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Deep Dive Summer 24 Release

Deep Dive Summer 24 Release

Deep Dive Summer 24 Release Get ready, Salesforce fans! The Summer ’24 release is here, and it’s like Christmas morning for tech geeks. We’re talking about new features, enhancements, and improvements that will make you wonder how you ever lived without them. This Tectonic insight is your ultimate guide to all the exciting updates, changes, and key considerations for this release. So hang on tight to your keyboards and let’s dive into the Christmas treat bag of goodies coming your way! Key Highlights – Deep Dive Summer 24 Release What’s New in Einstein AI? 1. Einstein for Flow Meet your new best friend for building Salesforce workflows, Salesforce Flow. Just describe what you need in plain English, and Einstein will whip up the workflow for you. For example, say “Notify sales reps when a lead converts,” and boom, it’s done. Automation just got a whole lot easier and way cooler. How to: Einstein for Flow makes complex processes feel like a walk in the park, letting you deliver solutions faster than you can say “workflow.” Considerations: 2. Einstein for Formulas No more tearing your hair out over formula syntax errors. Einstein for Formulas will not only tell you what’s wrong but also suggest fixes, saving you from endless hours of debugging. How to: Einstein for Formulas cuts down errors and speeds up formula creation, making your life exponentially easier. Like easier squared. Easier to the nth degree. Considerations: UI/UX Enhancements 1. Add New Custom Fields to Dynamic Forms-Enabled Pages Say goodbye to limitations! You can now add new custom fields directly to Dynamic Forms-enabled pages, aligning fields with your ever-changing business needs. Considerations: 2. Use Blank Spaces to Align Fields on Dynamic Forms-Enabled Pages Finally, a way to make your Dynamic Forms pages look neat and tidy with blank spaces for perfect alignment. Considerations: 3. Set Conditional Visibility for Individual Tabs in Lightning App Builder Now you can make specific tabs visible based on user profiles, record types, or other criteria. Customization just got a whole lot more precise. Considerations: 4. Create Rich Text Headings in Lightning App Builder Make your headings pop with bold, italic, and varied font sizes. Your Lightning pages are about to get a visual upgrade. Considerations: Flow Updates 1. Automation Lightning App A one-stop shop for managing and executing all your automation tools and processes. Considerations: 2. Lock and Unlock Records with Action Gain more control over your processes by locking records during critical stages and unlocking them when done. Considerations: 3. Check for Matching Records (Upsert) When Creating Records Avoid duplicates by checking for existing records before creating new ones. One can never have too many de-dupe tools. Considerations: 4. Transform Your Data in Flows (Generally Available) Now generally available, perform calculations, data transformations, and more with the Transform element in Flow Builder. Considerations: Admin Enhancements 1. Field History Tracking Manage tracked objects and fields more efficiently with a centralized page in “Setup.” Considerations: 2. See What’s Enabled in Permission Sets and Permission Set Groups (Generally Available) Enhanced permission set viewing improves visibility and control over security configurations. Considerations: 3. Get a Summary of User’s Permissions and Access Quickly view user permissions, public groups, and queues from the user’s detail page. Help and Training Community: Salesforce is simplifying Permission Set management by phasing out Profiles. Data Cloud Vector Database Vector search capabilities allow the creation of searchable “vector embeddings” from unstructured data, enhancing AI applications’ understanding of semantic similarities and context. Considerations: Deep Dive Summer 24 Release The Salesforce Summer ’24 release is packed with features designed to enhance your Salesforce experience. From a sleek new interface to powerful automation tools, enhanced analytics, and expanded integration options, this release aims to elevate workflow efficiency and data protection. Jump into the exciting updates, and let’s make automation simpler and more user-friendly together! 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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Kaspersky Banned by US Government

