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Autonomy, Architecture, and Action

Redefining AI Agents: Autonomy, Architecture, and Action AI agents are reshaping how technology interacts with us and executes tasks. Their mission? To reason, plan, and act independently—following instructions, making autonomous decisions, and completing actions, often without user involvement. These agents adapt to new information, adjust in real time, and pursue their objectives autonomously. This evolution in agentic AI is revolutionizing how goals are accomplished, ushering in a future of semi-autonomous technology. At their foundation, AI agents rely on one or more large language models (LLMs). However, designing agents is far more intricate than building chatbots or generative assistants. While traditional AI applications often depend on user-driven inputs—such as prompt engineering or active supervision—agents operate autonomously. Core Principles of Agentic AI Architectures To enable autonomous functionality, agentic AI systems must incorporate: Essential Infrastructure for AI Agents Building and deploying agentic AI systems requires robust software infrastructure that supports: Agent Development Made Easier with Langflow and Astra DB Langflow simplifies the development of agentic applications with its visual IDE. It integrates with Astra DB, which combines vector and graph capabilities for ultra-low latency data access. This synergy accelerates development by enabling: Transforming Autonomy into Action Agentic AI is fundamentally changing how tasks are executed by empowering systems to act autonomously. By leveraging platforms like Astra DB and Langflow, organizations can simplify agent design and deploy scalable, effective AI applications. Start building the next generation of AI-powered autonomy today. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Apple's Privacy Changes: A Call for Email Marketing Innovation

Liar Liar Apple on Fire

Apple Developing Update After AI System Generates Inaccurate News Summaries Apple is working on a software update to address inaccuracies generated by its Apple Intelligence system after multiple instances of false news summaries were reported. The BBC first alerted Apple in mid-December to significant errors in the system, including a fabricated summary that falsely attributed a statement to BBC News. The summary suggested Luigi Mangione, accused of killing United Healthcare CEO Brian Thompson, had shot himself, a claim entirely unsubstantiated. Other publishers, such as ProPublica, also raised concerns about Apple Intelligence producing misleading summaries. While Apple did not respond immediately to the BBC’s December report, it issued a statement after pressure mounted from groups like the National Union of Journalists and Reporters Without Borders, both of which called for the removal of Apple Intelligence. Apple assured stakeholders it is working to refine the technology. A Widespread AI Issue: Hallucinations Apple joins the ranks of other AI vendors struggling with generative AI hallucinations—instances where AI produces false or misleading information. In October 2024, Perplexity AI faced a lawsuit from Dow Jones & Co. and the New York Post over fabricated news content attributed to their publications. Similarly, Google had to improve its AI summaries after providing users with inaccurate information. On January 16, Apple temporarily disabled AI-generated summaries for news apps on iPhone, iPad, and Mac devices. The Core Problem: AI Hallucination Chirag Shah, a professor of Information Science at the University of Washington, emphasized that hallucination is inherent to the way large language models (LLMs) function. “The nature of AI models is to generate, synthesize, and summarize, which makes them prone to mistakes,” Shah explained. “This isn’t something you can debug easily—it’s intrinsic to how LLMs operate.” While Apple plans to introduce an update that clearly labels summaries as AI-generated, Shah believes this measure falls short. “Most people don’t understand how these headlines or summaries are created. The responsible approach is to pause the technology until it’s better understood and mitigation strategies are in place,” he said. Legal and Brand Implications for Apple The hallucinated summaries pose significant reputational and legal risks for Apple, according to Michael Bennett, an AI adviser at Northeastern University. Before launching Apple Intelligence, the company was perceived as lagging in the AI race. The release of this system was intended to position Apple as a leader. Instead, the inaccuracies have damaged its credibility. “This type of hallucinated summarization is both an embarrassment and a serious legal liability,” Bennett said. “These errors could form the basis for defamation claims, as Apple Intelligence misattributes false information to reputable news sources.” Bennett criticized Apple’s seemingly minimal response. “It’s surprising how casual Apple’s reaction has been. This is a major issue for their brand and could expose them to significant legal consequences,” he added. Opportunity for Publishers The incident highlights the need for publishers to protect their interests when partnering with AI vendors like Apple and Google. Publishers should demand stronger safeguards to prevent false attributions and negotiate new contractual clauses to minimize brand risk. “This is an opportunity for publishers to lead the charge, pushing AI companies to refine their models or stop attributing false summaries to news sources,” Bennett said. He suggested legal action as a potential recourse if vendors fail to address these issues. Potential Regulatory Action The Federal Trade Commission (FTC) may also scrutinize the issue, as consumers paying for products like iPhones with AI capabilities could argue they are not receiving the promised service. However, Bennett believes Apple will likely act to resolve the problem before regulatory involvement becomes necessary. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Salesforce Einstein Commerce

