Design Archives - gettectonic.com

30Mar

AI Then and Now

AI: Transforming User Interactions and Experiences Have you ever been greeted by a waitress who already knows your breakfast order? It’s a relief not to detail every aspect — temperature, how do you want your eggs, what kind of juice, bacon or sausage, etc. This example encapsulates the journey we’re navigating with AI today. AI Then and Now. This article isn’t about ordering breakfast; it’s about the evolution of user interactions, particularly how generative AI might evolve based on past trends in graphical user interfaces (GUIs) and emerging trends in AI interactions. We’ll explore the significance of context bundling, user curation, trust, and ecosystems as key trends in AI user experience in this Tectonic insight. From Commands to Conversations Let’s rewind to the early days of computing when users had to type precise commands in a Command-Line Interface (CLI). Imagine the challenge of remembering the exact command to open a file or copy data. This complexity meant that only a few people could use computers effectively. To reach a broader audience, a shift was necessary. You might think Apple’s creation of the mouse and drop down menues was the pinnacle of success, but truly the evolution predates Apple. Enter ELIZA in 1964, an early natural language processing program that engaged users in basic conversations through keyword recognition and scripted responses. Although groundbreaking, ELIZA’s interactions were far from flexible or scalable. Around the same time, Xerox PARC was developing the Graphical User Interface (GUI), later popularized by Apple in 1984 and Microsoft shortly thereafter. GUIs transformed computing by replacing complex commands with icons, menus, and windows navigable by a mouse. This innovation made computers accessible and intuitive for everyday tasks, laying the groundwork for technology’s universal role in our lives. Not only did it make computing accessible to the masses but it layed the foundation upon which every household would soon have one or more computers! The Evolution of AI Interfaces Just as early computing transitioned from the complexity of CLI to the simplicity of GUIs, we’re witnessing a parallel evolution in generative AI. User prompts are essentially mini-programs crafted in natural language, with the quality of outcomes depending on our prompt engineering skills. We are moving towards bundling complex inputs into simpler, more user-friendly interfaces with the complexity hidden in the background. Context Bundling Context bundling simplifies interactions by combining related information into a single command. This addresses the challenge of conveying complex instructions to achieve desired outcomes, enhancing efficiency and output quality by aligning user intent and machine understanding in one go. We’ve seen context bundling emerge across generative AI tools. For instance, sample prompts in Edge, Google Chrome’s tab manager, and trigger-words in Stable Diffusion fine-tune AI outputs. Context bundling isn’t always about conversation; it’s about achieving user goals efficiently without lengthy interactions. Context bundling is the difference in ordering the eggs versus telling the cook how to crack and prepare it. User Curation Despite advancements, there remains a spectrum of needs where users must refine outputs to achieve specific goals. This is especially true for tasks like researching, brainstorming, creating content, refining images, or editing. As context windows and multi-modal capabilities expand, guiding users through complexity becomes even more crucial. Humans constantly curate their experiences, whether by highlighting text in a book or picking out keywords in a conversation. Similarly, users interacting with ChatGPT often highlight relevant information to guide their next steps. By making it easier for users to curate and refine their outputs, AI tools can offer higher-quality results and enrich user experiences. User creation takes ordering breakfast from a manual conversational process to the click of a button on a vending-like system. Designing for Trust Trust is a significant barrier to the widespread adoption of generative AI. To build trust, we need to consider factors such as previous experiences, risk tolerance, interaction consistency, and social context. Without trust, in AI or your breakfast order, it becomes easier just to do it yourself. Trust is broken if the waitress brings you the wrong items, or if the artificial intelligence fails to meet your reasonable expectations. Context Ecosystems Generative AI has revolutionized productivity by lowering the barrier for users to start tasks, mirroring the benefits and journey of the GUI. However, modern UX has evolved beyond simple interfaces. The future of generative AI lies in creating ecosystems where AI tools collaborate with users in a seamless workflow. We see emergent examples like Edge, Chrome, and Pixel Assistant integrating AI functionality into their software. This integration goes beyond conversational windows, making AI aware of the software context and enhancing productivity. The Future of AI Interaction Generative AI will likely evolve to become a collaborator in our daily tasks. Tools like Grammarly and Github Copilot already show how AI can assist users in creating and refining content. As our comfort with AI grows, we may see generative AI managing both digital and physical aspects of our lives, augmenting reality and redefining productivity. The evolution of generative AI interactions is repeating the history of human-computer interaction. By creating better experiences that bundle context into simpler interactions, empower user curation, and augment known ecosystems, we can make generative AI more trustworthy, accessible, usable, and beneficial for everyone. 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

