Clari Archives - gettectonic.com

17May

The Salesforce AI Agent Maturity Model

The Salesforce AI Agent Maturity Model: A Roadmap for Scaling Intelligent Automation With 84% of CIOs believing AI will be as transformative as the internet, strategic adoption is no longer optional—it’s a competitive imperative. Yet many organizations struggle with where to begin, how to scale AI agents, and how to measure success. To help enterprises navigate this challenge, Salesforce has introduced the Agentic Maturity Model, a four-stage framework that guides businesses from basic automation to advanced, multi-agent ecosystems. “While agents can be deployed quickly, scaling them effectively requires a thoughtful, phased approach,” said Shibani Ahuja, SVP of Enterprise IT Strategy at Salesforce. “This model provides a clear roadmap to help organizations progress toward higher levels of AI maturity.” How Leading Companies Are Using the Framework Wiley: Building a Future-Ready AI Foundation “Visionary leadership is essential in today’s rapidly evolving AI landscape,” said Kevin Quigley, Director of Process Improvement at Wiley. “Salesforce’s framework ensures the building blocks we create today will support our long-term AI strategy.” Alpine Intel: Accelerating Efficiency in Insurance “Every minute saved counts in our high-volume claims business,” said Kelly Bentubo, Director of Architecture at Alpine Intel. “This model brings clarity to scaling AI—helping us move from time-saving automations to advanced multi-agent applications.” The Four Levels of Agentic Maturity Level 0: Fixed Rules & Repetitive Tasks (Chatbots & Co-pilots) What it is: Basic automation with no reasoning—think FAQ bots or scripted workflows.Example: A chatbot handling password resets via predefined decision trees. How to Advance to Level 1:✔ Identify rigid processes ripe for AI reasoning.✔ Measure time/cost savings from automation.✔ Start with low-risk, employee-facing agents. Level 1: Information Retrieval Agents What it is: AI that fetches data and suggests actions (but doesn’t act alone).Example: A support agent recommending troubleshooting steps from a knowledge base. How to Advance to Level 2:✔ Shift from recommendations to autonomous actions.✔ Improve data quality and governance.✔ Track metrics like case deflection and CSAT. Level 2: Simple Orchestration (Single Domain) What it is: Agents automating multi-step tasks within one system.Example: Scheduling meetings + sending follow-ups using calendar/email data. How to Advance to Level 3:✔ Choose between specialized agents or a “mega-agent.”✔ Extend capabilities with API integrations.✔ Design scalable architecture for future growth. Level 3: Complex Orchestration (Cross-Domain) What it is: AI coordinating workflows across departments (e.g., sales + service).Example: An agent analyzing CRM, support tickets, and financial data to optimize deals. How to Advance to Level 4:✔ Build a universal communication layer for agents.✔ Implement dynamic agent discovery & governance.✔ Measure ROI via cost savings and revenue impact. Level 4: Multi-Agent Ecosystems What it is: AI teams collaborating across systems with human oversight.Example: Agents processing orders, managing inventory, and routing feedback in real time. Maximizing Value:✔ Strengthen security for ecosystem-wide AI.✔ Develop new business models powered by agent collaboration.✔ Track revenue growth, retention, and operational efficiency. Beyond Technology: Key Implementation Factors “AI success hinges on more than just tech,” notes Ahuja. Organizations must: By addressing these pillars, businesses can accelerate AI adoption—turning experimentation into scalable, measurable value. Contact Tectonic today to harness the power of AI and move along the AI Agent maturity continuum. 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

May 17, 2025in Artificial Intelligence, Artificial Intelligence, Data, Enterprise, Salesforce, Technology0 Comments