Kaspersky Banned by US Government

This week, the U.S. Department of Commerce announced a prohibition on Kaspersky Lab Inc., the American arm of Russian antivirus software developer Kaspersky, and its affiliated companies from selling their products in the United States. Kaspersky Banned by US Government. The Biden administration’s new initiative to remove Kaspersky Lab’s antivirus software from U.S. tech infrastructure has been nearly a decade in the making. Why it Matters: Taking a measured approach to the ban — the most severe action yet against a foreign cybersecurity company — may help the U.S. government avoid the implementation challenges it has encountered in similar cases, according to experts. The Big Picture: The U.S. government is still struggling to eliminate Chinese telecommunications company Huawei’s equipment from American networks, nearly five years after initiating those actions. Additionally, lawmakers only recently passed legislation this year to force China-based ByteDance to divest its ownership in TikTok or face a ban, following about four years of regulatory deliberations. This law is currently being contested in court. Threat Level: Each of these companies is subject to laws in their home countries that could compel them to share U.S. customer data transmitted through their products. However, the U.S. government has not declassified specific instances of Russia or China forcing these companies to share information about Western customers. Context: Kaspersky’s antivirus product has been under scrutiny longer than both Huawei and TikTok, yet it took three administrations to implement a sales ban. Statements: “Kaspersky has done good research, they have a good product, but there was a concern that they had a sweet spot for the Russian government,” Lewis told Axios. Historical Context: Kaspersky first drew attention in Washington back in 2015 when the National Security Agency received a tip that the company may have collected information about U.S. hacking tools and shared it with the Kremlin. In 2017, Israeli government hackers found evidence that Kaspersky might have obtained the NSA hacking tools via an agency employee using the antivirus software on his home computer. In response, Kaspersky asserted it “does not have inappropriate ties to any government” and that it has been “caught in the middle of a geopolitical fight.” Effective July 20, the Bureau of Industry and Security of the Department of Commerce will enforce this ban, which also prevents the company from issuing new security updates to its existing customers starting September 29. Kaspersky users are really left no choice but to find an alternative antivirus solution. Kaspersky Banned by US Government doesn’t just mean the government can no longer use the software. Kaspersky Banned by US Government The decision stems from national security concerns. Following an extensive investigation, the Commerce Department determined that Kaspersky’s operations in the U.S. pose a risk to national security due to the Russian government’s offensive cyber capabilities and its potential influence over Kaspersky’s activities. The Department concluded that mitigation measures would not adequately address these risks. These accusations ultimately led to the U.S. government banning Kaspersky’s software on its networks, although it stopped short of halting new sales until last week. The Intrigue: The Department of Commerce recently acquired new authorities that facilitated the ban on Kaspersky’s antivirus sales, officials disclosed during a briefing. Between the Lines: Despite these concerns, U.S. critical infrastructure organizations continued to use Kaspersky’s antivirus and other cybersecurity products. State of Play: Experts note that unless Kaspersky completely restructured its organizational setup, changed leadership, or left Russia entirely, it had limited options to counter the impending ban. What’s Next: Homeland Security Secretary Alejandro Mayorkas told Axios that his department is equipped to help critical infrastructure organizations comply with Commerce’s implementation deadlines. The Commerce Department advises current users of Kaspersky software to transition to alternative vendors to mitigate potential cybersecurity vulnerabilities. While users who continue to utilize Kaspersky products will not face legal repercussions, they are advised to assume full responsibility for any associated cybersecurity risks. Secretary of Commerce Gina Raimondo emphasized the Department’s commitment to safeguarding U.S. national security and its citizens, stating, “Russia has repeatedly demonstrated its ability and intention to exploit Russian entities such as Kaspersky Lab to gather and weaponize sensitive U.S. information.” She underscored that this action, utilizing the Department’s ICTS authorities for the first time, underscores Commerce’s role in supporting national defense and sends a clear message to adversaries. Efforts to restrict or prohibit Kaspersky’s operations in the U.S. date back to 2017, when the Trump administration initially barred its software from use by most U.S. government agencies. Subsequently, in the same year, the Department of Homeland Security instructed federal agencies to discontinue the use of Kaspersky software. Despite legal challenges by Kaspersky, including appeals in court, these measures culminated in a permanent ban on the company’s products for government use in 2019. The comprehensive ban on Kaspersky from operating in the U.S. in 2024 coincides with heightened geopolitical tensions, particularly amidst Russia’s ongoing conflict in Ukraine. Responding to the ban, a Kaspersky spokesperson expressed disappointment, stating that the Department of Commerce’s decision seemed influenced by current geopolitical dynamics rather than an objective assessment of the company’s products and services. The company intends to explore all available legal avenues to protect its current operations and partnerships. Kaspersky Banned by US Government 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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Slack Integrating AI Into Platform