March 30, 2024in AI Tools, Artificial Intelligence, Data, Generative AI, Google, Salesforce, Salesforce Einstein, Technology

27Mar

Salesforce Bot Planning

Careful Planning: Key to an Effective Bot and Happy Customers When building your bot, thoughtful planning is essential to ensure it efficiently serves customers and meets their needs. Supported Editions Technical Planning Voice and Tone Planning Careful planning in these areas will help ensure your Einstein Bot delivers a smooth, efficient experience for your customers. 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

March 27, 2024in Enterprise

27Mar

Einstein Copilot – A Valued Team Member

What Can Salesforce Einstein Copilot AI Really Do? Einstein Copilot – A Valued Team Member To find out, let’s virtually attend a live demo of the service March 2024. The short answer to the question is “whatever your business needs,” but with a common caveat in AI demos: beware of hallucinations. Keeping Data SafeLet’s rewind a bit. Back in September, Salesforce unveiled Einstein Copilot at Dreamforce, emphasizing customer data safety as a key selling point. Salesforce CEO Marc Benioff stated, “Your data isn’t our product.” Then, in February, the product entered public beta. Salesforce re-emphasized that the Einstein Trust Layer, designed to protect customer data, was a critical reason why customers could trust the responses and actions of Salesforce Einstein Copilot. At the demo safety was again a primary focus. Salesforce Product Management leads Gary Brandeleer and Jaswinder Rattanpal highlighted that Einstein is designed to differentiate between sensitive and non-sensitive data and to verify if the end-user has appropriate access rights for their query. These measures prevent leaks of confidential information and also minimize the impact of any potential “hallucinations” by compartmentalizing data. Rattanpal offered a word of caution: “While we have these amazing tools, be careful because we are not at a stage when they can be 100% trusted. Always have a human in the loop, especially when dealing with information that may become public.” Maximizing EfficiencySalesforce’s emphasis on data safety is wise, and its more than 150,000 customers worldwide will appreciate it. However, the real appeal of Einstein Copilot lies in the efficiency it offers. This efficiency stems from two key principles that drive Salesforce’s approach to AI. The first principle is that AI copilots fundamentally change how humans interact with software. Instead of navigating through clicks and menus, users can ask questions and receive answers directly, making software interaction more conversational. This shift can potentially transform software development and reduce the time required to complete tasks, particularly in sales, marketing, and customer service. Users can access Einstein across Salesforce’s interface. One click launches the assistant, which can execute tasks while the user attends to other duties. This reduces the time spent sifting through information to find answers. During the demo, Rattanpal showcased how Einstein could summarize an account’s financial history and populate different fields with data from a single prompt. Customization and AvailabilityThe second principle is the mix of customization and availability. Salesforce aims to allow users to deploy Einstein Copilot across any desired modules and to customize these deployments to suit each customer’s specific needs. Recognizing that its vast customer base has diverse requirements, Salesforce makes Einstein flexible yet grounded in a safety-first approach. Admins can customize Einstein using Copilot Builder, Prompt Builder, and Model Builder, each offering different levels of customization. Standard actions, like “write an email,” require minimal development, while custom actions typically involve more intricate setups. More Than a Copilot: A CoworkerThese capabilities often make Einstein feel more like a valued team member than a mere copilot. During the demo, Brandeleer showed how Einstein could determine whether a sales opportunity was worth pursuing—a subjective query that Einstein backed with a dozen data-driven reasons. This level of analysis, which would take a human hours or days to compile, underscores Einstein’s potential to exceed human efficiency and objectivity. When an AI can provide better answers to subjective questions than a human, it transcends being a simple tool. If it can effectively manage hallucinations, the question becomes: what can’t Einstein do? Salesforce Einstein Copilot stands out not only for its robust data safety measures but also for the significant efficiency and customization it offers. With its advanced capabilities, Einstein has the potential to revolutionize how businesses handle routine and complex tasks, making it an invaluable asset for any organization. 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

March 27, 2024in Einstein 1 Platform, Salesforce

26Mar

Where Will AI Take Us?