07May

Mastering AI Prompts

Mastering AI Prompts: OpenAI’s Guide to Optimizing Reasoning Models OpenAI has released an updated prompting guide that reveals how to get the most accurate and useful responses from its reasoning models. As AI becomes more advanced, how you ask questions significantly impacts the quality of answers. Whether you’re a developer, business leader, or researcher, these best practices will help refine your AI interactions. Key Prompting Strategies from OpenAI 1. Simplicity Wins: Keep Prompts Direct Overloading prompts with unnecessary instructions can confuse the model. Instead of micromanaging its reasoning, trust the AI’s built-in logic. ✅ Better:“Analyze sales trends from this dataset.” ❌ Less Effective:“Break down this dataset step-by-step, explain each calculation, and ensure statistical best practices are followed.” 2. Skip the “Think Step by Step” Approach While some believe explicitly asking for reasoning helps, OpenAI found that models already optimize for logic—adding such instructions can backfire. ✅ Better:“What’s 25% of 200?” ❌ Less Effective:“Explain your reasoning step-by-step to calculate 25% of 200.” Need an explanation? Ask for it after getting the answer. 3. Use Delimiters for Complex Inputs When feeding structured data, contracts, or multi-part questions, clear separators prevent misinterpretation. ✅ Better: Copy Summarize the contract below: — [Contract text] — ❌ Less Effective:“Summarize this contract: The first party agrees to…” 4. Limit Context in Retrieval-Augmented Tasks When referencing external documents, only include relevant sections—too much info dilutes accuracy. ✅ Better:“Summarize key points from Sections 2 and 3 of this report.” ❌ Less Effective:“Read this 10-page document and summarize everything.” 5. Define Constraints for Precision The more specific your requirements, the better the output. ✅ Better:“Suggest a $500/month LinkedIn ad strategy for a B2B SaaS startup.” ❌ Less Effective:“Suggest a marketing plan.” 6. Iterate for Better Results If the first response isn’t perfect, refine your prompt with additional details. First Attempt:“Give me startup ideas.” Refined Prompt:“Suggest AI-powered B2B SaaS ideas for small business accounting.” Why This Matters OpenAI’s findings show that optimized prompting = better outputs. Whether you’re integrating AI into apps or using it for research, these techniques ensure smarter, faster, and more reliable responses. Try these strategies today—how will you refine your prompts? 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

May 7, 2025in Data0 Comments

06May

4 Steps to Unlock the Right Marketing Insights

Overwhelmed by Dashboard Data? 4 Steps to Unlock the Right Marketing Insights An effective dashboard should present marketing data clearly and concisely, enabling teams to quickly extract insights and make confident decisions. 4 Steps to Unlock the Right Marketing Insights Turning Data into Action with Trusted Insights Imagine walking into a restaurant with an overwhelming menu—dozens of dishes spanning multiple cuisines, making it difficult to choose. While the food may be good, the sheer volume of options leads to decision fatigue, causing diners to default to familiar choices rather than exploring new possibilities. The same challenge applies to marketing dashboards. When cluttered with excessive metrics, they become difficult to navigate, obscuring key insights rather than revealing them. A well-designed dashboard, like a well-curated menu, should guide users to the most valuable information—helping them act quickly and strategically. The Difference Between Reporting and Insights Many dashboards fall into the trap of displaying every possible metric, but true value comes from actionable insights, not just raw data. Example: A live campaign shows that email conversions outperform social ads. Instead of just noting the discrepancy, an insights-driven dashboard helps marketers diagnose why—perhaps stronger subject lines or better landing page alignment—and adjust social strategies in real time for immediate improvement. 4 Steps to Build Dashboards That Drive Decisions To transform dashboards from data overload into insight engines, follow this structured approach: 1. Define the User Persona Dashboards should cater to specific roles, not broad audiences. Different stakeholders need different insights: A one-size-fits-all dashboard drowns users in irrelevant data. Instead, tailor views to each persona’s core needs. 2. Align with Daily Tasks Collaborate with users to understand how they apply data in their workflows. A well-designed dashboard should: 3. Answer Key Business Questions Every dashboard should directly address the user’s most critical questions, such as: Prioritize KPIs that drive action, like:✔ Impressions (Reach)✔ Click-through rate (CTR) (Engagement)✔ Conversion rate (CVR) (Effectiveness)✔ Revenue per sale (ROI) Supplement these with supporting metrics (e.g., time on site, repeat visits) to uncover deeper trends. 4. Design for Clarity and Impact A great dashboard balances simplicity with depth: Example for Executives: A high-level dashboard showing revenue, CAC, and CLTV by region helps identify growth opportunities. If one region shows strong CLTV, leadership might invest further in similar markets. The Result? Faster, Smarter Decisions By focusing on personas, tasks, key questions, and clarity, marketers can move beyond data overload and unlock real business value. The best dashboards don’t just report numbers—they illuminate the path forward. Ready to streamline your insights? Start by having Tectonic refine one dashboard using these steps—and watch decision-making improve. 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

May 6, 2025in Data, Marketing Intelligence, Salesforce0 Comments

Analytics tools like Einstein Analytics can identify patterns and trends in patient data, helping healthcare providers optimize workflows and improve the effectiveness of care delivery.