Salesforce Commerce Cloud Passkeys

Adding Passkeys to Salesforce Commerce Cloud Ensuring secure, convenient user access is a top priority for Salesforce-based applications. Passkeys, a passwordless authentication solution, streamline user sign-up and login processes while enhancing security. By integrating passkeys into Salesforce Commerce Cloud (SFCC), businesses can protect users from password-related threats like phishing and credential theft, leveraging the security of asymmetric encryption behind passkeys. The seamless login experience offered by passkeys boosts user engagement, reduces drop-off rates, and fosters trust, improving overall user satisfaction. Implementing passkeys not only aligns with current security standards but also prepares businesses for the future of intuitive digital interactions and enhanced privacy. DIY Implementation vs. Dedicated Salesforce Commerce Cloud Passkey Solution When deciding how to integrate passkeys into Salesforce Commerce Cloud applications, businesses must weigh the options between a DIY approach and partnering with a dedicated solution provider like OwnID. Implementing passkeys from scratch can be time-consuming and resource-intensive, requiring significant technical effort to ensure compatibility with Salesforce systems and adherence to security and user experience best practices. By choosing a provider like OwnID, companies can implement passkeys in a matter of days rather than months. OwnID offers a ready-to-use, Salesforce-compatible solution that integrates seamlessly, features cutting-edge security, and provides ongoing support. This approach lifts the burden from internal development teams, speeds up deployment, and ensures a high-quality user experience without the need to manage authentication processes or stay on top of compliance updates. For more information, check out our DIY vs. Elite Passkey Implementation Guide. How to Implement the OwnID Solution in Salesforce Commerce Cloud Integrating OwnID’s passwordless login into Salesforce Commerce Cloud (SFCC) is a straightforward process that enhances both security and the user experience. Here’s an overview of the key steps involved: 1. Set Up an API Client in SFCC Begin by creating a new API Client in your SFCC environment. This client is essential for secure communication between SFCC and OwnID. Log into the Salesforce Commerce Cloud Account Manager, add a new API Client, and configure the appropriate roles and authentication methods (e.g., private_key_jwt). This step ensures secure integration between SFCC and OwnID. 2. Create and Configure an OwnID Application In the OwnID Console, set up an application dedicated to your SFCC integration. This application serves as the bridge between OwnID’s passkey system and your Salesforce Commerce Cloud app. Configure settings like API credentials, site URL, and other parameters specific to OwnID. This step connects OwnID’s authentication service to your Salesforce site seamlessly. 3. Install the OwnID Cartridge in SFCC OwnID provides a cartridge designed for SFCC integration. Installing this cartridge adds all necessary components to your SFCC instance, enabling easy interaction between OwnID and Salesforce. After installation, go to Merchant Tools → Site Preferences in SFCC to customize OwnID settings for your environment. This enables you to display the OwnID widget on login and registration pages, creating a smooth, passwordless experience. 4. Embed the OwnID SDK in Your Templates The final step is to embed the OwnID SDK script in your site’s templates (e.g., htmlHead.isml or a global template file). This SDK enables passkey-based login across all relevant pages. By embedding the script, you ensure users have access to passwordless login, enhancing security and user convenience. With these steps, OwnID will be fully integrated into your Salesforce Commerce Cloud application, offering users secure, password-free access. For more detailed instructions and configuration options, visit the OwnID Salesforce Commerce Cloud Documentation. Get Expert Help with Your Salesforce Commerce Cloud Passkey Integration Ready to implement passwordless authentication in your Salesforce Commerce Cloud application? The Tectonic team is here to guide you through every step of the integration process. From initial setup to ongoing optimization, we ensure a smooth and seamless experience for your users. For personalized support and to learn how OwnID’s passkey solution can elevate your SFCC environment, contact our expert team today. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Scope of Generative AI