Author Jeremy Wagstaff wrote a very thought provoking article on the future of AI, and how much of it we could predict based on the past. This insight expands on that article. Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think and learn. These machines can perform tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and language translation. Many people think of artificial intelligence in the vein of how they personally use it. Some people don’t even realize when they are using it. Artificial intelligence has long been a concept in human mythology and literature. Our imaginations have been grabbed by the thought of sentient machines constructed by humans, from Talos, the enormous bronze automaton (self-operating machine) that safeguarded the island of Crete in Greek mythology, to the spacecraft-controlling HAL in 2001: A Space Odyssey. Artificial Intelligence comes in a variety of flavors, if you will. Artificial intelligence can be categorized in several ways, including by capability and functionality: You likely weren’t even aware of all of the above categorizations of artificial intelligence. Most of us still would sub set into generative ai, a subset of narrow AI, predictive ai, and reactive ai. Reflect on the AI journey through the Three C’s – Computation, Cognition, and Communication – as the guiding pillars for understanding the transformative potential of AI. Gain insights into how these concepts converge to shape the future of technology. Beyond a definition, what really is artificial intelligence, who makes it, who uses it, what does it do and how. Artificial Intelligence Companies – A Sampling AI and Its Challenges Artificial intelligence (AI) presents a novel and significant challenge to the fundamental ideas underpinning the modern state, affecting governance, social and mental health, the balance between capitalism and individual protection, and international cooperation and commerce. Addressing this amorphous technology, which lacks a clear definition yet pervades increasing facets of life, is complex and daunting. It is essential to recognize what should not be done, drawing lessons from past mistakes that may not be reversible this time. In the 1920s, the concept of a street was fluid. People viewed city streets as public spaces open to anyone not endangering or obstructing others. However, conflicts between ‘joy riders’ and ‘jay walkers’ began to emerge, with judges often siding with pedestrians in lawsuits. Motorist associations and the car industry lobbied to prioritize vehicles, leading to the construction of vehicle-only thoroughfares. The dominance of cars prevailed for a century, but recent efforts have sought to reverse this trend with ‘complete streets,’ bicycle and pedestrian infrastructure, and traffic calming measures. Technology, such as electric micro-mobility and improved VR/AR for street design, plays a role in this transformation. The guy digging out a road bed for chariots and Roman armies likely considered none of this. Addressing new technology is not easy to do, and it’s taken changes to our planet’s climate, a pandemic, and the deaths of tens of millions of people in traffic accidents (3.6 million in the U.S. since 1899). If we had better understood the implications of the first automobile technology, perhaps we could have made better decisions. Similarly, society should avoid repeating past mistakes with AI. The market has driven AI’s development, often prioritizing those who stand to profit over consumers. You know, capitalism. The rapid adoption and expansion of AI, driven by commercial and nationalist competition, have created significant distortions. Companies like Nvidia have soared in value due to AI chip sales, and governments are heavily investing in AI technology to gain competitive advantages. Listening to AI experts highlights the enormity of the commitment being made and reveals that these experts, despite their knowledge, may not be the best sources for AI guidance. The size and impact of AI are already redirecting massive resources and creating new challenges. For example, AI’s demand for energy, chips, memory, and talent is immense, and the future of AI-driven applications depends on the availability of computing resources. The rise in demand for AI has already led to significant industry changes. Data centers are transforming into ‘AI data centers,’ and the demand for specialized AI chips and memory is skyrocketing. The U.S. government is investing billions to boost its position in AI, and countries like China are rapidly advancing in AI expertise. China may be behind in physical assets, but it is moving fast on expertise, generating almost half of the world’s top AI researchers (Source: New York Times). The U.S. has just announced it will provide chip maker Intel with $20 billion in grants and loans to boost the country’s position in AI. Nvidia is now the third largest company in the world, entirely because its specialized chips account for more than 70 percent of AI chip sales. Memory-maker Micro has mostly run out of high-bandwidth memory (HBM) stocks because of the chips’ usage in AI—one customer paid $600 million up-front to lock in supply, according to a story by Stack. Back in January, the International Energy Agency forecast that data centers may more than double their electrical consumption by 2026 (Source: Sandra MacGregor, Data Center Knowledge). AI is sucking up all the payroll: Those tech workers who don’t have AI skills are finding fewer roles and lower salaries—or their jobs disappearing entirely to automation and AI (Source: Belle Lin at WSJ). Sam Altman of OpenAI sees a future where demand for AI-driven apps is limited only by the amount of computing available at a price the consumer is willing o pay. “Compute is going to be the currency of the future. I think it will be maybe the most precious commodity in the world, and I think we should be investing heavily to make a lot more compute.” Sam Altman, OpenAI CEO This AI buildup is reminiscent of past technological transformations, where powerful interests shaped outcomes, often at the expense of broader societal considerations. Consider early car manufacturers. They focused on a need for factories, components, and roads.