03May

Healthcare Payers Turn to Data Analytics for Cost Savings and Improved Outcomes

Facing persistent financial and staffing pressures, healthcare payers are increasingly adopting data analytics platforms to streamline operations, reduce costs, and enhance member outcomes. A new April 2025 report from KLAS Research offers its first evaluation of payer experiences with these solutions, highlighting key vendors and emerging trends. The Growing Role of Data Analytics in Payer Operations With healthcare organizations under constant pressure to improve efficiency and decision-making, data analytics tools provide critical visibility into claims data, utilization patterns, and financial performance. These platforms enable payers to: While KLAS’ research in this space is still evolving, the initial report assesses three leading vendors, with plans to expand coverage as more data becomes available. Key Vendor Performances 1. MedInsight – Best in KLAS 2025 (Score: 85.8) 2. MedeAnalytics (Score: 87.1) 3. Clarify Health Solutions 4. Salesforce Health Cloud Looking Ahead: Expanding the Vendor Landscape Additional players like CareJourney (acquired by Arcadia in 2024), Cedar Gate Technologies, and Cognizant are expected to be evaluated in future KLAS reports as more performance data emerges. The Bottom Line As payers seek greater efficiency and data-driven decision-making, analytics platforms are becoming indispensable. While MedInsight and MedeAnalytics lead in early adoption, the competitive landscape is still evolving—making future KLAS insights critical for payer organizations evaluating their options. Next Steps: With the right analytics partner, payers can unlock cost savings, operational efficiencies, and better member outcomes—key priorities in today’s challenging healthcare environment. 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

May 3, 2025in Data, Life Sciences Cloud, Salesforce, Salesforce Health Cloud0 Comments

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 PublicSector@GetTectonic.com 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

April 23, 2025in Agentforce Platform, Agentic AI, AI Tools, Artificial Intelligence, Data, Enterprise, Generative AI, Generative AI Tools, Public Sector Solutions, Salesforce, Salesforce Development Services, Salesforce Implementation Services, Salesforce Optimization, Salesforce Public Sector Solutions, Technology0 Comments

21Apr

Copilots and Agents

Which Agentic AI Features Truly Matter? Modern large language models (LLMs) are often evaluated based on their ability to support agentic AI capabilities. However, the effectiveness of these features depends on the specific problems AI agents are designed to solve. The term “AI agent” is frequently applied to any AI application that performs intelligent tasks on behalf of a user. However, true AI agents—of which there are still relatively few—differ significantly from conventional AI assistants. This discussion focuses specifically on personal AI applications rather than AI solutions for teams and organizations. In this domain, AI agents are more comparable to “copilots” than traditional AI assistants. What Sets AI Agents Apart from Other AI Tools? Clarifying the distinctions between AI agents, copilots, and assistants helps define their unique capabilities: AI Copilots AI copilots represent an advanced subset of AI assistants. Unlike traditional assistants, copilots leverage broader context awareness and long-term memory to provide intelligent suggestions. While ChatGPT already functions as a form of AI copilot, its ability to determine what to remember remains an area for improvement. A defining characteristic of AI copilots—one absent in ChatGPT—is proactive behavior. For example, an AI copilot can generate intelligent suggestions in response to common user requests by recognizing patterns observed across multiple interactions. This learning often occurs through in-context learning, while fine-tuning remains optional. Additionally, copilots can retain sequences of past user requests and analyze both memory and current context to anticipate user needs and offer relevant suggestions at the appropriate time. Although AI copilots may appear proactive, their operational environment is typically confined to a specific application. Unlike AI agents, which take real actions within broader environments, copilots are generally limited to triggering user-facing messages. However, the integration of background LLM calls introduces a level of automation beyond traditional AI assistants, whose outputs are always explicitly requested. AI Agents and Reasoning In personal applications, an AI agent functions similarly to an AI copilot but incorporates at least one of three additional capabilities: Reasoning and self-monitoring are critical LLM capabilities that support goal-oriented behavior. Major LLM providers continue to enhance these features, with recent advancements including: As of March 2025, Grok 3 and Gemini 2.0 Flash Thinking rank highest on the LMArena leaderboard, which evaluates AI performance based on user assessments. This competitive landscape highlights the rapid evolution of reasoning-focused LLMs, a critical factor for the advancement of AI agents. Defining AI Agents While reasoning is often cited as a defining feature of AI agents, it is fundamentally an LLM capability rather than a distinction between agents and copilots. Both require reasoning—agents for decision-making and copilots for generating intelligent suggestions. Similarly, an agent’s ability to take action in an external environment is not exclusive to AI agents. Many AI copilots perform actions within a confined system. For example, an AI copilot assisting with document editing in a web-based CMS can both provide feedback and make direct modifications within the system. The same applies to sensor capabilities. AI copilots not only observe user actions but also monitor entire systems, detecting external changes to documents, applications, or web pages. Key Distinctions: Autonomy and Versatility The fundamental differences between AI copilots and AI agents lie in autonomy and versatility: If an AI system is labeled as a domain-specific agent or an industry-specific vertical agent, it may essentially function as an AI copilot. The distinction between copilots and agents is becoming increasingly nuanced. Therefore, the term AI agent should be reserved for highly versatile, multi-purpose AI systems capable of operating across diverse domains. Notable examples include OpenAI’s Operator and Deep Research. 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