Exploring Generative AI

Like most employees at most companies, I wear a few different hats around Tectonic. Whether I’m building a data model, creating and scheduing an email campaign, standing up a platform generative AI is always at my fingertips. At my very core, I’m a marketer. Have been for so long I do it without eveven thinking. Or at least, everyuthing I do has a hat tip to its future marketing needs. Today I want to share some of the AI content generators I’ve been using, am looking to use, or just heard about. But before we rip into the insight, here’s a primer. Types of AI Content Generators ChatGPT, a powerful AI chatbot, drew significant attention upon its November 2022 release. While the GPT-3 language model behind it had existed for some time, ChatGPT made this technology accessible to nontechnical users, showcasing how AI can generate content. Over two years later, numerous AI content generators have emerged to cater to diverse use cases. This rapid development raises questions about the technology’s impact on work. Schools are grappling with fears of plagiarism, while others are embracing AI. Legal debates about copyright and digital media authenticity continue. President Joe Biden’s October 2023 executive order addressed AI’s risks and opportunities in areas like education, workforce, and consumer privacy, underscoring generative AI’s transformative potential. What is AI-Generated Content? AI-generated content, also known as generative AI, refers to algorithms that automatically create new content across digital media. These algorithms are trained on extensive datasets and require minimal user input to produce novel outputs. For instance, ChatGPT sets a standard for AI-generated content. Based on GPT-4o, it processes text, images, and audio, offering natural language and multimodal capabilities. Many other generative AI tools operate similarly, leveraging large language models (LLMs) and multimodal frameworks to create diverse outputs. What are the Different Types of AI-Generated Content? AI-generated content spans multiple media types: Despite their varied outputs, most generative AI systems are built on advanced LLMs like GPT-4 and Google Gemini. These multimodal models process and generate content across multiple formats, with enhanced capabilities evolving over time. How Generative AI is Used Generative AI applications span industries: These tools often combine outputs from various media for complex, multifaceted projects. AI Content Generators AI content generators exist across various media. Below are good examples organized by gen ai type: Written Content Generators Image Content Generators Music Content Generators Code Content Generators Other AI Content Generators These tools showcase how AI-powered content generation is revolutionizing industries, making content creation faster and more accessible. I do hope you will comment below on your favorites, other AI tools not showcased above, or anything else AI-related that is on your mind. Written by Tectonic’s Marketing Operations Director, Shannan Hearne. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Marketing Cloud Connect

Marketing Cloud Connect Entry Data

If you’re a Marketing Cloud Connect customer that uses Salesforce data entry in your journeys, you can identify and act on journeys that are close to meeting the Apex limit of journeys per object.  On the Journeys Dashboard, select filters to see all journeys that use a Salesforce Data Entry event. Apply a subfilter to see journeys within a specific standard or custom object. What is entry data in Journey Builder? The entry source on the canvas tells Journey Builder where customers entering this journey come from. Each journey must include an entry source. Important Don’t modify a data extension that is used as the entry source in an active journey. When activated, the journey uses a snapshot of the entry source data extension. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Rise of Agentforce

