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When Will Quantum Computing Be Ready?

When Will Quantum Computing Be Ready?

When Will Quantum Computing Be Ready? The Answer Is More Complex Than You Think Quantum computing doesn’t have a single “launch date”—it’s arriving in stages, with different milestones depending on how you define “availability.” The Quantum Computing Landscape Today Right now, hundreds of quantum computers exist worldwide, deployed by companies like IBM, D-Wave, IonQ, and Quantinuum. They’re accessible via: But today’s quantum machines are mostly used for research, experimentation, and skill-building—not yet for real-world commercial advantage. The Quantum Readiness Spectrum: 4 Key Milestones 1️⃣ Quantum Supremacy (Achieved in Niche Cases) 2️⃣ Quantum Economic Advantage (2025-2027) 3️⃣ Quantum Computational Advantage (2028-2030+) 4️⃣ Quantum Practicality (Ongoing Adoption) What’s Accelerating (or Slowing) Quantum’s Progress? ✅ Positive Signs ⚠️ Remaining Challenges The Bottom Line: When Should Businesses Prepare? 🔹 Now: Experiment with cloud-based quantum access (IBM, AWS, Azure).🔹 2025-2027: Watch for quantum economic advantage in optimization, chemistry, and AI.🔹 2030+: Expect broad commercial impact in finance, logistics, and materials science. “Quantum computing won’t arrive with a bang—it’ll seep into industries, one breakthrough at a time.”— McKinsey Quantum Research, 2024 Want to stay ahead? Start piloting quantum use cases today—before your competitors do. 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

The AI Agent Revolution

The AI Agent Revolution: How Tectonic is Unifying Disparate AI Systems for Enterprises AI agents are proliferating at breakneck speed—embedded in platforms, deployed as standalone apps, and built on proprietary or open-source SDKs. Yet as these intelligent systems multiply, enterprises face a critical challenge: getting them to communicate, collaborate, and scale effectively across complex IT environments. Recent moves by Tectonic, Salesforce, and Google Cloud highlight the next frontier of enterprise AI: seamless, cross-platform agent orchestration. We’ve reached an inflection point where human-AI synergy can transform business operations—but only if organizations can unify their agent ecosystems. The AI Agent Collaboration Challenge Today’s enterprises use AI agents for:✔ Salesforce’s Agentforce (CRM automation)✔ Google’s Agentspace (cloud-based workflows)✔ Custom agents (built on Vertex AI, OpenAI, or open-source models) But without interoperability, these agents operate in silos—limiting their potential. Tectonic bridges this gap with secure, enterprise-grade agent orchestration, enabling businesses to: Tectonic and Supported Agent OS: The Glue Holding AI Ecosystems Together Tectonic and Agent Operating Systems (OS) are business-focused platform for orchestrating AI agents across enterprise environments. An “agent operating system” (AOS) is a type of operating system designed to facilitate the development, deployment, and management of AI agents, which are software systems that can act autonomously to achieve goals. AOS systems aim to provide a platform for AI agents to operate efficiently and effectively, offering features like resource management, context switching, and tool integration. AIOS, for example, is a particular implementation of this concept that aims to address the challenges of managing large language model (LLM)-based AI agents How It Works Real-World Use Cases 1. Salesforce + Google Gemini: Smarter CRM Salesforce’s Agentforce now integrates Google Gemini, enabling:🔹 Better RAG (Retrieval-Augmented Generation) for faster, more accurate customer responses🔹 Predictive trend analysis embedded directly in CRM workflows Tectonic’s Role: Deploys multi-agent solutions that turn AI insights into actionable items—like auto-recommending next steps for sales teams. 2. Retail: Unified Customer Experiences A retailer combines: Result: Customers get instant, accurate updates on orders—no manual backend checks required. 3. Financial Services: AI-Powered Risk Analysis Banks use: Outcome: Suspicious transactions trigger automated compliance workflows without leaving Salesforce. Tectonic’s AI Activation Path: From Pilot to Production For enterprises ready to scale AI agents, Tectonic offers a rapid deployment framework:✅ Discovery and Road Mapping – Co-design high-impact use cases✅ Rapid Implementation – Deploy working agents in sandbox environments✅ Pre-Built Industry Libraries – Accelerate time-to-value The Future: Harmonized AI Ecosystems The biggest barrier to AI adoption isn’t technology—it’s fragmentation. With the Agent OS in place, businesses can finally:✔ Break down silos between Salesforce, Google Cloud, and custom AI✔ Automate complex workflows end-to-end✔ Scale AI responsibly with enterprise-grade governance The bottom line? AI agents are powerful alone—but unstoppable when unified. Ready to orchestrate your AI ecosystem?Discover how Tectonic’s Agentforce approach can transform your enterprise AI strategy. 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 Anywhere