April 21, 2025in Agentic AI, AI Tools, Data, Google, Salesforce0 Comments

17Apr

Essential Teams Every SMB Needs

Lean & Mean: The Essential Teams Every SMB Needs to Thrive Gone are the days when success required massive budgets and bloated teams. Today’s most competitive small and medium businesses (SMBs) run lean, agile operations—often with remote teams, strategic outsourcing, and smart automation. But while you can cut costs, you can’t cut corners on these six core teams—the engine that keeps your business moving forward. 1. Sales & Customer Acquisition: Your Growth Engine Mission: Turn prospects into paying customers. Key Focus Areas: ✅ Lead generation – Find your ideal customers (social media, referrals, targeted outreach).✅ Pipeline management – Never let a hot lead slip through the cracks.✅ Closing deals – Guide buyers with confidence. Pro Tip: A CRM like Salesforce Starter Suite automates follow-ups, tracks leads, and uses AI to predict the best next steps. 2. Finance & Accounting: Your Money Guardians Mission: Keep cash flowing and finances healthy. Key Focus Areas: ✅ Bookkeeping – Track income, expenses, and profits.✅ Invoicing & payments – Get paid faster, pay vendors on time.✅ Tax compliance – Avoid penalties with organized records. Pro Tip: Tools like QuickBooks automate invoicing, expense tracking, and financial reporting. 3. Marketing & Branding: Your Storytellers Mission: Make sure the right people know (and love) your business. Key Focus Areas: ✅ Content marketing – Blogs, social media, videos that build trust.✅ Multi-channel campaigns – Email, social, SEO, ads.✅ Brand consistency – Same look, voice, and vibe everywhere. Pro Tip: With AI-powered tools like Agentforce, you can launch campaigns in minutes—just give a prompt, and it drafts emails, schedules posts, and optimizes engagement. 4. Operations & Logistics: Your Efficiency Experts Mission: Keep everything running smoothly behind the scenes. Key Focus Areas: ✅ Inventory management – Avoid stockouts or overstocking.✅ Supply chain optimization – Faster, cheaper deliveries.✅ Process automation – Reduce manual work. Pro Tip: Platforms like ShipBob automate order fulfillment, while Salesforce Operations Hub streamlines workflows. 5. Customer Support & Success: Your Retention Army Mission: Keep customers happy so they keep coming back. Key Focus Areas: ✅ Quick response times – Solve issues fast.✅ Proactive check-ins – Ensure customers succeed with your product.✅ Self-service options – FAQs, chatbots, tutorials. Pro Tip: Agentforce AI assistants handle 24/7 support, answering FAQs and escalating only when needed. 6. People & Culture: Your Team Builders Mission: Attract, retain, and empower top talent. Key Focus Areas: ✅ Hiring & onboarding – Find people who fit your culture.✅ Payroll & benefits – Keep employees happy.✅ Employee engagement – Foster a great workplace. Pro Tip: Salesforce Employee Service Management automates HR workflows, so your team spends less time on admin. How to Structure Your SMB for Success You don’t need corporate-level bureaucracy—just clarity, flexibility, and the right tools. 5 Steps to Build a Scalable Team Structure: 1️⃣ Identify core functions – What’s essential? (Sales, finance, marketing, ops, support, HR).2️⃣ Assign (or outsource) key roles – No need to hire full-time if a tool or freelancer can do it.3️⃣ Encourage cross-team collaboration – Break silos; share insights.4️⃣ Automate repetitive work – Free up time for high-value tasks.5️⃣ Stay adaptable – Evolve roles as you grow. The Bottom Line:With lean teams + smart tech, SMBs can punch above their weight. Starter Suite brings sales, service, marketing, and operations into one platform—so you stay nimble as you scale. 🚀 Want to optimize your small biz? Explore Salesforce for SMBs #SmallBusiness #Entrepreneurship #Salesforce #AI #BusinessGrowth 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