How Agentforce Augments Marketing Cloud

Key Features of Salesforce Agentforce for Marketing and Marketers AI-Powered Assistance: Agentforce leverages AI to automate and optimize marketing tasks, allowing your team to focus on strategic initiatives. From generating campaign plans to analyzing metrics, Agentforce acts as your trusted assistant working around the clock with nary a coffee break. Omnichannel Support: Engage with customers across multiple platforms, including email, social media, and messaging apps like WhatsApp. Agentforce ensures a consistent and personalized experience at every touchpoint. Recognizing your prospect and customer throughout every interaction. Real-Time Analytics and Reporting: Gain in-depth insights into your marketing performance with real-time analytics. Agentforce helps you track key metrics and make data-driven decisions to improve your campaigns. Integration with Salesforce CRM: Seamlessly connect Agentforce with your existing Salesforce CRM to leverage customer data and create more targeted and effective marketing strategies. Proactive Customer Engagement: Agentforce enables personalized, two-way conversations with customers, helping you build deeper relationships and reduce churn through proactive retention strategies. Added Value of Integrating Agentforce with Salesforce Marketing Cloud The integration of Agentforce with the Salesforce Marketing Cloud platform, whether you choose the Growth or Advanced edition, brings several benefits: Enhanced Personalization: With the power of AI and unified customer profiles, you can deliver highly personalized content and offers across every customer interaction. Scalability and Efficiency: The Growth edition supports companies looking to scale their marketing efforts with powerful data tools and content management features. The Advanced edition offers additional tools for deeper insights and more sophisticated customer engagement strategies. Seamless Campaign Management: Both editions provide tools to create, deploy, and adapt campaigns faster, with Agentforce helping to surface insights, define strategy, and generate content. Improved Customer Journeys: Use intelligent reprioritization and real-time interaction management to enhance customer journeys and drive better engagement. Elevating Customer Experience with AI-Powered Marketing Offering a great product or service is important—but have you considered how your customers feel when they engage with your brand? Beyond features and pricing, the real differentiator is the experience you create. How the customer experiences your company can be more impactful than how they experience your product or service. Salesforce research reveals that 80% of customers value their experience with a company as much as the products or services themselves. It’s not just about what you have to offer; it’s about how you make people feel at every interaction. Because in today’s competitive marketplace, customers don’t just buy products—they invest in experiences. In the go-to-market space, Salesforce Agentforce is redefining the Marketing Cloud experience by making customer interactions more intelligent, personalized, and human-like than ever before—all powered by AI. Imagine a marketing strategy where every interaction—every click, every purchase—delivers actionable insights instead of guesswork. This is the future of AI-driven marketing. In fact, recent research found that nearly half (46%) of financial services firms leveraging AI report enhanced customer experiences. With AI-driven automation, conversational intelligence, and predictive analytics, Agentforce helps businesses engage customers at the right time, in the right way, and on the right platform—building deeper, more meaningful relationships. Salesforce’s Ongoing Relationship with Data Since pioneering cloud-based CRM in 1999, Salesforce has been relentless in its pursuit of data-driven experiences. Over time, its capabilities have expanded far beyond traditional CRM, culminating in the Salesforce Data Cloud—a unified data platform that consolidates insights across Sales, Service, Commerce, and Marketing. Data, especially the data we use for ongoing marketing, lives in various platforms like email, advertising tools, social media, analytics, CRMs, and perhaps even spreadsheets. And it is completely unstructured. What began as a Data Management Platform has evolved into a real-time decision-making engine. By integrating Agentforce AI, Data Cloud moves beyond just storing information—it enables businesses to act on real-time insights with automation and intelligence that move deals closer to the goalpost. Meet Agentforce: Humanizing AI in Marketing Cloud At the heart of AI-driven marketing transformation is quality data—which is why Einstein AI is built on Salesforce Data Cloud. “AI is only as good as the data that powers it, and Salesforce is where thousands of companies across industries manage their sales, service, marketing, commerce, and IT data,” says Jayesh Govindarajan, Salesforce SVP of AI & Machine Learning. “That’s an advantage for Salesforce customers because they can use their existing data to create and deliver AI-generated content at scale, seamlessly within their current workflows.” With Agentforce, businesses go beyond access to data—they gain an AI partner that understands how to foster authentic customer connections. How AI is Humanizing the Marketing Experience Instead of generic messaging, Agentforce crafts and delivers hyper-personalized content, offers, and recommendations—at scale. The Future of AI-Driven Marketing is Here With Agentforce, Salesforce Data Cloud, and Einstein GPT, businesses can move beyond static campaigns and embrace dynamic, AI-driven experiences that feel authentic, intuitive, and deeply personal. The next era of marketing isn’t just about automation—it’s about delivering humanized AI experiences that drive lasting customer relationships. The evolution of Einstein, GPT, AI, and Data on top of a powerful marketing platform is the future of AI-driven marketing. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Autonomous AI Service Agents

How Do Autonomous Agents Work?