March 26, 2024in Generative AI

24Mar

Communications Cloud Summer 24

Salesforce Communications Cloud Summer ’24 Release: Elevating Business Performance and Workflow Efficiency With its Summer ’24 release, Salesforce Communications Cloud unveils an array of powerful new capabilities designed to elevate business performance and optimize workflow efficiency. In this blog, we’ll explore some of our favorite new features, including Field Service improvements that provide technicians with better insights and user experiences, new TM Forum API integrations, and Enterprise Sales Management (ESM) enhancements. Field Service Field Service for Industries optimizes field operations by equipping service teams with advanced tools, enabling companies to maximize asset lifetime value and enhance customer satisfaction. This release includes unique capabilities tailored for field technicians to help with work order execution and asset management. TM Forum In the latest Summer ’24 release, Salesforce has delivered two additional TM Forum APIs, enabling seamless integration of Communications Cloud instances with external systems. These include the TMF620 outbound Product Catalog Management and TMF651 inbound Agreement Management APIs. Enterprise Sales Management Conclusion The main features in the Summer ’24 release allow businesses to operate more efficiently, enhance user experience, and create an open and flexible platform with TM Forum APIs. There are also many other exciting enhancements such as CPQ API improvements, built-in diagnostic tools for EPC configuration, and more. 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

March 24, 2024in Salesforce Communications Cloud

24Mar

Salesforce Education Cloud for Educational Challenges

Educational institutions today confront a multitude of complex challenges, ranging from disjointed information systems to the need for agility in meeting evolving educational demands. Salesforce Education Cloud presents a unified solution aimed at overcoming these obstacles by enhancing operational efficiencies, boosting student engagement, and ensuring compliance with ever-changing educational standards. Below is an in-depth examination of the prevalent challenges faced by educational institutions and the tailored solutions provided by Salesforce Education Cloud. Key Challenges in the Education Sector Salesforce Education Cloud: Tailored Solutions for Education Salesforce Education Cloud addresses these challenges through a suite of customized features and tools designed to streamline operations, enhance student services, and promote effective communication. Real-World Impact of Salesforce Education Cloud Implementation of Salesforce Education Cloud yields transformative benefits across educational institutions: Conclusion Salesforce Education Cloud offers a comprehensive solution to the diverse challenges faced by educational institutions. By integrating this robust platform, schools, colleges, and universities can enhance operational efficiency, improve student outcomes, and cultivate a collaborative educational environment. Institutions seeking to explore the benefits of Education Cloud or enhance their existing systems are encouraged to consult with a Salesforce Education Cloud Consultant for tailored guidance and implementation strategies. 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

March 24, 2024in Salesforce, Salesforce Education Cloud, Salesforce Education Solutions, Salesforce Einstein