April 17, 2025in Agentforce Platform, Generative AI, Marketing Automation, Salesforce0 Comments

09Apr

5 Mindset Shifts That Revolutionized Salesforce Help with AI

When Salesforce challenged us to reinvent our help portal in just five days, we didn’t just redesign a UI—we reimagined how AI could transform customer support. Here’s how we turned Salesforce Help into an intuitive, agent-driven experience—and the key mindset shifts that made it possible. The Challenge: A Help Portal at Scale Salesforce Help serves 60 million annual visitors across 750,000+ articles in 18 languages. Yet, despite this vast knowledge base: Our mission? Reduce friction, boost self-service, and make help feel human—fast. From Static Portal to AI-Powered Guide: 5 Key Shifts 1. From Navigation to Conversation Old Approach: New Mindset: Result: Faster resolutions, fewer drop-offs. 2. From Content Management to Knowledge Engineering Old Approach: New Mindset: Result: Smarter self-service, fewer support tickets. 3. From Siloed Teams to Rapid Collaboration Old Approach: New Mindset: Result: A full UI overhaul in 5 days. 4. From Rigid UI to Adaptive Engagement Old Approach: New Mindset: Result: Feels like a helpful conversation, not a maze. 5. From Feature-Centric to Outcome-Driven Old Approach: New Mindset: Result: Cleaner, faster, higher adoption. The Impact: A Blueprint for AI-Powered Help Watch the full story: Salesforce+ Video Your Turn: How Will You Rethink Support? AI isn’t just about adding chatbots—it’s about redesigning experiences around how people actually seek help. Ask yourself: Less is more. Clarity is king. And sometimes, a 5-day sprint can change everything. 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

April 9, 2025in Agentforce Platform, Data, Google, Salesforce

31Mar

Salesforce’s 7 Top AI Sales Tools and Software for 2025

Based on Erin Hueffner, Writer, Salesblazer. article Your AI Sales Tools can double the sales calls generated from inbound leads! They can convert 40% more customers! AI-driven automation can eliminate many time-consuming and repetitive tasks and accelerate workflows. Sales AI tools often use algorithms to automate sales operations, like adding information from customer calls and emails to a CRM database. AI can also streamline several key follow-ups to prospects after a sales call. Reclaim Your Selling Time with AI Sales Tools What if you could spend less time on admin and more time closing deals? Manual tasks like updating CRMs, drafting emails, and compiling reports drain productivity—and our State of Sales research shows 67% of reps risk missing quotas, partly due to inefficient tech stacks. AI sales tools are changing the game. By automating workflows, analyzing data, and personalizing outreach, they empower teams to focus on what truly drives revenue: building relationships and sealing deals. Here’s how AI is revolutionizing sales—and the top tools to help your team work smarter. What Are AI Sales Tools? AI sales tools leverage automation, machine learning, and predictive analytics to:✅ Eliminate busywork (data entry, scheduling, note-taking)✅ Uncover insights (lead scoring, deal forecasts, market trends)✅ Enhance engagement (personalized emails, call coaching, real-time recommendations) For SMBs, AI acts as a smart assistant; for enterprises, it scales into predictive forecasting and pipeline optimization. The result? Reps spend less time on logistics and more time selling. How AI Sales Tools Work These tools integrate with your CRM to: The impact is clear: 83% of AI-powered teams grew revenue last year vs. 66% without AI. 9 Top AI Sales Tools (Rated 4+ Stars) Curated from G2 and Capterra, these platforms excel in usability, features, and ROI. 1. Salesforce (Sales Cloud) 2. Outreach 3. Apollo.io 4. Pipedrive 5. Gong 6. Salesloft 7. APE AI 8. Clari 9. Instantly AI 5 Must-Have AI Sales Tool Features Trends Shaping AI Sales Tools in 2024 🔮 Deeper Analytics: AI spots hidden pipeline opportunities.🤖 Autonomous Assistants: Tools like Agentforce handle lead nurturing 24/7.🔒 Tighter Security: Encryption and privacy controls are non-negotiable.🛠️ Bias Guardrails: AI outputs are fact-checked to maintain trust. How to Choose the Right Tool The Bottom Line AI sales tools aren’t just about efficiency—they’re revenue multipliers. By automating grunt work and sharpening strategy, they help teams: Ready to upgrade your sales stack? The right AI tool can turn missed quotas into exceeded targets. Key Takeaways: Which sales task would you automate first? Let us know in the comments. 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

