Software Archives - gettectonic.com

The Rise of AI Agents

The Rise of AI Agents: How Autonomous AI is Reshaping Business As artificial intelligence advances, so does the terminology around it. The term “AI agent” is gaining traction as generative AI becomes deeply embedded in business operations. Unlike traditional AI tools that follow rigid scripts, AI agents are autonomous programs capable of learning, adapting, and executing tasks with minimal human intervention. Why AI Agents Are Booming The rapid expansion of large language models (LLMs) has slashed the cost of developing AI agents, fueling a surge in startups specializing in industry-specific AI solutions. According to Stripe’s 2024 research, AI startups achieved record revenue growth last year, signaling a shift from generic AI tools (like ChatGPT) to verticalized AI agents tailored for specific sectors. In their annual letter, Stripe co-founders Patrick and John Collison noted: “Just as SaaS evolved from horizontal platforms (Salesforce) to vertical solutions (Toast), AI is following the same path. Industry-specific AI agents ensure businesses fully harness LLMs by integrating contextual data and workflows.” AI Agents in Action: Industry Success Stories From manufacturing to finance, AI agents are already delivering tangible benefits: David Lodge, VP of Engineering at IBS Software, explains: “Fragmented systems limit AI’s potential. Unifying CRM, PMS, and loyalty data into a single platform is critical for AI to drive real transformation.” Hospitality’s AI Revolution: Breaking Down Data Silos Hotels like Wyndham and IHG have partnered with Salesforce to consolidate millions of guest records, enabling AI agents to deliver hyper-personalized service. In February 2025, Apaleo launched an AI Agent Marketplace for hospitality, allowing hotels to integrate AI solutions without costly system overhauls. Case Study: mk Hotels The Future: Autonomous Agents Redefining Workflows In September 2024, Salesforce introduced Agentforce, a platform for building secure, data-grounded AI agents that automate complex workflows. Jan Erik Aase, Partner at ISG, predicts: “The shift to agent-driven enterprises isn’t just technological—it’s cultural. As AI agents grow smarter, they’ll redefine customer interactions and decision-making.” Key Takeaways The AI agent revolution is here—and businesses that embrace it will lead the next wave of productivity and innovation. 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 in a Mega-Data Deal with Informatica

Salesforce and Informatica Again

Salesforce Revives Talks to Acquire Informatica in Major Data Play San Francisco, CA – Salesforce is reportedly in advanced discussions to acquire cloud data management firm Informatica, reigniting a potential deal that collapsed last year, according to sources familiar with the matter. Deal Details & Strategic Rationale A Deal Years in the Making Strategic Fit & Potential Hurdles Salesforce’s Acquisition History The CRM giant has a track record of blockbuster deals, including: However, activist investors recently pushed Salesforce to curb large acquisitions in favor of organic growth, leading to: The revived Informatica talks suggest a strategic pivot back to growth via acquisitions. Informatica’s Ownership & Market Position What’s Next? Industry Watch: Will Salesforce secure its next big bet, or will history repeat itself with another stalled deal? Key Takeaway: If successful, this acquisition would mark Salesforce’s return to large-scale M&A, positioning it as a stronger player in AI-powered data management. Follow-up Question: How would an Informatica acquisition impact Salesforce’s competition with Microsoft, Oracle, and Snowflake? 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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Understanding Total Addressable Market