Autonomous agents like Florida Bay’s understand and respond to requests, and then act without human intervention. Give the agent a goal, and it generates tasks for itself, completes them, and moves on to the next one until the goal is achieved. Unlike traditional chatbots that follow predefined rules, autonomous agents operate in dynamic environments, making them perfect for complex tasks in customer service, marketing, commerce, sales, and more. While autonomous agents don’t need human help to complete their tasks, they still need you to describe the ideal goals and main objectives you want to achieve. Once in action, the agent can save your business significant time and resources and allow you to focus on improving the overall customer experience and driving growth–just like at Florida Bay. You might think setting up an agent takes a lot of time, but autonomous agents‌ require less time to build compared with traditional bots. And they can do more when you set them up with the right data and actions. Let’s take a look at the key components that make them effective. Data Data is the foundation of an autonomous agent‘s functionality. It’s what enables an agent to make informed decisions and execute tasks autonomously. At Florida Bay, the concierge agent analyzes opt-in data about the Smith family, including family member profiles, past travel history, and more, to gain a deeper understanding of their preferences. With these insights, the agent can personalize every aspect of their trip and provide a seamless and enjoyable vacation. Decision-Making When an autonomous agent analyzes data, it uses advanced decision-making algorithms to prioritize and execute tasks efficiently. For the concierge agent at Florida Bay, that means evaluating various options and scenarios to ensure that every decision aligns with the Smith family’s preferences and goals. Action Execution After making data-driven decisions, the agent seamlessly transitions to executing the planned actions. For the concierge agent, those planned actions might be autonomously reserving hotel rooms, arranging transportation, and more. This not only enhances the customer experience but also allows the business to save an immense amount of time and focus on other critical tasks that provide even better customer service. Learning and Adaptation Over time, the agent continuously learns from each interaction and adapts to improve future performance. It analyzes feedback and outcomes to refine its algorithms and decision-making processes to better meet the customer’s needs. In addition, autonomous agents are adaptable to various situations and can provide data-driven solutions to simplify and improve efficiency in a wide range of areas. Let’s take a look at that next. Autonomous Agents in Action Autonomous agents are becoming increasingly universal and offer support in a wide range of fields. Here are some industries where they bring significant benefits and support to CRM platforms. Healthcare An autonomous agent can engage with patients, providers, and payers to resolve inquiries, provide summaries, and take action. For example, a patient services agent can answer simple patient questions, help schedule appointments with the best physician, review coverage benefits, generate medical history summaries, and approve care requests. Example: A patient needs to schedule a follow-up appointment with a specialist. They use the healthcare provider’s agent to request the appointment. The autonomous agent checks the availability of the best-suited specialist, confirms the patient’s insurance coverage, and schedules the appointment. The agent also generates a summary of the patient’s medical history and sends it to the specialist in advance. This streamlined process ensures that the patient receives timely care and reduces the administrative burden on healthcare staff. Financial Services Banks can autonomously manage transaction disputes through various channels such as the banking app, SMS, website, or phone. Prebuilt service flows allow agents to file complaints, meet regulatory reporting requirements, verify transaction history, alert merchants, and even issue provisional credits or new cards. These autonomous agents only escalate to a human for final authorizations, saving time and allowing human experts to focus on more complex interactions. Example: A customer notices a fraudulent transaction on their bank statement and reports it through the banking app. The autonomous agent verifies the transaction history, files the complaint, and issues a provisional credit to the customer’s account. The agent also alerts the merchant and schedules a follow-up with a human representative for final authorization. This process, which used to take several days, is now completed within hours, significantly improving customer satisfaction and reducing the workload on human service reps. Insurance Insurance companies can autonomously update coverage, extend better pricing to qualified policyholders, update beneficiaries, schedule and deploy claims adjusters, and even issue claims checks or policy renewals—all without human intervention. Wealth advisors reported that 67% of their daily work is non–value-added administrative work. Autonomous agents can reduce this by planning, scheduling, and summarizing client meetings, drafting client communications, and ensuring compliance by routing communications to the proper licensed supervisors. Example: An insurance policyholder wants to update their beneficiary information. They use the insurance company’s mobile app to make the change. The autonomous agent verifies the policyholder’s identity, updates the beneficiary’s information, and sends a confirmation email. The agent also ensures that the change is compliant with regulatory requirements by routing the communication to a licensed supervisor for a final review. This process, which previously required a phone call and manual processing, is now completed in seconds, freeing up the policyholder’s time and reducing administrative workload. Retail Autonomous agents can share campaign insights, proactively manage customer outreach, and resolve cases for retailers. A personal shopper autonomous agent acts like a digital concierge for online shoppers, using generative AI to help customers on ecommerce sites, chat, or messaging apps like WhatsApp. While basic chatbots only solve predefined questions, autonomous AI agents learn from shoppers’ behavior and preferences and can provide natural language searches, conversational responses, and quick cart additions for instant checkout. Example: A customer is shopping for a new pair of shoes on an ecommerce site. The personal shopper autonomous agent, integrated into the chat feature, engages with the customer and analyzes their past purchases and preferences.