Salesforce Anywhere

Salesforce Anywhere: The Future of Remote Collaboration The New Era of Distributed Work Modern businesses rely on remote teams to drive productivity and growth. Salesforce Anywhere redefines remote collaboration by integrating powerful communication, file-sharing, and project management tools directly into Salesforce—keeping teams connected, customers engaged, and workflows streamlined—all from a single platform. Why Remote Teams Need Salesforce Anywhere Remote work introduces challenges that hinder productivity:❌ Scattered communications – Delayed responses, lost messages❌ Disconnected workflows – Manual updates, switching between tools❌ Low visibility – Missed deadlines, stagnant deals❌ Security risks – Data leaks from unsecured file-sharing Salesforce Anywhere solves these problems by unifying collaboration within Salesforce, so teams can:✔ Chat, share files, and track projects without leaving CRM records✔ Automate repetitive tasks to focus on high-value work✔ Get AI-powered alerts to prevent missed opportunities✔ Integrate with Slack, Teams, and Google Workspace for seamless workflows Key Features for Remote Productivity 1. Centralized Document & File Sharing Problem: Files scattered across email, cloud drives, and messaging apps slow down work.Solution: Business Impact:🔹 No more lost files or duplicate versions🔹 Faster access to critical documents🔹 Secure sharing without external tools 2. Workflow Automation Problem: Manual follow-ups, approvals, and task assignments waste time.Solution: Business Impact:🔹 30-50% faster deal progression🔹 Fewer missed follow-ups🔹 Reduced administrative workload 3. AI-Powered Alerts & Insights Problem: Remote teams miss critical signals (stagnant deals, unhappy customers).Solution: Business Impact:🔹 Proactive issue resolution🔹 Higher customer retention🔹 Better project on-time delivery 4. Seamless Tool Integrations Problem: Constant app-switching kills productivity.Solution: Business Impact:🔹 40% less time wasted switching apps🔹 Unified communication history🔹 Fewer missed updates Business Benefits at a Glance Challenge Salesforce Anywhere Solution Outcome Disconnected teams Real-time chat & file-sharing in CRM Stronger collaboration Manual workflows Automated task assignments Faster execution Missed insights AI-driven alerts Smarter decisions Tool fragmentation Slack/Teams/Google integrations Streamlined work Data security risks Enterprise-grade encryption Protected information Best Practices for Implementation The Bottom Line Salesforce Anywhere isn’t just another collaboration tool—it’s the only platform that embeds teamwork directly into your CRM. By eliminating app-switching, automating busywork, and surfacing AI-driven insights, it helps remote teams work faster, smarter, and more securely—all while strengthening customer relationships. 🚀 Ready to transform remote work? Get started with Salesforce Anywhere 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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What is Up with Salesforce Analytics?

What is Up with Salesforce Analytics?

Tableau/CRM Analytics, Tableau Next, and Marketing Intelligence represent different facets of a unified analytics platform built on the Salesforce ecosystem. They offer various levels of integration and AI-driven capabilities for data analysis and insights, catering to diverse user needs within organizations.  Let’s break it down: Tableau/CRM Analytics (formerly Einstein Analytics): Tableau Next: Marketing Intelligence: Relationship and Integration: In essence, Tableau/CRM Analytics provides a foundational layer for CRM-specific analytics, while Tableau Next and Marketing Intelligence build upon that foundation to offer more advanced and AI-driven insights across the entire organization, according to Salesforce.  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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Expanded Availability of Marketing Cloud Growth and Advanced