20Mar

Technology for a Human-Centric Impact: Introducing the New Nonprofit Cloud

In times of disaster or need, it’s not technology that distributes supplies or ensures access to fundamental rights—it’s people. Nonprofits, whether large or small, work alongside individuals, partner organizations, government agencies, healthcare providers, volunteers, and staff to drive community and planetary improvements. From large-scale disaster responses to community food drives, real change and impact come from collaborative efforts, not isolated actions. Introducing the New Nonprofit Cloud for today’s NGOs. Salesforce’s vision for nonprofits has always been to empower impact makers with the best technology. Technology should be a critical enabler that brings people and organizations together, scaling those moments of impact. Breaking Down Barriers for Greater Impact Salesforce aims to simplify operations for the nonprofit sector by breaking down information silos within organizations and among local or global partners. Achieving greater impact collectively requires collaboration with stakeholders, information sharing, and effective data utilization. Salesforce collaborated with partners and nonprofit peers to address four key priorities: Introducing the New Nonprofit Cloud With these priorities in mind, Salesforce has announced a new vision for Nonprofit Cloud—a suite of nonprofit technology solutions built specifically for the sector. For the first time, instead of layering nonprofit applications on top of the platform, Salesforce is building directly into the core, unlocking innovation across all Salesforce industries. The new Nonprofit Cloud aims to address all goals in a single solution. For over two decades, Salesforce has worked with its community and partner ecosystem to deliver purpose-built packages on top of the Salesforce platform. Together, they have built more than 14 software packages, anchored by the Nonprofit Success Pack (NPSP), which is used by thousands of organizations. Salesforce will continue to support existing offerings like NPSP, Nonprofit Cloud Case Management, the Program Management Module, and more. Today, we have the thrill of Introducing the New Nonprofit Cloud However, Salesforce is now offering a new solution to nonprofit organizations with reimagined program management, case management, outcomes, marketing engagement, and fundraising in one package. The next generation of Nonprofit Cloud, available today, focuses on delivering programs and case management, leveraging the full power of the Salesforce platform. Fundraising and outcomes will be integrated into this solution later this year. Faster and Easier Access to Nonprofit Technology Supporters measure organizations by their impact, and the goal is to focus on driving that impact, not piecing together data from different systems. This new approach provides a faster and more unified way to drive impact by consolidating stakeholder experiences from across organizations and partners. The new Nonprofit Cloud unifies programs, fundraising, engagement, and outcomes, giving easier and faster access to innovations from across all of Salesforce. This connection to Salesforce’s portfolio of best-in-class solutions enhances the ability to make data-driven decisions swiftly, focusing on what works and where changes are needed. Greater Cross-Sector Impact – Introducing the New Nonprofit Cloud The new Nonprofit Cloud is designed for whole-person care. By building Nonprofit Cloud directly into the Salesforce platform, it’s easier to adopt technology used in other industries, such as Health & Life Sciences and the Public Sector. This integration reflects how jobs are actually done—working with program participants, their families, governments, healthcare organizations, and other nonprofits to ensure everyone achieves their goals. This fosters better cross-sector engagement and impact for all served. Impact is Driven by Everyone Behind every relationship, person, or program is data. When these data points are combined, they can be learned from, validated, and traced throughout the process. With the reimagined Nonprofit Cloud, Salesforce is building every component with outcomes in mind, partnering with the customer community to determine critical data to capture. This simplifies outcome measurement, reduces the need for heavy customization, and standardizes the process. Introducing the New Nonprofit Cloud Starting with programs and case management, available today, Salesforce will soon add outcomes, engagement, and fundraising, connecting them to all future innovations. The Power of Us Program Salesforce remains committed to giving 1% of equity, product, and employee time back to its communities through the Power of Us program, which grants qualified nonprofit and educational organizations 10 free technology licenses. The new Nonprofit Cloud innovation will be included. Salesforce will also continue to support existing licenses and paid nonprofit offerings, including the Nonprofit Success Pack (NPSP). This new approach for the nonprofit sector has been successfully used by other industries within Salesforce for years. Salesforce is dedicated to continuing investment in best-in-class nonprofit technology to help achieve significant and lasting impact. Connect with Salesforce Ready to implement Salesforce Nonprofit Cloud to streamline operations and amplify impact? Connect with Salesforce experts for more information. 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

March 20, 2024in Salesforce Nonprofit Cloud

18Mar

Custom Copilot Actions

How to Create a Custom Copilot Action Custom Copilot Actions allow you to extend Copilot’s functionality within Salesforce, enabling users to perform tasks specific to your business needs. By utilizing invocable Apex classes, autolaunched flows, and prompt templates, you can build custom actions tailored to your organization’s requirements. Extend your unified copilot with custom actions. Before You Begin: Steps to Create a Custom Copilot Action: Testing and Deployment: Understanding Einstein Copilot Einstein Copilot is Salesforce’s AI assistant designed to enhance productivity and user experience across various applications and departments. Admins can configure and deploy Copilots to empower users with AI capabilities, streamlining workflows and increasing efficiency. Out-of-the-Box Actions: In the Spring ’24 release, Einstein Copilot offers several out-of-the-box actions, including: Customization and Future Development: Admins can create custom actions to tailor Copilot’s capabilities to their organization’s specific requirements. Custom actions enable tasks such as updating records and integrating with external systems, enhancing productivity and efficiency. When you create a custom action, you build it on top of platform functionality you want to make available in Einstein Copilot, such as invocable Apex classes, autolaunched flows, or prompt templates. Adding custom actions lets you customize your copilot and get more mileage out of your current Salesforce platform capabilities. Access to a custom copilot action depends on the type of Salesforce action it references. For example, if a custom action was built using a flow, the custom action adheres to the permissions, field-level security, and sharing settings configured in the flow. Use Cases and Considerations: Typical Use Cases: Considerations: Building Custom Copilot Actions: Power of Custom Actions: Custom actions extend Copilot’s capabilities, offering a wide range of use cases and functionalities. Actions can be built using flows, prompts, or Apex, providing flexibility and customization options. Descriptive Instructions: Accurate descriptions of actions, inputs, and outputs are essential for Copilot’s understanding and execution. Clear instructions provide context and improve response accuracy. Best Practices: Einstein Copilot, coupled with custom actions, empowers organizations to optimize workflows and drive efficiency. By following best practices and leveraging the full potential of Copilot, Salesforce admins can enhance user experiences and unlock new levels of productivity. Explore these features within your organization to realize the benefits of Salesforce Einstein Copilot Custom Actions. Assign an action to your copilot from the Copilot Actions page, the record page for an action, or the Copilot Action Library tab of the actions panel in the Copilot Builder. Your copilot must be deactivated. To test your action and preview how the output appears in a copilot conversation, open the copilot in the Copilot Builder and start a preview conversation. Enter utterances that you expect to trigger your action, and then make adjustments to the copilot action instructions based on your results. What powers Einstein Copilot custom actions? By facilitating the flow of work through smart, AI-driven actions, Einstein Copilot enhances efficiency and decision-making. Here’s how organizations can harness its power through the design of custom actions, ensuring their operations are as streamlined and effective as possible. 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

