through the Sales Cloud Einstein For Everyone permission set. Ensure the right team members have access by reviewing the permissions, features included, and how to manage assignments. Einstein Copilot Setup for Sales Einstein Copilot helps sales teams stay organized by guiding them through deal management, closing strategies, customer communications, and sales forecasting. Each Copilot action corresponds to specific topics designed to optimize the sales process. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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October 24, 2024in Artificial Intelligence, Data, Salesforce, Salesforce Sales Cloud, Technology
Salesforce Flow Tests
23Oct

Salesforce Flow is Here

Hello, Salesforce Flow. Goodbye, Workflow Rules and Process Builder. As Bob Dylan famously sang, “The times they are a-changin’.” If your nonprofit is still relying on Workflow Rules and Process Builder to automate tasks in Salesforce, it’s time to prepare for change. These tools are being retired, but there’s no need to panic—Salesforce Flow, a more powerful, versatile automation tool, is ready to take the lead. Why Move to Salesforce Flow? Salesforce is consolidating its automation features into one unified platform: Flow. This shift comes with significant benefits for nonprofits: What This Means for Nonprofits While existing Workflow Rules and Process Builders will still function for now, Salesforce plans to end support by December 31, 2025. This means no more updates or bug fixes, and unsupported automations could break unexpectedly soon after the deadline. To avoid disruptions, nonprofits should start migrating their automations to Flow sooner rather than later. How to Transition to Salesforce Flow Resources to Simplify Migration: Planning Your Migration: Start by auditing your existing automations to determine which Workflow Rules and Process Builders need to be transitioned. Think strategically about how to improve processes and leverage Flow’s expanded capabilities. What Can Flow Do for Your Nonprofit? Salesforce Flow empowers nonprofits to automate processes in innovative ways: Don’t Go It Alone Transitioning to Salesforce Flow may seem overwhelming, but it’s a chance to elevate your nonprofit’s automation capabilities. Whether you need help with migration tools, strategic planning, or Flow development, you don’t have to do it alone. Reach out to our support team or contact us to get started. Together, we can make this transition seamless and set your nonprofit up for long-term success with Salesforce Flow. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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October 23, 2024in Salesforce, Salesforce Flow
Scaling Generative AI
23Oct

Scaling Generative AI

Many organizations follow a hybrid approach to AI infrastructure, combining public clouds, colocation facilities, and on-prem solutions. Specialized GPU-as-a-service vendors, for instance, are becoming popular for handling high-demand AI computations, helping businesses manage costs without compromising performance. Business process outsourcing company TaskUs, for example, focuses on optimizing compute and data flows as it scales its gen AI deployments, while Cognizant advises that companies distinguish between training and inference needs, each with different latency requirements.

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October 23, 2024in Data, Enterprise, Generative AI, Google, Salesforce

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