Expanded Availability of Marketing Cloud Growth and Advanced

What the Expanded Global Availability of Marketing Cloud Growth and Advanced Editions Means for You Salesforce is bringing more power, more reach, and more connections to marketers around the globe. Since the debut of Marketing Cloud Growth and Advanced Editions last spring, Salesforce has steadily expanded their global footprint—bringing powerful capabilities to marketers worldwide. In 2024, these editions rolled out across North America, Asia/Middle East, and Latin America, enabling organizations to unify marketing, sales, service, and commerce on a single platform. With built-in access to Agentforce, teams can now save time and unlock smarter marketing by tapping into data from across the Salesforce ecosystem. Now, in spring 2025, Salesforce is extending access even further—launching in five new regions and enabling new channels like WhatsApp. This means more businesses can take advantage of unified workflows, regional data residency, and AI-powered customer journeys at scale. 🌍 New Regions Now Supported As of early 2025, Marketing Cloud Growth and Advanced Editions (and Data Cloud) are now available in five additional regions, enhancing data residency and local compliance: Why it matters:Data residency—storing and processing data in the same region it’s collected—is critical for compliance, trust, and security. These new region-specific deployments help businesses meet local regulations and ensure a secure, performant experience for users. What’s next?Additional regions, including markets across ASEAN, are set to go live in the first half of 2025. 📲 Channel Expansion: Now with Native WhatsApp Salesforce has also expanded channel support for Marketing Cloud Growth and Advanced Editions by introducing native WhatsApp messaging. 🚀 The Big Picture With expanded regional support, native WhatsApp messaging, and seamless integration with Agentforce and Data Cloud, Marketing Cloud Growth and Advanced Editions are empowering global teams to deliver more personalized, automated, and compliant experiences—at scale. This is marketing that meets the moment—wherever your customers are. 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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Real-World AI

AI in the Travel Industry

AI in Travel: How the Industry is Transforming with Intelligent Technology The travel sector has long been at the forefront of AI adoption, with airlines, hotels, and cruise lines leveraging advanced analytics for decades to optimize pricing and operations. Now, as artificial intelligence evolves—particularly with the rise of generative AI—the industry is entering a new era of smarter automation, hyper-personalization, and seamless customer experiences. “AI and generative AI have emerged as truly disruptive forces,” says Kartikey Kaushal, Senior Analyst at Everest Group. “They’re reshaping how travel businesses operate, compete, and serve customers.” According to Everest Group, AI adoption in travel is growing at 14-16% annually, driven by demand for efficiency and enhanced customer engagement. But as adoption accelerates, the industry must balance automation with the human touch that travelers still value. 10 Key AI Use Cases in Travel & Tourism 1. Dynamic Pricing Optimization Travel companies pioneered AI-driven dynamic pricing, adjusting fares based on demand, competitor rates, weather, and events. Now, AI takes it further with hyper-personalized pricing—tracking user behavior (like repeated searches) to offer tailored deals. 2. Customer Sentiment Analysis AI evaluates traveler emotions through voice tone, reviews, and social media, enabling real-time adjustments. Hotels and airlines use sentiment tracking to improve service before complaints escalate. 3. Automated Office Tasks Travel agencies use generative AI (like ChatGPT) to draft emails, marketing content, and customer onboarding materials, freeing staff for high-value interactions. 4. Self-Service & Customer Empowerment AI-powered chatbots, itinerary builders, and booking tools let travelers plan trips independently. Some even bring AI-generated plans to agents for refinement—blending automation with human expertise. 5. Operational Efficiency & Asset Management Airlines and cruise lines deploy AI for:✔ Predictive maintenance (reducing downtime)✔ Route optimization (cutting fuel costs)✔ Staff scheduling (improving productivity) 6. AI-Powered Summarization Booking platforms use generative AI to summarize hotel reviews, local attractions, and FAQs—delivering concise, personalized travel insights. 7. Frictionless Travel Experiences From contactless hotel check-ins to AI-driven real-time recommendations (restaurants, shows, transport), AI minimizes hassles and enhances convenience. 8. AI Agents for Problem-Solving Agentic AI autonomously resolves disruptions—like rebooking flights, rerouting luggage, and updating hotels—without human intervention. 9. Enhanced Personalization Without “Creepiness” AI tailors recommendations based on past behavior but must avoid overstepping. The challenge? “A customer segment of one”—balancing customization with privacy. 10. Risk & Compliance Management AI helps navigate data privacy laws (GDPR, CCPA) and detects fraud, but companies must assign clear accountability for AI-driven decisions. Challenges in AI Adoption for Travel The Future: AI + Human Collaboration The most successful travel companies will blend AI efficiency with human empathy, ensuring technology enhances—not replaces—the art of travel. “The goal isn’t full automation,” says McKinsey’s Alex Cosmas. “It’s using AI to make every journey smoother, smarter, and more personal.” As AI evolves, so will its role in travel—ushering in an era where smarter algorithms and human expertise work together to create unforgettable experiences. What’s Next? The journey has just begun. 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 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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Healthcare Cybersecurity Challenges Persist