March 18, 2024in Mulesoft, Salesforce Einstein

16Mar

AI Success is a Team Sport

The contemporary workplace is currently experiencing a profound transformation. The Future of Jobs Report from the World Economic Forum predicts that AI will replace approximately 85 million jobs by 2025, while concurrently generating around 97 million AI-related jobs. AI Success is a Team Sport and will require hiring and training people. This significant shift necessitates a reevaluation of work dynamics, introducing new roles that involve collaboration between “humans, machines, and algorithms.” Amidst this transformative period, AI provides opportunities for organizations to reimagine existing roles, offer upskilling opportunities, and design innovative positions to meet evolving needs. For leaders in the data domain, the crucial task is to assess which jobs could benefit from AI. This requires a thorough understanding of organizational tasks, skills, and strategic goals, complemented by a scalable change management process to accommodate the growth of AI initiatives. To pinpoint relevant jobs, the following steps can be taken: Despite 67% of global business leaders considering the use of generative AI, an equal number of IT leaders acknowledge a skills gap among their employees. “I think most business leaders have a good sense of what the key jobs are inside their organizations. Of those key jobs, what are the good candidates for AI? I think it’s important for any executive—data or not—to understand what they are and plan accordingly.” SOLOMON KAHN DATA LEADERSHIP COLLABORATIVE The implementation of AI necessitates a specialized team, encompassing roles from project managers to domain experts. The composition of the team depends on the project’s complexity, scope, budget, and overall strategic objectives. But to be sure, AI Success is a Team Sport. Key roles for AI initiatives include: AI acts as a disruptor to traditional business practices, and this disruption is viewed positively. The bonuses far outweigh the challenges. The new generation of user-friendly AI technologies, such as generative AI, has moved beyond the hype cycle, offering applications that generate personalized offers and automated chatbots capable of solving complex customer support issues. In this era powered by AI, data leaders play a pivotal role in driving transformative change. 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

March 16, 2024in Salesforce Einstein

11Mar

Customized Conversational AI Assistant

Create and Customize a Conversational AI Assistant for CRM Einstein Copilot is your all-in-one CRM AI assistant, seamlessly integrated into every Salesforce application. It empowers teams to accelerate tasks with intelligent actions, deploy conversational AI with built-in trust, and easily scale a unified copilot across your organization. Customized Conversational AI Assistant. Einstein 1 Studio Customize and Enhance AI for CRM:Einstein 1 Studio allows you to tailor Einstein Copilot to your specific business needs. Configure actions, prompts, and models to create a personalized AI experience. Users can interact with the AI using natural language, making task execution more intuitive and efficient. Copilot Builder Expand Einstein Copilot with Advanced Features:Enhance Einstein Copilot by integrating actions with familiar Salesforce platform features like Flows, Apex code, and Mulesoft APIs. Convert workflows into copilot actions and test these interactions within a user-friendly interface, enabling you to monitor and refine your copilot’s performance. Prompt Builder Accelerate Employee Task Completion:Design prompt templates that quickly summarize and generate content, helping employees complete tasks faster. Create prompts that draw from CRM data, Data Cloud, and external sources to make every business task more relevant. Develop prompts once and deploy them across Einstein Copilot, Lightning pages, and flows. Model Builder Integrate and Manage AI Models:Incorporate your predictive AI models and large language models (LLMs) within Salesforce through the Einstein Trust Layer. Utilize no-code ML models in Data Cloud, and manage all your AI models from a centralized control platform, ensuring seamless operation and integration. Deploy Trustworthy AI Leverage Generative AI with Built-In Safeguards:Einstein Copilot is designed to ensure the privacy and security of your data, while improving result accuracy and promoting responsible AI use across your organization. Built directly into the Salesforce Platform, the Einstein Trust Layer offers top-tier features and safeguards to ensure your AI deployments are trustworthy. “The combination of AI, data, and CRM allows us to help busy parents solve the ‘what’s for dinner’ dilemma with personalized recipe recommendations their family will love.”— Heather Conneran, Director, Brand Experience Platforms, General Mills 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