Understanding Total Addressable Market

Understanding Total Addressable Market (TAM): Calculation & Examples Calculating your Total Addressable Market (TAM) is the cornerstone of a strong growth strategy, ensuring all teams work toward the same goals. This metric represents your “blue sky” opportunity—the maximum revenue potential if you captured 100% of your market. Learn how to leverage TAM to refine your sales and business strategy. What Is Total Addressable Market (TAM)? TAM refers to the total demand for your product or service, measured either by the number of potential customers or the total revenue opportunity. It defines the full scope of your business opportunity. Why TAM Matters TAM vs. SAM vs. SOM: Key Differences While TAM represents the entire market, Serviceable Addressable Market (SAM) and Serviceable Obtainable Market (SOM) refine it into realistic targets: Example: From TAM to SOM Suppose you sell baseball bats in the U.S.: This breakdown helps prioritize growth strategies, such as expanding distribution or increasing production. How to Calculate TAM Basic Formula: TAM = Total Potential Customers × Average Revenue Per User (ARPU) Calculation Methods: TAM Calculation Examples 1. Software Company 2. Lemonade Stand 3. Pizzeria Expansion Common TAM Calculation Challenges & Solutions ✅ Overestimating TAM → Narrow focus using realistic customer segments.✅ Outdated Data → Re-evaluate TAM quarterly or annually.✅ Lack of Market Research → Use related industry data or pilot sales metrics. Using TAM in Strategic Planning Final Thoughts TAM helps quantify opportunities, prioritize investments, and scale effectively. Use sales planning tools to track progress and adjust strategies as markets evolve. By mastering TAM, you unlock data-driven growth—ensuring every business move aligns with real market potential. 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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Agentic AI Race

The Evolution Beyond AI Agents

The Evolution Beyond AI Agents: What Comes Next? The Rapid Progression of AI Terminology The landscape of artificial intelligence has undergone a remarkable transformation in just three years. What began with ChatGPT and generative AI as the dominant buzzwords quickly evolved into discussions about copilots, and most recently, agentic AI emerged as 2024‘s defining concept. This accelerated terminology cycle mirrors fashion industry trends more than traditional technology adoption curves. Major players including Adobe, Qualtrics, Oracle, OpenAI, and Deloitte have recently launched agentic AI platforms, joining earlier entrants like Microsoft, AWS, and Salesforce. This rapid market saturation suggests the industry may already be approaching the next conceptual shift before many organizations have fully implemented their current AI strategies. Examining the Staying Power of Agentic AI Industry analysts present diverging views on the longevity of the agentic AI concept. Brandon Purcell, a Forrester Research analyst, acknowledges the pattern of fleeting AI trends while recognizing agentic AI’s potential for greater staying power. He cites three key factors that may extend its relevance: Klaasjan Tukker, Adobe’s Senior Director of Product Marketing, draws parallels to mature technologies that have become invisible infrastructure. He predicts agentic AI will follow a similar trajectory, becoming so seamlessly integrated that users will interact with it as unconsciously as they use navigation apps or operate modern vehicles. The Automotive Sector as an AI Innovation Catalyst The automotive industry provides compelling examples of advanced AI applications that transcend current “agentic” capabilities. Modern autonomous vehicles demonstrate sophisticated AI behaviors including: These implementations suggest that what the tech industry currently labels as “agentic” may represent only an intermediate step toward more autonomous, context-aware systems. The Definitional Challenges of Agentic AI The technology sector faces significant challenges in establishing common definitions for emerging AI concepts. Adobe’s framework describes agents as systems possessing three core attributes: However, as Scott Brinker of HubSpot notes, the term “agentic” risks becoming overused and diluted as vendors apply it inconsistently across various applications and functionalities. Interoperability as the Critical Success Factor For agentic AI systems to deliver lasting value, industry observers emphasize the necessity of cross-platform compatibility. Phil Regnault of PwC highlights the reality that enterprise environments typically combine solutions from multiple vendors, creating integration challenges for AI implementations. Three critical layers require standardization: Without such standards, organizations risk creating new AI silos that mirror the limitations of legacy systems. The Future Beyond Agentic AI While agentic AI continues its maturation process, the technology sector’s relentless innovation cycle suggests the next conceptual breakthrough may emerge sooner than expected. Historical naming patterns for AI advancements indicate several possibilities: As these technologies evolve, they may shed specialized branding in favor of more utilitarian terminology, much as “software bots” became normalized after their initial hype cycle. The automotive parallel suggests that truly transformative AI implementations may become so seamlessly integrated that their underlying technology becomes invisible to end users—the ultimate measure of technological maturity. Until that point, the industry will likely continue its rapid cycle of innovation and rebranding, searching for the next paradigm that captures the imagination as powerfully as “agentic AI” has in 2024. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more 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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Once Upon a Time in Data Land