Healthcare Cybersecurity Challenges Persist

Healthcare Cybersecurity Challenges Persist as Sector Struggles to Shift from Reactive to Proactive Strategies Healthcare organizations of all sizes continue to face significant challenges in addressing systemic cybersecurity risks, with new benchmarking data revealing that the industry remains largely reactive rather than proactive in its approach. The findings come from the 2025 Healthcare Cybersecurity Benchmarking Study, a collaborative effort by KLAS Research, Censinet, the American Hospital Association (AHA), the Health Information Sharing and Analysis Center (H-ISAC), the Healthcare and Public Health Sector Coordinating Council (HSCC), and the Scottsdale Institute. The study gathered responses from 69 healthcare and payer organizations between September and December 2024, assessing their alignment with key cybersecurity frameworks, including: Key Findings: Strong Response & Recovery, but Gaps in Prevention & Risk Management 1. Persistent Focus on Reactive Measures Consistent with past years, healthcare organizations reported high coverage in the “Respond” and “Recover” functions of the NIST CSF 2.0, indicating strong incident response and disaster recovery capabilities. However, long-term recovery planning lags behind immediate response efforts, suggesting room for improvement. “As cyber threats grow, healthcare organizations are preparing for when—not if—they will face a breach, emphasizing incident response and business continuity strategies,” the study noted. 2. Critical Gaps in Supply Chain & Asset Management Under the NIST CSF, the lowest coverage areas were: This is particularly concerning given the rising number of third-party breaches impacting healthcare. 3. Cybersecurity Insurance Benefits from Framework Adoption Organizations implementing the NIST CSF saw slower growth in cybersecurity insurance premiums, reinforcing the financial benefits of proactive risk management. 4. Emerging AI Risk Management Efforts Adoption of the NIST AI RMF remains in early stages, with many organizations still establishing governance structures for AI-related risks. 5. HICP & HPH CPG Findings Align with Past Trends Moving from Reactive to Proactive Security While progress has been made, the study highlights that greater adherence to leading cybersecurity frameworks can help healthcare organizations transition to a more proactive security posture, reducing risk and improving resilience. “The healthcare sector must prioritize foundational cybersecurity practices—particularly in supply chain and asset management—to mitigate escalating threats,” the report concluded. Final Takeaway:Healthcare cybersecurity remains heavily reactive, but organizations that invest in comprehensive risk management, third-party oversight, and AI governance can better protect patient data and reduce long-term vulnerabilities. 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 Advanced Routing

Salesforce Advanced Routing

Salesforce Advanced Routing is a feature within the Salesforce Service Cloud that helps organizations efficiently route cases, leads, and other work items to the most appropriate agents or teams. This ensures that customer inquiries and issues are handled by the right person at the right time, improving response times, customer satisfaction, and overall operational efficiency. Key Features of Salesforce Advanced Routing: Benefits of Salesforce Advanced Routing: Use Cases: Implementation Considerations: In summary, Salesforce Advanced Routing is a powerful tool that helps organizations efficiently manage and route work items to the most appropriate agents or teams. By leveraging features like omni-channel routing, skill-based routing, and real-time routing, businesses can improve customer experience, increase agent efficiency, and optimize their overall operations. 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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SaaS Data Protection from Own