Slack Integrating AI Into Platform

Slack’s CEO Denise Dresser announced that AI will soon be integrated into every aspect of the platform, enabling users to manage tasks and launch new projects without leaving the application. This announcement highlights a significant shift towards enhancing productivity and collaboration within Slack using advanced AI capabilities. Slack Integrating AI Into Platform. During a media session following her keynote at Salesforce’s World Tour event in Boston, Dresser outlined her vision for AI in Slack. Having taken on her role six months ago after years with Salesforce, she emphasized the integration of Slack with Salesforce’s Einstein Copilot. Acquired by Salesforce in late 2020, Slack aims to provide a unified experience for users by leveraging AI to manage both structured and unstructured data. The goal is to help users quickly find key conversations and turn them into actionable tasks and projects. Dresser noted the challenges in navigating chat histories and identifying important moments, which AI integration aims to address. Slack Integrating AI Into Platform “AI can significantly drive productivity,” Dresser said. “With Slack AI Search, Slack becomes your organization’s long-term memory. It allows users to easily find what they need through generative summaries, which was a major breakthrough for us.” Dresser highlighted the rapid adoption of AI and its integration into Slack’s functionality, leading to an evolution in skills such as prompt engineering and natural language processing. These advancements enable tasks like software creation without traditional coding methods. She pointed out the rapid growth in AI adoption, comparing it to the adoption rates of ChatGPT, mobile phones, and Facebook. Dresser believes this trend will continue as people experience productivity improvements with AI. AI will be embedded in various Slack features, including Canvas, Workflow, and Huddle, providing seamless assistance within the application. Users may not even realize they are interacting with AI, as it will naturally enhance Slack’s functionality. For instance, instead of manually searching through messages, AI will highlight the most important summaries. Dresser also mentioned the newly launched Slack Lists feature, which automatically captures and surfaces key parts of channel conversations. She stressed the importance of reducing the need to switch between different applications, which can drain time and productivity. “We have millions of people working in Slack; why leave Slack?” she said. “We wanted to integrate capabilities for tasks, lists, and projects directly into Slack, starting right within conversations.” In the future, Slack will also suggest relevant chat channels for project purposes, providing users with powerful insights and capabilities. Dresser noted that while only about a third of employees currently use AI-powered platforms, those who do report an average 81% increase in productivity by eliminating mundane tasks. As AI continues to be embedded into Slack and Salesforce tools, Dresser acknowledged the challenge of maintaining the platform’s beloved feel and integrity. “We’ve already integrated Slack, Sales Elevate, and Salesforce. Copilot’s integration will be excellent,” she said. “We have focused on preserving the unique Slack experience, even while enhancing it with new architectural integrations. Our goal is to ensure that Slack remains efficient and productive while staying true to its core identity.” 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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Lakeflow for Data Engineering

Lakeflow for Data Engineering

Databricks unveiled Databricks LakeFlow last week, a new tool designed to unify all aspects of data engineering, from data ingestion and transformation to orchestration. What is Databricks LakeFlow? According to Databricks, LakeFlow simplifies the creation and operation of production-grade data pipelines, making it easier for data teams to handle complex data engineering tasks. This solution aims to meet the growing demands for reliable data and AI by providing an efficient and streamlined approach. The Current State of Data Engineering Data engineering is crucial for democratizing data and AI within businesses, yet it remains a challenging field. Data teams must often deal with: How LakeFlow Addresses These Challenges LakeFlow offers a unified experience for all aspects of data engineering, simplifying the entire process: Key Features of LakeFlow LakeFlow comprises three main components: LakeFlow Connect, LakeFlow Pipelines, and LakeFlow Jobs. Availability LakeFlow is entering preview soon, starting with LakeFlow Connect. Customers can register to join the waitlist today. 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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Single Digit Members

Single Digit Members

The Single Digit Growth Club: A Surge in New Members What Do Salesforce and Asana Have in Common? Both Salesforce and Asana: They have now joined the ranks of The Single Digit Growth Club, projecting growth below 10% for the coming year. It Wasn’t Supposed to Be This Way Why not? Mainly due to historically high Net Revenue Retention (NRR). Salesforce traditionally maintained an NRR well above 110%. Asana, despite catering to many SMBs (where high NRR is harder to achieve), also had high NRR until recently. With an NRR of 110%, growth expectations were typically around 20%-30% annually. With an NRR of 120% or more, as many companies had until recently (and some, like Databricks, still have at 140%+), 40% annual growth seemed attainable even at $1B ARR. However, while NRR is still strong, often at least 100%, it is no longer overperforming in many cases. Even high fliers like Monday.com have seen dips in NRR. Despite their smaller deal sizes, Monday.com’s NRR is the lowest it has been in over four years. The Impact of NRR Declines A drop of 10%-20% in NRR is significantly hampering growth, pushing even market leaders into The Single Digit Growth Club. But not everyone is struggling. The Haves and Have Nots in SaaS In today’s SaaS landscape, there is a stark contrast between the Haves and the Have Nots. Companies operating outside of B2B, those that are truly AI-native, and others are experiencing remarkable growth. However, within tech sales, a decline in NRR is severely impacting growth. Conclusion The shift to single-digit growth is a reality many SaaS companies are grappling with. As we navigate this new landscape, it’s clear that maintaining high NRR and adapting to market changes are crucial for sustaining growth. 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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AI Impact on Workforce