Once Upon a Time in Data Land: Building the Artificial Intelligence-Ready Warehouse In the early days of data, businesses simply wanted to know what had already happened in the past. Questions like “How many units shipped?” or “What were last month’s sales?” drove the first major digital settlements—the Digitally Filed Data Warehouse. Looking back this seems like the aluminum carport you can have erected in your driveway. The Meticulously Organized Library (The Digitally Filed Data Warehouse Era) Imagine a grand, meticulously organized library. Data from sales, finance, and inventory wasn’t just dumped inside—it went through ETL (Extract, Transform, Load), where it was cleaned, standardized, and structured into predefined formats. Need quarterly sales figures? They were always in the same place, ready for reliable reporting. But then, the world outside got messy. Suddenly, businesses weren’t just dealing with neat rows and columns—they faced website clicks, customer emails, sensor data, social media streams, images, and videos. The rigid Digitally Filed Data Warehouse struggled to adapt. Trying to force unstructured data through ETL was like trying to shelve a waterfall—slow, expensive, and often impossible. The Everything Shed (The Rise of the AI-Powered Warehouse) Enter the AI-Powered Warehouse—a vast, flexible storage space built for raw, unstructured data. Instead of forcing structure upfront, it embraced “store first, organize later” (schema-on-read). Data scientists could explore everything, from tweets to video transcripts, without constraints. But freedom had a cost. Without governance, many AI-Powered Warehouses became “data swamps”—cluttered, unreliable, and slow. Finding clean, trustworthy data was a treasure hunt, and building reliable AI pipelines was a challenge. Organizing the Shed (The AI-Ready Warehouse Paradigm) The solution? Structure without sacrifice. The AI-Ready Warehouse kept the flexibility of raw storage but added intelligence on top. Technologies like Delta Lake, Apache Iceberg, and Apache Hudi introduced:✔ ACID transactions (no more corrupted data)✔ Data versioning (“time travel” to past states)✔ Schema enforcement (order without rigidity)✔ Performance optimizations (speed at scale) A key innovation was the Medallion Architecture, organizing data by quality: This hybrid approach unified BI dashboards, analytics, and machine learning—all on the same foundation. The AI Factory (The Modern AI-Functioning Warehouse) Just as businesses adapted, AI evolved. Generative AI, autonomous agents, and real-time decision-making demanded more than batch-processed data. The AI-Ready Warehouse transformed into a fully integrated AI factory, built for: 🔹 Real-Time & Streaming Data 🔹 Seamless MLOps Integration 🔹 Vector Databases & Embeddings 🔹 Robust AI Governance Why This Matters for AI Agents Autonomous AI agents don’t just analyze data—they act on it. The AI-Functioning Warehouse gives them:✔ Context: Real-time data + historical insights✔ Consistency: Features match training data✔ Memory: Logged actions for continuous learning The Future: An AI-Native Data Ecosystem The journey from Digitally Filed Data Warehouse to AI-Powered Warehouse to AI-Functioning Warehouse reflects a shift from static reporting to dynamic intelligence. For businesses embracing AI, the question is no longer “Do we need a data strategy?” but “Is our data foundation AI-ready?” The answer will separate the leaders from the laggards in the age of AI. Next Steps: The future belongs to those who build not just for data, but for AI. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more 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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Sales Enablement