Salesforce Integrates Own Co. Capabilities

Salesforce Integrates Own Co. Capabilities to Strengthen Data Resilience, Security, and AI Readiness Salesforce has fully integrated Own Co.’s data backup, recovery, and security solutions into its platform, equipping partners and customers with enhanced tools for data resilience, compliance, and security—critical foundations as businesses adopt AI-driven solutions. Marla Hay, Vice President of Product Management for Security, Privacy, and Data Management at Salesforce, emphasized in an interview with CRN that these new capabilities are essential as partners guide customers through AI adoption. “Before launching any major AI initiative, ensuring robust data backup and hygiene is critical,” Hay said. “With AI and autonomous agents, the quality of insights depends entirely on the integrity of your data. These new tools help businesses minimize risk while maximizing AI’s potential.” Key Enhancements for AI and Security The integration empowers solution providers to: “Clean, well-managed data isn’t just about compliance—it accelerates operations, enhances customer experiences, and ensures accuracy,” Hay added. Salesforce announced its acquisition of Own Co. in September 2023, bringing over 7,000 customers into its ecosystem. The newly integrated features include: 1. Secure Data Masking & Sandbox Testing 2. Enhanced Monitoring & Threat Detection 3. Robust Backup & Recovery 4. AI-Ready Data Insights with Salesforce Discover 5. Cost-Efficient Data Archiving Why This Matters for AI Adoption As businesses increasingly rely on AI agents and predictive analytics, ensuring data integrity, security, and recoverability is non-negotiable. Salesforce’s integration of Own Co.’s capabilities provides a low-risk pathway to cleaner, more resilient data—ultimately leading to: For partners and customers, these enhancements mean smoother AI deployments, reduced risk, and better business outcomes. Interested in leveraging these new capabilities? 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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Second Wave of AI Agents

Second Wave of AI Agents

The “second wave” of AI agents refers to the evolution of AI beyond simple chatbots and into more sophisticated, autonomous systems that can plan, execute, and deliver results independently, often leveraging large language models (LLMs). These agents are characterized by their ability to interact with other applications, interpret the screen, fill out forms, and coordinate with other AI systems to achieve a desired outcome. They are also seen as a significant step beyond the first wave of AI, which primarily focused on predictive models and statistical learning.  Key Characteristics of the Second Wave of AI Agents: Examples and Applications: In 2023 Bill Gates prophesized AI Agents would be here in 5 years. His timing was off. But not his prediction. The Future of Computing: Your AI Agent, Your Digital Sidekick Imagine this: No more juggling apps. No more digging through menus. No more searching for a document or a spreadsheet. Just tell your device—in plain English—what you need, and it handles the rest. Whether it’s planning a tour, managing your schedule, or helping with work, your AI assistant will understand you personally, adapting to your life based on what you choose to share. This isn’t science fiction. Today, everyone online has access to an AI-powered personal assistant far more advanced than anything available in 2023. Meet the Agent: The Next Era of Computing This next-generation software—called an agent—responds to natural language and accomplishes tasks using deep knowledge of you and your needs. Bill Gates first wrote about agents in his 1995 book The Road Ahead, but only now, with recent AI breakthroughs, have they become truly possible. Agents won’t just change how we interact with technology. They’ll reshape the entire software industry, marking the biggest shift in computing since we moved from command lines to touchscreens. Consider Salesforce’s AgentForce. A platform driven by automated AI agents that can be trained to do virtually anything. Freeing staff up from mundane data entry and administrative work to really set them loose. Marketers can once again create content, but with the insights provided by AI. Sales teams can close deals, but with the lead rating details provided by AI. Developers can devote more time to writing code but letting AI do the repetitive pieces that take time away from awe inspiring development. Why This Changes Everything We’re on the brink of a revolution—one where technology doesn’t just respond to commands but anticipates your needs and acts on your behalf. The age of the AI agent is here, and it’s going to redefine how we live and work. By Tectonic’s Marketing Operations Manager, 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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Alaska Inspires