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AI Captivates the World

AI Captivates the World

In the late 1990s, a transformative moment unfolded that expanded the world to enquiring minds—the screeching of a dial-up modem, followed by a pixelated “Welcome” screen that connected users to a vast, invisible network spanning the globe. The internet revolution redefined how people interacted with information and one another, permanently reshaping digital communication. Fast forward to 2024, and a similar wave of innovation is underway. Artificial intelligence is captivating the world with its ability to understand, create, and process information. Massive datasets can now be uploaded to AI tools, which instantly distill complex insights—tasks that once took teams of analysts weeks to complete are now executed in seconds. Just as the internet linked people and information, AI is deepening connectivity across all aspects of life, from healthcare and finance to workplaces and homes. In this evolving digital divide, designers hold a critical role—not only in making AI usable but in ensuring it remains understandable, trustworthy, and human-centered. As Fei-Fei Li, Co-Director of Stanford’s Human-Centered AI Institute, states, “If we want machines to think, we need to teach them to see.” The traditional linear process of problem ideation, design, prototyping, and delivery is no longer sufficient for AI design. Instead, designers find themselves on an “AI design rollercoaster”—a dynamic cycle of constant iteration. One day, a seemingly impossible feature is prototyped, and the next, the entire approach pivots due to breakthroughs in large language model (LLM) capabilities. Many teams develop working prototypes before even defining their target audience. It is akin to painting a landscape from a moving train—compelling, challenging, and occasionally bewildering. However, this state of flux is where innovation thrives. Strategies for Designers: Understanding AI’s Capabilities and Limitations Designing for AI requires an understanding of its strengths and weaknesses. While designers do not need to become machine learning engineers, they must grasp AI fundamentals to communicate effectively with technical teams. For example, neural networks excel at recognizing patterns in unstructured data but often struggle with logical reasoning. Recognizing these limitations prevents the development of features that sound promising in theory but fail in practice. Strategies for Designers: Designing for Data Scalability Data is the lifeblood of AI systems, yet its quality and availability fluctuate over time. Designers must create interfaces that can adapt to changing data landscapes. For instance, an AI-powered personal finance app may initially rely on basic transaction data but later incorporate richer datasets for advanced investment recommendations. Interfaces should be modular and scalable, capable of accommodating evolving AI functionalities. Strategies for Designers: The Role of Prototyping in AI Design Static wireframes and basic mockups are insufficient for AI-driven products. AI prototypes must capture the responsive, dynamic nature of intelligent systems. Interactive prototypes offer stakeholders a tangible preview of AI’s potential, highlighting both opportunities and challenges early in the design process. Strategies for Designers: Developing AI Design Intuition To navigate AI design effectively, professionals must cultivate an “AI design sixth sense”—an intuitive understanding of what works well in AI-driven interactions. Immersing in AI experiences, exploring different tools, and analyzing emerging design patterns help build this expertise. Strategies for Designers: Pushing Boundaries in AI Design There are no established rulebooks for AI design—only a vast frontier waiting to be explored. The absence of rigid norms offers designers the freedom to experiment and push boundaries. Some of the most groundbreaking innovations stem from unconventional ideas once deemed impractical. Strategies for Designers: Strengthening Collaboration Between Design and Engineering In AI product design, the traditional “design then handoff” model is giving way to a more integrated approach. Designers and engineers increasingly work in tandem, refining AI experiences through continuous iteration. Some of the most effective design solutions emerge from close collaboration with technical teams. Strategies for Designers: The Next Frontier of Design As AI design continues to evolve, the parallels to the early days of the internet are striking. The excitement, potential, and magnitude of change are reminiscent of Web 1.0, yet amplified in scope. Looking ahead, the field must address profound questions: Will AI become indistinguishable from human intelligence? Will designers craft interfaces for AI-human hybrids yet to be imagined? Designers play an essential role in shaping this future—not as passive observers, but as architects of the next digital revolution. The experiences they create will define humanity’s interactions with artificial intelligence. This responsibility should inspire innovation, challenge conventions, and push the boundaries of what is possible. Call to Action Begin the AI design journey today. Choose an AI tool, explore its interface, and analyze its capabilities. Identify strengths, weaknesses, and opportunities for improvement. Share insights with fellow designers and contribute to the evolving conversation on AI design. The next breakthrough may arise from a single moment of curiosity. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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user q and a