Salesforce’s Top Sales Enablement Tools

The 9 Best Sales Enablement Tools for 2025 Based on original research by Erin Hueffner, Writer at Salesforce Sales enablement software has become a must-have for high-performing sales teams. According to the Salesforce State of Sales report, adoption surged 48% in 2024, with 75% of reps crediting these tools for helping them meet quotas. But with so many options, how do you choose the right one? Below, we break down the top 9 sales enablement platforms—ranked by features, user ratings, and real-world impact. What Is Sales Enablement Software? Sales enablement tools help teams:✅ Train & onboard reps faster✅ Organize sales content (playbooks, case studies, scripts)✅ Track performance with CRM-linked analytics✅ Coach sellers with AI-driven insights The best platforms combine learning (LMS), content management (CMS), and CRM integration to drive measurable ROI. Who Uses Sales Enablement Tools? Key Benefits of Sales Enablement Software 🔹 Faster onboarding – Reduce ramp time for new hires.🔹 Higher win rates – AI recommends best-performing content.🔹 Larger deal sizes – Data reveals upselling opportunities.🔹 Shorter sales cycles – Right content at the right time. The 9 Best Sales Enablement Tools for 2025 (Ranked by G2 & Capterra ratings, features, and real-world impact) 1. Salesforce Sales Cloud Best for: End-to-end CRM-powered enablement⭐ Rating: 4.4/5 (G2) | ✅ Top Feature: AI-powered coaching (Agentforce) 2. Seismic Best for: Enterprise content & training unification⭐ Rating: 4.5/5 (G2) | ✅ Top Feature: AI-generated learning paths 3. Highspot Best for: AI-driven content recommendations⭐ Rating: 4.6/5 (Capterra) | ✅ Top Feature: Highspot Copilot (AI coaching) 4. Mindtickle Best for: Data-backed sales coaching⭐ Rating: 4.7/5 (G2) | ✅ Top Feature: AI role-play simulations 5. HubSpot Sales Hub Best for: SMBs needing CRM + enablement⭐ Rating: 4.3/5 (G2) | ✅ Top Feature: Conversation intelligence 6. Showpad Best for: Visual, interactive sales content⭐ Rating: 4.5/5 (G2) | ✅ Top Feature: AI-powered pitch coaching 7. Demodesk Best for: Virtual sales teams⭐ Rating: 4.6/5 (Capterra) | ✅ Top Feature: AI meeting summaries 8. ClientPoint Best for: Proposal & contract automation⭐ Rating: 4.4/5 (Capterra) | ✅ Top Feature: AI assistant (Meg) 9. Lessonly by Seismic Best for: Rapid sales training⭐ Rating: 4.5/5 (G2) | ✅ Top Feature: Microlearning modules Key Features to Look For 🔎 AI-powered coaching (e.g., call analysis, role-play feedback)📂 Smart content management (searchable, version-controlled libraries)📊 CRM integration (tie training to deal outcomes)📈 Predictive analytics (flag at-risk deals & skill gaps) How to Choose the Right Tool Final Verdict Sales enablement tools are no longer optional—they’re competitive necessities. The right platform can:✔ Cut ramp time by 50%+✔ Boost win rates by 20%✔ Reduce content search time by 80% Top Pick for 2025? Need AI coaching? Mindtickle & Demodesk lead the pack. Ready to enable your team? The right tool could be the difference between missing quota and smashing targets. 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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Streamline Data Collection from Connected Vehicles and Assets with AWS and Salesforce

Streamline Data Collection from Connected Vehicles and Assets with AWS and Salesforce

Unlock Real-Time Insights with AWS IoT and Salesforce Industry Clouds This guide explains how to gather, process, and distribute data from connected vehicles and industrial assets—such as manufacturing equipment or utility meters—into Salesforce Industry Cloud solutions using Amazon Web Services (AWS). Key AWS IoT Services for Data Collection By leveraging these services, businesses can integrate telemetry data into: Why This Integration Matters Strong customer relationships rely on real-time insights. Automakers, manufacturers, and utility providers can enhance customer interactions by unifying telemetry data with CRM workflows—enabling smarter marketing, sales, and service decisions. Prerequisites To integrate AWS IoT with Salesforce, you’ll need: AWS Services Salesforce Requirements Use Cases 1. Predictive Maintenance with AWS & Salesforce 2. In-Car Notifications 3. On-Demand Vehicle/Asset Health Insights 4. Data-Driven Customer Engagement Solution Architecture Data Flow Overview Implementation Steps 1. Set Up AWS IoT Rules 2. Configure Salesforce Event Handling 3. Enable Real-Time Analytics Conclusion By integrating AWS IoT with Salesforce Industry Clouds, businesses can:✔ Improve operational efficiency with predictive maintenance.✔ Enhance customer experiences through real-time alerts and diagnostics.✔ Drive data-driven decisions with unified analytics. Next Steps: Empower your teams with real-time IoT insights—start building 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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agentic revolution