Alaska Inspires

Alaska Airlines Launches Guest-Facing Generative AI Tool, Alaska Inspires Alaska Airlines has become the first airline to introduce a guest-facing Generative AI (GenAI) tool with the launch of Alaska Inspires. Designed to simplify travel planning, this AI-powered assistant helps guests discover destinations more efficiently. “We heard from our guests that planning a trip to a new destination can take up to 40 hours,” says Bernadette Berger, Director of Innovation at Alaska Airlines. “Much of that time is spent comparing destinations, prices, travel times, and reading reviews. We built a Natural Language Search tool to let guests explore travel options using their own words, preferred language, or voice.” With Alaska Inspires, travelers can ask questions like, “Where can I go in Europe for under 80,000 miles?” or “Where can I go skiing within four hours?” Powered by OpenAI, the tool provides highly personalized responses and recommends up to four destinations, explaining why each was selected. This initiative is part of Alaska Airlines’ broader effort to develop a suite of GenAI tools that make discovering, shopping, and booking travel faster and more intuitive. Enhancing the Day-of-Travel Experience with AI Beyond trip planning, Alaska Airlines is leveraging GenAI to provide real-time, personalized travel insights. Berger highlights the growing role of AI in understanding guest preferences and delivering information in their preferred format. “Using voice as an interface—especially in a guest’s preferred language—is ideal for quick questions or simple tasks,” she explains. “How many minutes until I board?” or “Check me in for my flight” are prime examples of how voice-enabled GenAI can enhance the customer experience. Additionally, translating live announcements and direct messages into a traveler’s native language helps improve clarity and engagement. Bridging the Gap Between Data and Human Understanding Airlines operate in a world of complex policies, acronyms, and industry jargon. GenAI helps bridge this gap by translating raw operational data into clear, guest-friendly language. “GenAI excels at ingesting rules, policies, and operational data while generating responses that explain situations in a brand-aligned, easy-to-understand way,” Berger says. Currently, Alaska Airlines uses GenAI to assist customer service agents in quickly answering policy-related questions and responding to guest inquiries with speed and care. Balancing Innovation with Privacy and Quality While the opportunities with GenAI are vast, Berger acknowledges the challenges of implementing AI responsibly. “Building AI-powered tools is fast, but it requires time for model training, security, and rigorous user testing,” she notes. Ensuring privacy and maintaining high-quality outputs remain top priorities. Advice for the Industry: Experiment, Learn, and Scale For airlines, airports, and industry stakeholders exploring GenAI, Berger offers practical advice: focus on reducing the cost of testing. “If your AI roadmap is filled with expensive, time-consuming trials, your team will get stuck in hypotheticals,” she warns. “Build fast, low-cost experiments to validate the technology, use case, inputs, and outputs. Identify failures quickly and move on, then scale what works. This approach helps separate marketing hype from real business value and, most importantly, delivers solutions that truly enhance the customer experience.” With Alaska Inspires and a growing suite of AI-driven innovations, Alaska Airlines is leading the way in making travel planning and the day-of-travel experience more seamless and personalized. 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 Code Genie

Salesforce Code Genie

How Salesforce’s Agentforce Is Reshaping Development—Saving 30,000 Hours a Month “AI agents are transforming my role—shifting me from pure technical execution to strategic leadership,” says one Salesforce developer. Instead of spending hours on repetitive tasks like code reviews or debugging, she now focuses on designing scalable architectures, optimizing workflows, and driving innovation. This shift reflects a broader evolution in software development: Developers are becoming AI supervisors, guiding autonomous agents, refining outputs, and ensuring alignment with business goals. Success in this new paradigm requires systems thinking, context management, and strategic oversight—not just coding expertise. Agentforce: The AI-Powered Developer Revolution Salesforce is already leading this transition with Agentforce, its digital labor platform, which has saved 30,000 developer hours per month—equivalent to 15 full-time engineers—by automating routine tasks. Key tools powering this transformation include: Unlike traditional AI coding assistants (which suggest snippets or autocomplete boilerplate), Agentforce agents act autonomously. For example, a developer can simply prompt: “Create a component that calls this API, processes these parameters, and returns success/failure status.” The AI then: The developer’s role? Review, refine, and ensure alignment with broader system goals. CodeGenie: Salesforce’s Internal AI Powerhouse Behind Agentforce lies CodeGenie, Salesforce’s internal AI assistant, built on its proprietary CodeGen model. The results speak for themselves: ✅ 7M+ lines of code accepted✅ 500K+ developer questions answered✅ 30K+ hours saved monthly✅ Seamless integration (IDEs, GitHub, Slack, CLI) “CodeGenie handles repetitive work, freeing me to solve complex problems,” says NaveenKumar Namachivayam, Senior Software Engineer at Salesforce. “It’s like having an expert collaborator—making coding faster, smarter, and more efficient.” Lessons from Salesforce’s AI Journey These insights don’t just benefit Salesforce—they directly shape Agentforce’s external offerings. CodeGenie’s success, for example, informed Agentforce for Developers, ensuring enterprise users get battle-tested AI assistance. The Bottom Line: AI Won’t Replace Developers—It Will Elevate Them Just as cloud computing didn’t kill IT jobs, AI won’t make developers obsolete—it will redefine their roles. The future belongs to those who: 🔹 Embrace AI as a force multiplier🔹 Shift from writing code to orchestrating AI agents🔹 Focus on architecture, strategy, and innovation For organizations, this demands investment in training, culture, and tools that empower teams to lead in the agentic era. The message is clear: Developers who adapt will thrive—not as coders, but as AI-powered strategists. Salesforce’s Agentforce is proving it’s possible 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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Agentforce: Modernizing 311 and Case Management