AI Impact on Workforce

About a month ago, Jon Stewart did a segment on AI causing people to lose their jobs. He spoke against it. Well, his words were against it, but deep down, he’s for it—and so are you, whether you realize it or not. AI Impact on Workforce is real, but is it good or bad? The fact that Jon Stewart can go on TV to discuss cutting-edge technology like large language models in AI is because previous technology displaced jobs. Lots of jobs. What probably felt like most jobs. Remember, for most of human history, 80–90% of people were farmers. The few who weren’t had professions like blacksmithing, tailoring, or other essential trades. They didn’t have TV personalities, TV executives, or even TVs. Had you been born hundreds of years ago, chances are you would have been a farmer, too. You might have died from an infection. But as scientific and technological progress reduced the need for farmers, it also gave us doctors and scientists who discovered, manufactured, and distributed cures for diseases like the plague. Innovation begets innovation. Generative AI is just the current state of the art, leading the next cycle of change. The Core Issue This doesn’t mean everything will go smoothly. While many tech CEOs tout the positive impacts of AI, these benefits will take time. Consider the automobile: Carl Benz patented the motorized vehicle in 1886. Fifteen years later, there were only 8,000 cars in the US. By 1910, there were 500,000 cars. That’s 25 years, and even then, only about 0.5% of people in the US had a car. The first stop sign wasn’t used until 1915, giving society time to establish formal regulations and norms as the technology spread. Lessons from History Social media, however, saw negligible usage until 2008, when Facebook began to grow rapidly. In just four years, users soared from a few million to a billion. Social media has been linked to cyberbullying, self-esteem issues, depression, and misinformation. The risks became apparent only after widespread adoption, unlike with cars, where risks were identified early and mitigated with regulations like stop signs and driver’s licenses. Nuclear weapons, developed in 1945, also illustrate this point. Initially, only a few countries possessed them, understanding the catastrophic risks and exercising restraint. However, if a terrorist cell obtained such weapons, the consequences could be dire. Similarly, if AI tools are misused, the outcomes could be harmful. Just this morning a news channel was covering an AI bot that was doing robo-calling. Can you imagine the increase in telemarketing calls that could create? How about this being an election cycle year? AI and Its Rapid Adoption AI isn’t a nuclear weapon, but it is a powerful tool that can do harm. Unlike past technologies that took years or decades to adopt, AI adoption is happening much faster. We lack comprehensive safety warnings for AI because we don’t fully understand it yet. If in 1900, 50% of Americans had suddenly gained access to cars without regulations, the result would have been chaos. Similarly, rapid AI adoption without understanding its risks can lead to unintended consequences. The adoption rate, impact radius (the scope of influence), and learning curve (how quickly we understand its effects) are crucial. If the adoption rate surpasses our ability to understand and manage its impact, we face excessive risk. Proceeding with Caution Innovation should not be stifled, but it must be approached with caution. Consider historical examples like x-rays, which were once used in shoe stores without understanding their harmful effects, or the industrial revolution, which caused significant environmental degradation. Early regulation could have mitigated many negative impacts. AI is transformative, but until we fully understand its risks, we must proceed cautiously. The potential for harm isn’t a reason to avoid it altogether. Like cars, which we accept despite their risks because we understand and manage them, we need to learn about AI’s risks. However, we don’t need to rush into widespread adoption without safeguards. It’s easier to loosen restrictions later than to impose them after damage has been done. Let’s innovate, but with foresight. Regulation doesn’t kill innovation; it can inspire it. We should learn from the past and ensure AI development is responsible and measured. We study history to avoid repeating mistakes—let’s apply that wisdom to AI. Content updated July 2024. 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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Changes in Advertising Changing CRMs