The Agentic AI Revolution

The Agentic AI Revolution: Reskilling and Trust as Competitive Imperatives The rise of agentic AI—autonomous systems capable of independent decision-making—isn’t just another tech trend; it’s a fundamental shift in how businesses operate. With AI agents projected to unlock $6 trillion in digital labor value, companies that fail to adapt risk being outpaced by AI-driven competitors. To thrive in this new era, business leaders must focus on two critical pillars: 1. Reskilling for the Age of AI Collaboration The Urgent Skills Gap Key Competencies for the AI Era ✅ Human-AI Collaboration – Managing AI agents, prompt engineering, and oversight✅ Strategic Thinking – Shifting from routine tasks to big-picture planning✅ Leadership & Management – Overseeing AI “teams” and decision flows A Call to Action for Businesses “With AI handling routine coding, developers can now focus on system architecture and innovation—but only if we equip them for this shift.” 2. Trust: The Foundation of AI Adoption The Risks of Unchecked AI Building a Trusted AI Framework 🛡️ Guardrails & Escalation Protocols – Define when AI must defer to humans🔐 Data Protection – Ensure compliance with zero-retention LLM policies (e.g., Einstein Trust Layer)📊 Transparency Tools – Give employees visibility into AI decision logic Salesforce’s Approach: Agentforce The Path Forward: AI + Humans in Partnership Why This Matters Now Key Takeaways for Leaders Linda SaundersCountry Manager & Senior Director of Solution Engineering, Africa | Salesforce “The future belongs to businesses that combine AI’s efficiency with human ingenuity—guided by an unwavering commitment to trust.” Ready to lead in the agentic AI era? The AI revolution isn’t coming—it’s here. The question is: Will your organization be a disruptor or disrupted? 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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Model Context Protocol

Model Context Protocol

The AI Revolution Has Arrived: Meet MCP, the Protocol Changing Everything Imagine an AI that doesn’t just respond—it understands. It reads your emails, analyzes your databases, knows your business inside out, and acts on live data—all through a single universal standard. That future is here, and it’s called MCP (Model Context Protocol). Already adopted by OpenAI, Google, Microsoft, and more, MCP is about to redefine how we work with AI—forever. No More Copy-Paste AI Picture this: You ask your AI assistant about Q3 performance. Instead of scrambling through spreadsheets, Slack threads, and CRM reports, the AI already knows. It pulls real-time sales figures, checks customer feedback, and delivers a polished analysis—in seconds. This isn’t sci-fi. It’s happening today, thanks to MCP. The Problem With Today’s AI: Isolated Intelligence Most AI models are like geniuses locked in a library—brilliant but cut off from the real world. Every time you copy-paste data into ChatGPT or upload files to Claude, you’re working around a fundamental flaw: AI lacks context. For businesses, deploying AI means endless custom integrations: MCP: The Universal Language for AI Introduced by Anthropic in late 2024, MCP is the USB-C of AI—a single standard connecting any AI to any data source. Here’s how it works: Instead of building N×M connections (every AI × every data source), you build N + M—one integration per AI model and one per data source. MCP in Action: The Future of Work Why MCP Changes Everything The MCP Ecosystem is Exploding In less than a year, MCP has been adopted by: Beyond RAG: Real-Time Knowledge Traditional RAG (Retrieval-Augmented Generation) relies on stale vector databases. MCP changes the game: Security & Governance Built In The Next Frontier: AI Agents & Workflow Automation MCP enables AI agents that don’t just follow scripts—they adapt. The Time to Act is Now MCP isn’t just another API—it’s the foundation for true AI integration. The question isn’t if you’ll adopt it, but how fast. Welcome to the era of connected intelligence. 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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AI Revolution in Government