Join Tectonic for an informational webinar on Salesforce Agentforce, Modernizing 311 services, and Case management. In this webinar you will hear: For more information fill out the contact us form below or reach out to the Public Sector team [email protected] Get ready for the Next Frontier in Enterprise AI: Shaping Public Policies for Trusted AI Agents! AI agents are a technological revolution – the third wave of artificial intelligence after predictive and generative AI. They go beyond traditional automation, being capable of searching for relevant data, analyzing it to formulate a plan, and then putting the plan into action. Users can configure agents with guardrails that specify what actions they can take and when tasks should be handed off to humans. For the past 25 years, Salesforce has led their customers through every major technological shift: from cloud, to mobile, to predictive and generative AI, and, today, agentic AI. We are at the cusp of a pivotal moment for enterprise AI that has the opportunity to supercharge productivity and change the way we work forever. This will require governments working together with industry, civil society, and all stakeholders to ensure responsible technological advancement and workforce readiness. We look forward to continuing our contributions to the public policy discussions on trusted enterprise AI agents. 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 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 Instance Refresh Maintenance

Why Salesforce is the Key to Cloud Transformation

Cloud transformation is essential for businesses aiming to scale, boost efficiency, and enhance customer experiences. As a leading cloud platform, Salesforce plays a pivotal role in this transition—connecting cloud ecosystems, optimizing operations, and ensuring seamless customer interactions. But to unlock its full potential, organizations need the right Salesforce experts to drive the transformation successfully. The Role of Salesforce in Cloud Transformation As a cloud-native platform, Salesforce provides automation, AI-driven insights, and deep integration across business functions. It acts as the central hub, linking sales, marketing, customer service, and back-end operations. During cloud migration, Salesforce ensures:✅ Customer data remains accessible and secure✅ Workflows stay optimized for efficiency✅ AI-powered insights drive smarter decision-making Without experienced Salesforce professionals, businesses risk data silos, inefficient processes, and failed integrations—leading to costly delays and operational setbacks. Challenges in Hiring Salesforce Experts 1. Talent Shortages & High Demand The growing reliance on Salesforce has created a ultra-competitive hiring landscape. Roles like Salesforce Developers, Architects, and Administrators are in high demand, making it challenging for companies to attract and retain top talent. 2. The Need for More Than Just Technical Skills Many organizations focus solely on coding expertise, but cloud transformation demands professionals who understand business processes, data architecture, and integration strategies. A developer who codes without considering business goals may create solutions that don’t align with the organization’s needs. 3. Integration Complexities Salesforce rarely operates in isolation—it must integrate with ERP systems, marketing automation tools, and other cloud platforms. Poorly planned integrations can lead to inefficiencies and disrupt transformation efforts, underscoring the need for specialists who can manage system connectivity effectively. Strategies for Hiring the Right Salesforce Experts 1. Clearly Define Roles & Responsibilities Before hiring, identify the specific expertise required. For example: 2. Prioritize Certifications & Hands-On Experience Look for candidates with certifications like: Additionally, hands-on experience with cloud integrations, API development, and data migration is crucial for success. 3. Assess Problem-Solving Abilities Cloud transformation is complex, often presenting unexpected challenges. A structured hiring process should include scenario-based questions and technical assessments to evaluate candidates’ ability to handle real-world Salesforce challenges. 4. Explore Contract & Full-Time Hiring Models Given the talent shortage, companies may need a mix of contract and full-time hires: 5. Align Hiring with Cloud Strategy Salesforce experts must collaborate with cloud engineers and IT teams to ensure seamless integration. When hiring, prioritize candidates who understand system architecture and can align Salesforce capabilities with long-term business goals. Building a Strong Salesforce Team for Cloud Transformation Hiring the right Salesforce experts is critical for a smooth and effective cloud transformation. By defining roles, prioritizing experience, and assessing real-world skills, businesses can build teams that drive long-term success. Salesforce managed services is an alternative to the talent shortage. If your organization is looking to strengthen its Salesforce talent strategy, partnering with experts like Tectonic can bridge hiring gaps. Tectonic delivers top-tier Salesforce talent to power your digital transformation. With a vast network of vetted professionals and data-driven recruitment strategies, we help companies secure skilled experts—fast without increasing headcount. Let’s build your Salesforce dream team. 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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Large and Small Language Models