March 11, 2024in Data, Generative AI, Mulesoft, Salesforce

08Mar

UX Design Trends 2024

Navigating Design Trends: AI, Discovery, Accessibility, and Collaboration. Salesforce UX Design Trends 2024. As we reflect on the past year and look ahead, design trends are emerging, signaling a pivotal moment in the intersection of creativity, usability, and AI. For developers, admins, architects, and business leaders, understanding these trends is crucial in shaping the future. Here are the four design trends steering this transformative journey: As we move forward, these design trends signify a paradigm shift, emphasizing the significance of AI, streamlined discovery, accessibility, and the growing collaboration between designers and developers. Navigating this transformative landscape requires an adaptable mindset and a commitment to ethical, inclusive design practices from the outset. When you work with Tectonic we take all these considerations to mind as we design or re-design your Salesforce org. Contact Tectonic today. UX Design Trends 2024 Like2 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

March 8, 2024in Salesforce

07Mar

Einstein Trust Layer Explained

The Einstein Trust Layer, seamlessly integrated into the Salesforce Platform, serves as a secure AI architecture designed to meet enterprise security standards. This foundational layer prioritizes stringent security measures, allowing teams to harness the power of generative AI without compromising customer data. Simultaneously, it empowers companies to make the most of their trusted data, thereby enhancing the precision of generative AI responses. Key features of the Einstein Trust Layer include: Integrated and Grounded: An inherent component of every Einstein Copilot, the Trust Layer ensures that generative prompts are firmly rooted and enriched in trusted company data. Its integration with Salesforce Data Cloud establishes a seamless connection, reinforcing the reliability and relevance of generative responses. Zero-Data Retention and PII Protection: Companies can trust that their data will never be retained by third-party Large Language Model (LLM) providers. The Trust Layer incorporates masking techniques for personally identifiable information (PII), ensuring an added layer of data privacy. Toxicity Awareness and Compliance-Ready AI Monitoring: A dedicated safety-detector LLM within the Trust Layer acts as a guard against toxicity, assessing risks to brand reputation by scoring AI generations. This scoring mechanism instills confidence in the safety of responses. Moreover, each AI interaction is meticulously recorded in a secure, monitored audit trail, providing companies with visibility and control over how their data is utilized and ensuring compliance readiness. In alignment with Microsoft’s introduction of Copilot solutions powered by generative AI, Salesforce is leveraging the capabilities of Large Language Models (LLMs) to empower professionals in sales, marketing, and customer service. Building on Salesforce’s existing suite of Einstein AI features, the company unveiled “Einstein 1” this year—a next-generation suite of tools empowering users to seamlessly integrate AI into their everyday workflows. At the core of this advancement is the Einstein Copilot solution, complemented by the new Copilot studio and the Einstein Trust Layer. Like2 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