Ready for AI in Government

AI Agents in Government: Who’s Ready? A new Salesforce survey reveals strong public support for AI-driven government efficiency, with the potential to save Americans hours of bureaucratic hassle. However, the findings also highlight a demographic divide, underscoring the need for a tailored approach to implementation. Public Readiness for AI in Government Salesforce surveyed 1,000 Americans and found that 87% would use an AI agent to navigate complex government processes. AI agents—software programs that automate tasks and interact with citizens—could function as virtual assistants, making services more accessible and efficient. The demand for 24/7 assistance is driven by frustration with time-consuming government tasks. Respondents identified these processes as the biggest waste of time due to confusing or redundant questions: AI in Action: A Proven Use Case Salesforce has already helped government agencies enhance efficiency through AI. For example, the California Department of Motor Vehicles reduced the time required to apply for a Real ID from 35 minutes to just 7 minutes using AI-powered digital solutions. According to Nasi Jazayeri, EVP and GM of Public Sector at Salesforce, license renewals present a prime opportunity for AI-driven improvements: “Now, in minutes, state and local government agencies can set up an AI agent powered by agency-specific data to make this process easier on both the applicant and the reviewer.” Addressing Public Concerns Despite the enthusiasm, the survey also highlights key concerns about AI in government. The top issues cited were: Additionally, certain demographics were less open to AI adoption. The survey found that: The Road Ahead The Salesforce survey highlights a public eager for AI-driven improvements in government services, but with critical concerns that must be addressed. The challenge now is to deploy AI thoughtfully, ensuring accessibility, transparency, and trust while bridging the demographic divide. 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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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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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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Can Tech Companies Use Generative AI for Good?