Architecture for Enterprise-Grade Agentic AI Systems

LangGraph: The Architecture for Enterprise-Grade Agentic AI Systems Modern enterprises need AI that doesn’t just answer questions—but thinks, plans, and acts autonomously. LangGraph provides the framework to build these next-generation agentic systems capable of: ✅ Multi-step reasoning across complex workflows✅ Dynamic decision-making with real-time tool selection✅ Stateful execution that maintains context across operations✅ Seamless integration with enterprise knowledge bases and APIs 1. LangGraph’s Graph-Based Architecture At its core, LangGraph models AI workflows as Directed Acyclic Graphs (DAGs): This structure enables:✔ Conditional branching (different paths based on data)✔ Parallel processing where possible✔ Guaranteed completion (no infinite loops) Example Use Case:A customer service agent that: 2. Multi-Hop Knowledge Retrieval Enterprise queries often require connecting information across multiple sources. LangGraph treats this as a graph traversal problem: python Copy # Neo4j integration for structured knowledge from langchain.graphs import Neo4jGraph graph = Neo4jGraph(url=”bolt://localhost:7687″, username=”neo4j”, password=”password”) query = “”” MATCH (doc:Document)-[:REFERENCES]->(policy:Policy) WHERE policy.name = ‘GDPR’ RETURN doc.title, doc.url “”” results = graph.query(query) # → Feeds into LangGraph nodes Hybrid Approach: 3. Building Autonomous Agents LangGraph + LangChain agents create systems that: python Copy from langchain.agents import initialize_agent, Tool from langchain.chat_models import ChatOpenAI # Define tools search_tool = Tool( name=”ProductSearch”, func=search_product_db, description=”Searches internal product catalog” ) # Initialize agent agent = initialize_agent( tools=[search_tool], llm=ChatOpenAI(model=”gpt-4″), agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION ) # Execute response = agent.run(“Find compatible accessories for Model X-42”) 4. Full Implementation Example Enterprise Document Processing System: python Copy from langgraph.graph import StateGraph from langchain.embeddings import OpenAIEmbeddings from langchain.vectorstores import Pinecone # 1. Define shared state class DocProcessingState(BaseModel): query: str retrieved_docs: list = [] analysis: str = “” actions: list = [] # 2. Create nodes def retrieve(state): vectorstore = Pinecone.from_existing_index(“docs”, OpenAIEmbeddings()) state.retrieved_docs = vectorstore.similarity_search(state.query) return state def analyze(state): # LLM analysis of documents state.analysis = llm(f”Summarize key points from: {state.retrieved_docs}”) return state # 3. Build workflow workflow = StateGraph(DocProcessingState) workflow.add_node(“retrieve”, retrieve) workflow.add_node(“analyze”, analyze) workflow.add_edge(“retrieve”, “analyze”) workflow.add_edge(“analyze”, END) # 4. Execute agent = workflow.compile() result = agent.invoke({“query”: “2025 compliance changes”}) Why This Matters for Enterprises The Future:LangGraph enables AI systems that don’t just assist workers—but autonomously execute complete business processes while adhering to organizational rules and structures. “This isn’t chatbot AI—it’s digital workforce AI.” Next Steps: 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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