Changes in Advertising Changing CRMs

Oracle announced last week that it is exiting the advertising business and will sunset its adtech by September 30. While the announcement is not surprising given the massive layoffs in 2022 affecting Oracle Advertising teams, the rapidity of Oracle Advertising’s decline is a clear indicator of how swiftly the digital advertising landscape can evolve. This move is likely just the first of many significant Changes in Advertising Changing CRMs. What happened? Oracle Advertising faced challenges beginning in 2018 and never managed to recover. Several forces related to data deprecation adversely impacted the business: Changes in Advertising Changing CRMs Retooling its acquisitions to function in a consent-driven and regulated environment would have required significant investment from Oracle. Given its track record with privacy law compliance, this would have been a daunting task, necessitating both rapid innovation and market trust in its solutions. What does this mean for the advertising ecosystem? Oracle’s exit from adtech marks a significant shift in the advertising ecosystem. The sharp decline in advertising revenue from $2 billion in 2022 to $300 million in 2024 suggests a major miscalculation by Oracle. Without demand- or supply-side platforms (unlike Google, Microsoft, and Amazon) and lacking a large audience base (unlike Meta, Disney, and Netflix), Oracle’s benefits as an adtech partner or acquirer were unclear. The key question now is whether Oracle’s intellectual property will find new ownership and continue in some form. What does this mean for the marketing ecosystem? The broader marketing ecosystem is likely to see more shifts as major players adapt to the new landscape. Leading martech vendors like Adobe and Salesforce have already transitioned from DMPs to CDPs. Adobe Real-Time CDP and Salesforce Data Cloud for Marketing are gaining market share, while Oracle has struggled in the B2C martech space. Oracle’s decision to cut investments in martech and adtech has significantly impaired its B2C market efforts, with products like Responsys failing to gain the traction that Eloqua has in the B2B space. Oracle also announced it will sunset related B2C marketing products like Oracle Maxymiser in the coming months. These changes are just the beginning of a broader transformation in digital advertising, driven by evolving privacy standards, consumer expectations, and technological advancements. This marks the dawn of a new era in which agility and compliance will be key to success in the digital advertising and marketing landscapes. 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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Requirements Engineering

Requirements Engineering

Every project needs clear requirements. No exceptions. Without them, a project turns into a group of people standing around, unsure of what to do, essentially making things up as they go. This scenario may sound familiar to anyone who has been involved in disorganized projects. What are requirements? According to the Association for Project Management (APM), “Requirements are the wants and needs of stakeholders clearly defined with acceptance criteria.” Requirements engineering is the process for managing the entire lifecycle of these needs and involves five key stages: Let’s dive deeper into these stages: 1. Requirements Elicitation Sometimes, the term “requirements capture” is used, as if stakeholders’ needs are floating around, waiting to be caught. However, requirements are not passively waiting; they must be actively elicited. Elicitation Methods: Eliciting requirements involves interpreting genuine needs, not just compiling a wish list of requested features. 2. Requirements Analysis Once you’ve gathered a set of requirements, it’s time for analysis to ensure they are comprehensive, feasible, and aligned with the project’s objectives. This phase is crucial because 80% of project errors occur during the requirements phase, yet it often receives less than 20% of a project’s time. Key steps include: 3. Requirements Documentation After analyzing requirements, document them clearly to communicate with stakeholders and developers. A good requirements document typically includes: One popular method for documenting requirements is through user stories, which frame requirements from the user’s perspective: User stories focus on meeting user needs rather than prescribing technical specifications. 4. Requirements Validation The next step is validating your documented requirements. This ensures they accurately represent what users and stakeholders need. Validation methods include: Validation is essential to ensure requirements are complete, realistic, and verifiable. 5. Requirements Management The final phase involves tracking and managing changes to requirements throughout the project. Key Concepts: Agile frameworks often rely on iterative approaches, where product owners manage changes during sprint reviews and retrospectives. Summary Requirements engineering consists of five interdependent stages: elicitation, analysis, documentation, validation, and management. While these concepts may seem detailed, they offer a structured framework that’s essential for delivering high-quality solutions. By following this approach, even smaller, lower-risk digital projects can benefit from clear and actionable requirements. 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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Agentic AI is Here