Marketing Cloud Engagement Send Times

How do I ensure emails from Marketing Cloud Engagement go to my recipients in the correct time zone? To configure a user’s time zone in Marketing Cloud Engagement, navigate to Setup > Users > [Select User] > Edit, and then select the desired time zone from the “Time Zone” dropdown menu within the “Locale Settings” section; this will update the user’s interface to display times according to their chosen time zone.  Key points to remember: If you need assistance configuring this in Marketing Cloud Engagement, contact Tectonic today. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Salesforce Business Automation

Streamlining Business Automation: A Guide to Successful Salesforce Implementation Salesforce is a lightning jolt for business automation, offering powerful tools to enhance efficiency and productivity. However, implementing Salesforce is a complex process that requires strategic planning and execution. This insight will walk you through best practices for Salesforce implementation, helping you avoid common pitfalls and maximize the platform’s benefits. From defining clear business objectives to post-implementation performance measurement, we’ve got you covered. Understanding Salesforce Implementation Implementing Salesforce is more than simply installing software—it’s a strategic process that must align with your business goals. Successful implementation requires understanding each critical phase, including: Each phase builds toward a solution that drives operational improvements and delivers measurable results. The Role of Salesforce in Business Automation Salesforce transforms business processes by automating repetitive tasks, integrating workflows, and providing real-time analytics. These capabilities empower teams to focus on strategic activities, fostering growth and improving customer engagement. The platform’s automation features enhance decision-making, streamline operations, and deliver actionable insights, making it an essential tool for any data-driven organization. Best Practices for Salesforce Implementation 1. Define Clear Business Objectives Set specific, measurable, and strategic goals that Salesforce can address. Identify business challenges and align objectives with user needs to ensure widespread adoption and long-term success. 2. Conduct a Thorough Needs Analysis Analyze existing processes, identify gaps, and engage stakeholders to gather input. A detailed needs analysis ensures Salesforce is configured to address real pain points and deliver value. 3. Develop a Comprehensive Roadmap Create an implementation roadmap outlining timelines, responsibilities, resources, and risk mitigation strategies. A clear roadmap keeps the project on track and fosters effective communication. 4. Prioritize Data Quality and Governance Start by cleansing existing data to remove inaccuracies and duplicates. Implement governance policies to maintain data integrity, ensuring Salesforce delivers accurate insights. 5. Customize Thoughtfully Tailor Salesforce to enhance existing workflows rather than disrupting them. Engage users to understand their needs and avoid unnecessary complexity that could hinder usability or future updates. 6. Engage Certified Salesforce Partners Collaborate with experienced Salesforce partners to leverage best practices, avoid common pitfalls, and tailor the platform to your unique requirements. The Importance of User Adoption and Training User adoption is crucial for Salesforce’s success. Engage end-users early, involve them in the process, and provide tailored, hands-on training. Post-launch, offer continuous support and advanced training to help users unlock Salesforce’s full potential. Strategies to maximize adoption include: Post-Implementation Success Once Salesforce is live, focus on monitoring performance, gathering feedback, and fostering continuous improvement. 1. Measure Success with KPIs Track key performance indicators (KPIs) to evaluate Salesforce’s impact on your business objectives. Identify trends, address challenges, and ensure the platform remains aligned with your goals. 2. Establish a Feedback Mechanism Encourage users to share feedback and suggest improvements. Regularly review input to refine the system and ensure it evolves with your organization’s needs. 3. Provide Ongoing Support Maintain a dedicated support team to address queries and troubleshoot issues promptly. Continuous training sessions keep users updated and confident in leveraging new features. Avoiding Common Pitfalls Awareness of potential challenges can help you mitigate risks. Common pitfalls to avoid include: By addressing these challenges proactively, you set your Salesforce implementation up for success. Embracing the Salesforce Journey Implementing Salesforce is a transformative opportunity for your business. With strategic planning, stakeholder engagement, and a commitment to continuous improvement, Salesforce can revolutionize your operations. If you’re seeking a streamlined solution, consider leveraging tools like Sweep, an AI-powered visual workspace that simplifies Salesforce implementation. With Sweep’s no-code interface, you can design processes, customize fields, and automate workflows effortlessly. Ready to transform your business with Salesforce?Connect with our experts today and unlock the full potential of Salesforce for your organization. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Marketing Cloud Account Engagement Send Times