March 7, 2024in Einstein 1 Platform

04Mar

AI Product Management Tools

Embracing AI in Product Management: Your New Best Friend, Not a Replacement-Original published by https://zedaio.medium.com/ Amid the lively debates about AI taking over product management roles, let’s set the record straight: AI is here as an ally, not a replacement. It’s about leveraging AI to amplify our capabilities, streamline mundane tasks, and make room for the creative and strategic aspects of product management. AI Product Management Tools. Here are seven AI tools that will automate your daily routines, offering support that transforms the way you manage products. Ready to upgrade your product management game with AI by your side? Let’s dive in! 1. Zeda.io Zeda.io is one of the best AI tools for product managers. It offers a complete suite of features that help you in feedback management, strategic planning, and closing the loop. It is a perfect tool if you are striving to balance your customer needs and business goals. With integrations like Slack, Gong, Teams, Salesforce, and more, you can gather and manage customer feedback effortlessly. Its unique AI technology generates valuable, actionable insights by categorizing all the feedback, helping you uncover pressing customer issues and decide what to build next. Key Features: 2. ChatGPT An obvious choice, ChatGPT can automate many of your tasks. It helps make sense of vague product user feedback, create PRDs, release notes, and other documents. The key is to use the right prompts and GPT plugins tailored for product managers. Key Features: 3. Notion AI Notion is a cloud-based productivity and collaboration tool that provides various organizational tools, including task management, project tracking, to-do lists, bookmarking, and more. Notion’s AI can assist product managers in several ways. Key Features: 4. Uizard Uizard is a user interface design tool that uses AI to quickly and efficiently create wireframes, mockups, and prototypes in minutes. The tool’s advanced deep-learning algorithms analyze images provided by product teams and managers to create design themes. Key Features: 5. ClickUp ClickUp is a cloud-based tool that helps teams manage their work effectively, offering features like task management, time tracking, file sharing, and communication tools. ClickUp is highly customizable and offers multiple AI tools that integrate seamlessly into workflows. Key Features: 6. Delibr Delibr is an excellent tool for AI product teams to collaborate effectively during the feature refinement process. It helps capture, synthesize, and organize feedback from diverse sources, enabling informed decision-making and creating high-quality documentation. Key Features: 7. Fireflies.ai Fireflies.ai enhances meeting productivity by transcribing, summarizing, and analyzing voice conversations. It integrates with major video-conferencing platforms and offers various ways to capture meetings, including a Chrome extension and direct uploads. Key Features: AI Product Management Tools Embracing AI in product management doesn’t mean diminishing the value of human insight; it’s about enhancing our capabilities and efficiency. The seven AI tools outlined here offer a glimpse into a future where technology and creativity intersect, empowering product managers to achieve more in less time. By integrating suitable tools into your workflow, you can focus on innovation and strategy, ensuring your products not only meet but exceed user expectations. Let AI be your ally to achieve greater heights and product 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

March 4, 2024in AI Tools, Data, Google, Salesforce, Salesforce Einstein, Technology

03Mar

Train Your Own SORA Model

Unveiling the Vision Transformer: A Leap in Video Generation The closest open-source model to SORA is Latte, which uses the same Vision Transformer architecture. So, what makes the Vision Transformer so outstanding, and how does it differ from previous methods? You can Train Your Own SORA Model. Latte hasn’t open-sourced its text-to-video training code. We’ve replicated this code from the paper and made it available for anyone to use in training their own SORA alternative model. Let’s discuss how effective our training was. From 3D U-Net to Vision Transformer Image generation has advanced significantly, with the U-Net model structure being the most commonly used: If you’re confused about the network structures, remember the key principle of deep learning: “Just Add More Layers!” Vision Transformer: A Game Changer In 3D U-Net, the transformer can only function within the U-Net, limiting its view. The Vision Transformer, however, enables transformers to globally manage video generation. Training Your Open-Source SORA Alternative with Latte Latte uses the video slicing sequence and Vision Transformer method discussed. While Latte hasn’t open-sourced its text-to-video model training code, we’ve replicated it here: GitHub Repo. Training involves three steps: For more details, see the GitHub repo. They’ve also made improvements to the training process: Model Performance The official Latte video shows impressive performance, especially in handling significant motion. However, our own tests indicate that while Latte performs well, it isn’t the top-performing model. Other open-source models have shown better performance. We will continue to share information on models with better performance, so stay tuned to Tectonic’s Insights. Hardware Requirements Due to its large scale, training Latte requires an A100 or H100 with 80GB of memory. 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

March 3, 2024in Salesforce

02Mar

Einstein Copilot Studio Explained

Einstein Copilot Studio Explained: Crafting and Personalizing a Reliable AI Assistant Enterprises aiming to personalize Einstein Copilot can leverage the newly introduced Einstein Copilot Studio. This platform enables the construction and customization of AI assistants, incorporating pertinent prompts, skills, and AI models tailored for specific sales, service, marketing, commerce, and IT tasks. Beyond the confines of Salesforce applications, companies can seamlessly integrate Einstein Copilot into consumer-facing channels. This extension enhances customer interactions by embedding AI assistants into websites for real-time chat capabilities or integrating with popular messaging platforms such as Slack, WhatsApp, or SMS. Einstein Copilot Studio comprises the following key components: Just as Microsoft has introduced its own Copilot solutions, powered by generative AI, Salesforce is tapping into the power of LLMs to empower sales, marketing, and customer service professionals. Building on Salesforce’s existing range of Einstein AI features, the company announced “Einstein 1” this year – the next generation of the Salesforce platform. Einstein 1 is a comprehensive suite of tools that empowers users to bring AI into their everyday workflows. The Einstein Copilot (Salesforce Copilot) solution is at the core of this solution, alongside the new Copilot studio and the Einstein Trust Layer. Contact Tectonic today to explore the value of Einstein Copilot Studio for your company., Like2 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

March 2, 2024in Einstein 1 Platform

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