Agentic AI is Here

Embracing the Era of Agentic AI: Redefining Autonomous Systems A new paradigm in artificial intelligence, known as “Agentic Artificial Intelligence,” is poised to revolutionize the capabilities of the known autonomous universe. This cutting-edge technology represents a significant leap forward in AI-driven decision-making and action, promising transformative impacts across various industries including healthcare, manufacturing, IT, finance, marketing, and HR. Agents are the way to go! There is no two ways about this. Looking into the progression of the Large Language Model based applications since last year, its not hard to see that the Agentic Process (agents as reusable, specific and dedicated single unit of work) — would be the way to build Gen AI applications. What is Agentic AI? Agentic Artificial Intelligence marks a departure from traditional AI models that primarily focus on passive observation and analysis. Unlike its predecessors, which often require human intervention to execute tasks, Agentic AI systems possess the autonomy to initiate actions independently based on their assessments. This allows them to navigate much more complex environments and undertake tasks with a level of initiative and adaptability previously unseen. At least outside of sci-fy movies. Real-World Applications of Agentic Artificial Intelligence Healthcare In healthcare, Agentic AI systems are transforming patient care. These systems autonomously monitor vital signs, administer medication, and assist in surgical procedures with unparalleled precision. By augmenting healthcare professionals’ capabilities, these AI-driven agents enhance patient outcomes and streamline care processes. Augmenting is the key word, here. Manufacturing and Logistics In manufacturing and logistics, Agentic AI optimizes operations and boosts efficiency. Intelligent agents handle predictive maintenance of machinery, autonomous inventory management, and robotic assembly. Leveraging advanced algorithms and sensor technologies, these systems anticipate issues, coordinate complex workflows, and adapt to real-time production demands, driving a shift towards fully autonomous production environments. Customer Service Within enterprises, AI agents are revolutionizing business operations across various departments. In customer service, AI-powered chatbots with Agentic Artificial Intelligence capabilities engage with customers in natural language, providing personalized assistance and resolving queries efficiently. This enhances customer satisfaction and allows human agents to focus on more complex tasks. Marketing and Sales Agentic Artificial Intelligence empowers marketing and sales teams to analyze vast datasets, identify trends, and personalize campaigns with unprecedented precision. By understanding customer behavior and preferences at a granular level, AI agents optimize advertising strategies, maximize conversion rates, and drive revenue growth. Finance and Accounting In finance and accounting, Agentic AI streamlines processes like invoice processing, fraud detection, and risk management. These AI-driven agents analyze financial data in real time, flag anomalies, and provide insights that enable faster, more informed decision-making, thereby improving operational efficiency. Ethical Considerations of Agentic Artificial Intelligence The rise of Agentic AI also brings significant ethical and societal challenges. Concerns about data privacy, algorithmic bias, and job displacement necessitate robust regulation and ethical frameworks to ensure responsible and equitable deployment of AI technologies. Navigating the Future with Agentic AI The advent of Agentic AI ushers in a new era of autonomy and innovation in artificial intelligence. As these intelligent agents permeate various facets of our lives and enterprises, they present both challenges and opportunities. To navigate this new world, we must approach it with foresight, responsibility, and a commitment to harnessing technology for the betterment of humanity. 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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SFR-Embedding v2 from Salesforce

SFR-Embedding v2 from Salesforce

The release of Salesforce Embedding Model version 2 (SFR-embedding-v2) marks a notable milestone in the field of Natural Language Processing (NLP), underscoring Salesforce’s commitment to advancing AI technologies. SFR-Embedding v2 from Salesforce. Key Highlights of the SFR-embedding-v2 Model Release: Achievement on MTEB Benchmark: SFR-embedding-v2 has achieved a top-1 position on the HuggingFace MTEB benchmark, surpassing a performance score of 70+. This accomplishment reflects its advanced capabilities and the rigorous development undertaken by Salesforce’s research team. Enhanced Multitasking Capabilities: The model introduces a new multi-stage training recipe aimed at enhancing multitasking abilities. This innovative approach enables simultaneous performance across multiple tasks, significantly improving versatility and efficiency. Advancements in Classification and Clustering: Significant strides have been made in classification and clustering tasks, enhancing the model’s ability to understand and categorize data accurately. These improvements make SFR-embedding-v2 highly effective across diverse applications, from data sorting to pattern identification. Strong Retrieval Performance: Beyond classification and clustering, the model excels in retrieval tasks, efficiently locating and retrieving relevant information from extensive datasets. This capability is crucial for AI applications requiring rapid access to data insights. Technical Specifications: SFR-embedding-v2 boasts a substantial size with 7.11 billion parameters and utilizes the BF16 tensor type. These technical specifications contribute to its robust performance and capacity to handle complex tasks, showcasing Salesforce’s innovative AI model architecture. Community and Collaboration: Developed collaboratively by a dedicated team of Salesforce researchers including Rui Meng, Ye Liu, Tong Niu, Shafiq Rayhan Joty, Caiming Xiong, Yingbo Zhou, and Semih Yavuz, the model integrates diverse expertise and innovative approaches, pivotal to its success. Future Directions: Salesforce continues to explore new avenues and enhancements for the model. Future updates aim to push the boundaries of AI capabilities, addressing current limitations and expanding its utility across various sectors. Practical Applications: The versatility of SFR-embedding-v2 extends to text generation, feature extraction, and natural language understanding, making it invaluable across industries such as healthcare and finance where accurate and efficient data processing is critical. In summary, the release of Salesforce Embedding Model version 2 represents a significant advancement in AI technology. Its top performance on benchmarks, enhanced multitasking capabilities, and improvements in critical tasks like classification and clustering underscore its potential to revolutionize AI applications. Supported by robust technical specifications and ongoing research efforts, SFR-embedding-v2 is poised to lead the AI community forward with its innovative capabilities. 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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Mamba-2