AI and the Future of IT Careers

AI and the Future of IT Careers: Jobs That Remain Secure As AI technology advances, concerns about job security in the IT sector continue to grow. AI excels at handling repetitive, high-speed tasks and has made significant strides in software development and error prediction. However, while AI offers exciting possibilities, the demand for human expertise remains strong—particularly in roles that require interpersonal skills, strategic thinking, and decision-making. So, which IT jobs are most secure from AI displacement? To answer this question, industry experts shared their insights: Their forecasts highlight the IT roles most resistant to AI replacement. In all cases, professionals should enhance their AI knowledge to stay competitive in an evolving landscape. Top AI-Resistant IT Roles 1. Business Analyst Role Overview:Business analysts act as a bridge between IT and business teams, identifying technology opportunities and facilitating collaboration to optimize solutions. Why AI Won’t Replace It:While AI can process vast amounts of data quickly, it lacks emotional intelligence, relationship-building skills, and the ability to interpret nuanced human communication. Business analysts leverage these soft skills to understand software needs and drive successful implementations. How to Stay Competitive:Develop strong data analysis, business intelligence (BI), communication, and presentation skills to enhance your value in this role. 2. Cybersecurity Engineer Role Overview:Cybersecurity engineers protect organizations from evolving security threats, including AI-driven cyberattacks. Why AI Won’t Replace It:As AI tools become more sophisticated, cybercriminals will exploit them to develop advanced attack strategies. Human expertise is essential to adapt defenses, investigate threats, and implement security measures AI alone cannot handle. How to Stay Competitive:Continuously update your cybersecurity knowledge, obtain relevant certifications, and develop a strong understanding of business security needs. 3. End-User Support Professional Role Overview:These professionals assist employees with technical issues and provide hands-on training to ensure smooth software adoption. Why AI Won’t Replace It:Technology adoption is becoming increasingly complex, requiring personalized support that AI cannot yet replicate. Human interaction remains crucial for troubleshooting and user training. How to Stay Competitive:Pursue IT certifications, strengthen customer service skills, and gain experience in enterprise software environments. 4. Data Analyst Role Overview:Data analysts interpret business and product data, generate insights, and predict trends to guide strategic decisions. Why AI Won’t Replace It:AI can analyze data, but human oversight is needed to ensure accuracy, recognize context, and derive meaningful insights. Companies will continue to rely on professionals who can interpret and act on data effectively. How to Stay Competitive:Specialize in leading BI platforms, gain hands-on experience with data visualization tools, and develop strong analytical thinking skills. 5. Data Governance Professional Role Overview:These professionals set policies for data usage, access, and security within an organization. Why AI Won’t Replace It:As AI handles increasing amounts of data, the need for governance professionals grows to ensure ethical and compliant data management. How to Stay Competitive:Obtain a degree in computer science or business administration and seek training in data privacy, security, and governance frameworks. 6. Data Privacy Professional Role Overview:Data privacy professionals ensure compliance with data protection regulations and safeguard personal information. Why AI Won’t Replace It:With AI collecting vast amounts of personal data, organizations require human experts to manage legal compliance and maintain trust. How to Stay Competitive:Develop expertise in privacy laws, cybersecurity, and regulatory compliance through certifications and training programs. 7. IAM Engineer (Identity and Access Management) Role Overview:IAM engineers develop and implement systems that regulate user access to sensitive data. Why AI Won’t Replace It:The growing complexity of digital identities and security protocols requires human oversight to manage, audit, and secure access rights. How to Stay Competitive:Pursue a computer science degree, gain experience in authentication frameworks, and build expertise in programming and operating systems. 8. IT Director Role Overview:IT directors oversee technology strategies, manage teams, and align IT initiatives with business goals. Why AI Won’t Replace It:Leadership, motivation, and strategic decision-making are human-driven capabilities that AI cannot replicate. How to Stay Competitive:Develop strong leadership, business acumen, and team management skills to effectively align IT with organizational success. 9. IT Product Manager Role Overview:Product managers oversee tech adoption, service management, and organizational change strategies. Why AI Won’t Replace It:Effective product management requires a human touch, particularly in change management and stakeholder communication. How to Stay Competitive:Pursue project management training and certifications while gaining experience in software development and enterprise technology. Staying AI-Proof: Learning AI Expert Insights on Future IT Careers Final Thoughts As AI continues to reshape the IT landscape, the key to job security lies in adaptability. Professionals who develop AI-related skills and focus on roles that require human judgment, creativity, and leadership will remain indispensable in the evolving workforce. 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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AI Agents in Business 2025

Digital-First Auto Expectations

Gen Z is Reshaping the Auto Industry with AI and Digital-First Expectations As the first generation of digital natives, Gen Z is entering the car market with a strong preference for personalized, tech-driven experiences—disrupting traditional purchasing and leasing models. According to recent Salesforce research, 74% of Gen Z buyers want AI-powered agents to advise them on the optimal time to buy based on pricing trends, promotions, and incentives. To stay competitive, automotive leaders must adapt their strategies to meet these evolving expectations. Gen Z Embraces AI for Car Research and Financing Compared to older generations, Gen Z is far more likely to rely on AI for car shopping: A Tech-First Approach to Car Buying Gen Z’s reliance on technology stems from challenges in navigating the traditional car-buying process: Greater Trust in AI and Demand for Personalization Gen Z shows significantly higher confidence in AI-driven solutions: Subscription Models and Flexible Ownership Younger buyers favor innovative payment and ownership options: The Future of Automotive Retail With Gen Z leading the shift toward AI-powered car buying, maintenance, and flexible ownership models, automakers and dealers must prioritize digital-first solutions, transparent pricing, and hyper-personalized experiences to capture this influential market. Tectonic is here to help your company deliver on these Gen Z expectations with Salesforce. Contact us today! Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more 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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