Scheduled email sends are going out of Marketing Cloud at unexpected hours. Can this be fixed? To configure a user’s time zone in Marketing Cloud, navigate to Setup > Users > [Select User] > Edit, and then select the desired time zone from the “Time Zone” dropdown menu within the “Locale Settings” section; this will update the user’s interface to display times according to their chosen time zone.  Key points to remember: Please don’t hesitate to reach out to Tectonic if you need assistance configuring, have additional concerns, or just want to make Marketing Cloud greater. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Why Build a General-Purpose Agent?

A general-purpose LLM agent serves as an excellent starting point for prototyping use cases and establishing the foundation for a custom agentic architecture tailored to your needs. What is an LLM Agent? An LLM (Large Language Model) agent is a program where execution logic is governed by the underlying model. Unlike approaches such as few-shot prompting or fixed workflows, LLM agents adapt dynamically. They can determine which tools to use (e.g., web search or code execution), how to use them, and iterate based on results. This adaptability enables handling diverse tasks with minimal configuration. Agentic Architectures Explained:Agentic systems range from the reliability of fixed workflows to the flexibility of autonomous agents. For instance: Your architecture choice will depend on the desired balance between reliability and flexibility for your use case. Building a General-Purpose LLM Agent Step 1: Select the Right LLM Choosing the right model is critical for performance. Evaluate based on: Model Recommendations (as of now): For simpler use cases, smaller models running locally can also be effective, but with limited functionality. Step 2: Define the Agent’s Control Logic The system prompt differentiates an LLM agent from a standalone model. This prompt contains rules, instructions, and structures that guide the agent’s behavior. Common Agentic Patterns: Starting with ReAct or Plan-then-Execute patterns is recommended for general-purpose agents. Step 3: Define the Agent’s Core Instructions To optimize the agent’s behavior, clearly define its features and constraints in the system prompt: Example Instructions: Step 4: Define and Optimize Core Tools Tools expand an agent’s capabilities. Common tools include: For each tool, define: Example: Implementing an Arxiv API tool for scientific queries. Step 5: Memory Handling Strategy Since LLMs have limited memory (context window), a strategy is necessary to manage past interactions. Common approaches include: For personalization, long-term memory can store user preferences or critical information. Step 6: Parse the Agent’s Output To make raw LLM outputs actionable, implement a parser to convert outputs into a structured format like JSON. Structured outputs simplify execution and ensure consistency. Step 7: Orchestrate the Agent’s Workflow Define orchestration logic to handle the agent’s next steps after receiving an output: Example Orchestration Code: pythonCopy codedef orchestrator(llm_agent, llm_output, tools, user_query): while True: action = llm_output.get(“action”) if action == “tool_call”: tool_name = llm_output.get(“tool_name”) tool_params = llm_output.get(“tool_params”, {}) if tool_name in tools: try: tool_result = tools[tool_name](**tool_params) llm_output = llm_agent({“tool_output”: tool_result}) except Exception as e: return f”Error executing tool ‘{tool_name}’: {str(e)}” else: return f”Error: Tool ‘{tool_name}’ not found.” elif action == “return_answer”: return llm_output.get(“answer”, “No answer provided.”) else: return “Error: Unrecognized action type from LLM output.” This orchestration ensures seamless interaction between tools, memory, and user queries. When to Consider Multi-Agent Systems A single-agent setup works well for prototyping but may hit limits with complex workflows or extensive toolsets. Multi-agent architectures can: Starting with a single agent helps refine workflows, identify bottlenecks, and scale effectively. By following these steps, you’ll have a versatile system capable of handling diverse use cases, from competitive analysis to automating workflows. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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