Mamba-2

Introducing Mamba-2: A New Era in State Space Model Architecture Researchers Tri Dao and Albert Gu have unveiled Mamba-2, the next iteration of their widely popular Mamba-1 model on GitHub. This new model promises significant improvements and innovations in the realm of state space models, particularly for information-dense data like language models. What is Mamba-2? M2 is a state space model architecture designed to outperform older models, including the widely used transformers. It shows remarkable promise in handling data-intensive tasks with greater efficiency and speed. Key Features of Mamba-2 Core Innovation: Structured State Space Duality (SSD) Performance Improvements Architectural Changes Performance Metrics In rigorous testing, M2 demonstrated superior scaling and faster training times compared to M1. Pretrained models, with sizes ranging from 130 million to 2.8 billion parameters, have been trained on extensive datasets like Pile and SlimPajama. Performance remains consistent across various tasks, with only minor variations due to evaluation noise. Specifications Getting Started with Mamba-2 To start using M2, install it via the command !pip install mamba-ssm and integrate it with PyTorch. Pretrained models are available on Hugging Face, facilitating easy deployment for various tasks. Conclusion Mamba-2 marks a significant advancement in state space model architecture, offering enhanced performance and efficiency over its predecessor and other models like transformers. Whether you’re engaged in language modeling or other data-intensive projects, M2 provides a powerful and efficient solution. 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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Cyber Group Targets SaaS Platforms

Cyber Group Targets SaaS Platforms

Cyber Group UNC3944 Targets SaaS Platforms like Azure, Salesforce, vSphere, AWS, and Google Cloud UNC3944, also known as “0ktapus” and “Scattered Spider,” has shifted its focus to attacking Software-as-a-Service (SaaS) applications, as reported by Google Cloud’s Mandiant threat intelligence team. This hacking group, previously linked to incidents involving companies such as Snowflake and MGM Entertainment, has evolved its strategies to concentrate on data theft and extortion. Cyber Group Targets SaaS Platforms Attack Techniques UNC3944 exploits legitimate third-party tools for remote access and leverages Okta permissions to expand their intrusion capabilities. One notable aspect of their attacks involves creating new virtual machines in VMware vSphere and Microsoft Azure, using administrative permissions linked through SSO applications for further activities. The group uses commonly available utilities to reconfigure virtual machines (VMs), disable security protocols, and download tools such as Mimikatz and ADRecon, which extract and combine various artifacts from Active Directory (AD) and Microsoft Entra ID environments. Evolving Methods Initially, UNC3944 employed a variety of techniques, but over time, their methods have expanded to include ransomware and data theft extortion. Active since at least May 2022, the group has developed resilience mechanisms against virtualization platforms and improved their ability to move laterally by abusing SaaS permissions. The group also uses SMS phishing to reset passwords and bypass multi-factor authentication (MFA). Once inside, they conduct thorough reconnaissance of Microsoft applications like SharePoint to understand remote connection needs. According to Google Cloud’s Mandiant team, UNC3944’s primary activity is now data theft without using ransomware. They employ expert social engineering tactics, using detailed personal information to bypass identity checks and target employees with high-level access. Social Engineering and Threats Attackers often pose as employees, contacting help desks to request MFA resets for setting up new phones. If help desk staff comply, attackers can easily bypass MFA and reset passwords. If social engineering fails, UNC3944 resorts to threats, including doxxing, physical threats, or releasing compromising material to coerce credentials from victims. Once access is gained, they gather information on tools like VPNs, virtual desktops, and remote work utilities to maintain consistent access. Targeting SaaS and Cloud Platforms UNC3944 targets Okta’s single sign-on (SSO) tools, allowing them to create accounts that facilitate access to multiple systems. Their attacks extend to VMware’s vSphere hybrid cloud management tool and Microsoft Azure, where they create virtual machines for malicious purposes. By operating within a trusted IP address range, they complicate detection. Additional targets include SaaS applications like VMware’s vCenter, CyberArk, Salesforce, CrowdStrike, Amazon Web Services (AWS), and Google Cloud. Office 365 is another focus, with attackers using Microsoft’s Delve tool to identify valuable information. To exfiltrate data, they use synchronization utilities such as Airbyte and Fivetran to transfer information to their own cloud storage. The group also targets Active Directory Federation Services (ADFS) to extract certificates and employ Golden SAML attacks for continued access to cloud applications. They leverage Microsoft 365 capabilities like Office Delve for quick reconnaissance and data mining. Recommendations – Cyber Group Targets SaaS Platforms Mandiant advises deploying host-based certificates with MFA for VPN access, implementing stricter conditional access policies, and enhancing monitoring for SaaS applications. Consolidating logs from crucial SaaS applications and monitoring virtual machine setups can help identify potential breaches. 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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Salesforce and MySQL

Salesforce and MySQL

Salesforce CRM houses a wealth of customer data, encompassing interactions, leads, and purchase histories. However, without proper organization, these insights risk being lost in the shuffle. Get a handle on data with Salesforce and MySQL. MySQL, a free, open-source relational database management system (RDBMS) that acts as a digital filing cabinet for structured data, including customer information. Integrating Salesforce CRM with MySQL presents a compelling solution by establishing a seamless bridge between the two systems. This integration enables businesses to efficiently transfer customer data from Salesforce into MySQL, ensuring centralized, accessible, and analyzable data. Imagine having all customer data neatly organized within a single, searchable database, facilitating holistic insights that empower informed decision-making and personalized marketing campaigns. Let’s explore the significant benefits of integrating Salesforce CRM and MySQL, and how this synergy can revolutionize your business operations. Benefits of Integrating Salesforce CRM and MySQL How to Integrate Salesforce CRM and MySQL Integrating Salesforce CRM with MySQL involves leveraging Salesforce APIs for secure data communication and synchronization. Here’s a step-by-step approach: Common Challenges and Solutions Conclusion Integrating Salesforce CRM with MySQL represents a transformative approach to streamline data management and enhance operational efficiency. By combining Salesforce’s robust CRM capabilities with MySQL’s flexible database management, businesses can unlock real-time insights, improve customer engagement, and drive strategic growth initiatives seamlessly. Embrace the power of Salesforce CRM and MySQL integration to stay competitive in today’s data-driven landscape effortlessly. 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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Time to Reset AI Expectations

Time to Reset AI Expectations

AI is often portrayed as either the ultimate solution to all our problems or a looming threat that must be handled with extreme caution. These are the two polar extremes of a debate that surrounds any transformative technology, and the reality likely lies somewhere in the middle. Time to Reset AI Expectations. At the recent 2024 MIT Sloan CIO Symposium, AI was the central theme, with numerous keynotes and panels devoted to the topic. The event also featured informal roundtable discussions that touched on legal risks in AI deployment, AI as a driver for productivity, and the evolving role of humans in AI-augmented workplaces. Time to Reset AI Expectations A standout moment was the closing keynote, “What Works and Doesn’t Work with AI,” delivered by MIT professor emeritus Rodney Brooks. Brooks, who directed the MIT AI Lab from 1997 to 2003 and was the founding director of MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) until 2007, offered insights to distinguish between the hype and reality of AI. A seasoned robotics entrepreneur, Brooks founded several companies, including iRobot, Rethink Robotics, and Robust.AI. In his keynote, Brooks introduced his “Three Laws of Artificial Intelligence,” which serve to ground our understanding of AI: Brooks reminded the audience that AI has been a formal academic discipline since the 1950s when its pioneers believed that nearly every aspect of human intelligence could, in principle, be encoded as software and executed by increasingly powerful computers. Decades of Efforts In the 1980s, leading AI researchers were confident that within a generation, AI systems capable of human-like cognitive abilities could be developed. They secured government funding to pursue this vision. However, these projects underestimated the complexities of replicating human intelligence, particularly cognitive functions like language, thinking, and reasoning, in software. After years of unmet expectations, these ambitious projects were largely abandoned, leading to the so-called AI winter—a period of reduced interest and funding in AI. AI experienced a resurgence in the 1990s with a shift towards a statistical approach that analyzed patterns in vast amounts of data using sophisticated algorithms and high-performance supercomputers. This data-driven approach yielded results that approximated intelligence and scaled far better than the earlier programming-based models. Over the next few decades, AI achieved significant milestones, including Deep Blue’s 1997 victory over chess grandmaster Garry Kasparov, Watson’s 2011 win in the Jeopardy! Challenge, and AlphaGo’s 2016 triumph over Lee Sedol, one of the world’s top Go players. AI also made strides in autonomous vehicles, as evidenced by the successful completion of the 2007 DARPA Grand Challenge and the 2012 DARPA Robotics Challenge for disaster response robots. Is It Different Now? Following these achievements, AI seemed poised to “change everything,” according to Brooks. But is it really? Since 2017, Brooks has published an annual Predictions Scorecard, comparing predictions for future milestones in robotics, AI, machine learning, self-driving cars, and human space travel. “I made my predictions because, then as now, I saw an immense amount of hype surrounding these topics,” Brooks said. He observed that the media and public were making premature conclusions about the impact of AI on jobs, road safety, space exploration, and more. “My predictions, complete with timelines, were meant to temper expectations and inject some reality into what I saw as irrational exuberance.” So why have so many AI predictions missed the mark? Brooks, who has a penchant for lists, attributes this to what he calls the Seven Deadly Sins of Predicting the Future of AI. In a 2017 essay, he described these “sins”: The takeaway? While AI has made remarkable progress, there’s still a long journey ahead. It’s Time to Reset AI Expectations. 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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