March 31, 2025in AI Tools, Data, Enterprise, Generative AI, Salesforce

19Mar

How Salesforce’s 5-Level Framework for AI Agents Cuts Through the Hype

The tech industry is abuzz with talk of AI agents, but what can they actually accomplish? Amid the noise, Salesforce has introduced a practical five-level framework—the Agentic Maturity Model—that clarifies the real capabilities and limitations of today’s AI agents. The Problem with AI Agent Hype AI agents are often overpromised, vaguely defined, and limited by ecosystem barriers. Major players like Microsoft and Google tout AI agents for everything from enterprise workflows to personal computing, yet many of these tools remain constrained by data silos and interoperability issues. Salesforce’s framework provides a structured way to assess AI agent maturity, helping businesses distinguish between basic automation and truly intelligent, cross-platform AI systems. The 5 Levels of AI Agent Maturity Level 0: Fixed Rules & Repetitive Tasks Level 1: Information Retrieval Agents Level 2: Simple Orchestration, Single Domain Level 3: Complex Orchestration, Multiple Domains Level 4: Multi-Agent Orchestration Why This Framework Matters Salesforce’s model demystifies AI agent capabilities, helping businesses:✅ Evaluate vendor claims (Is it Level 2 or Level 4?).✅ Plan AI adoption (Start with Level 0 automation, then scale up).✅ Avoid ecosystem lock-in by understanding data interoperability challenges. Final Verdict: A Much-Needed Reality Check While AI agents hold immense potential, most current implementations are far from autonomous. Salesforce’s framework provides a clear, honest roadmap—helping businesses cut through the hype and adopt AI agents strategically. For now, Levels 0-2 are widely achievable, while Levels 3-4 remain aspirational for most organizations. The key takeaway? AI agents are evolving, but true cross-platform intelligence is still a work in progress. What’s Next?Businesses should: Salesforce’s framework is a wake-up call: AI agents are powerful, but not magic. The future lies in practical, phased adoption—not blind hype. 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

March 19, 2025in Agentforce Platform, Data, Enterprise, Google, Salesforce

12Feb

Prompt Decorators

Prompt Decorators: A Structured Approach to Enhancing AI Responses Artificial intelligence has transformed how we interact with technology, offering powerful capabilities in content generation, research, and problem-solving. However, the quality of AI responses often hinges on how effectively users craft their prompts. Many encounter challenges such as vague answers, inconsistent outputs, and the need for repetitive refinement. Prompt Decorators provide a solution—structured prefixes that guide AI models to generate clearer, more logical, and better-organized responses. Inspired by Python decorators, this method standardizes prompt engineering, making AI interactions more efficient and reliable. The Challenge of AI Prompting While AI models like ChatGPT excel at generating human-like text, their outputs can vary widely based on prompt phrasing. Common issues include: Without a systematic approach, users waste time fine-tuning prompts instead of getting useful answers. What Are Prompt Decorators? Prompt Decorators are simple prefixes added to prompts to modify AI behavior. They enforce structured reasoning, improve accuracy, and customize responses. Example Without a Decorator: “Suggest a name for an AI YouTube channel.”→ The AI may return a basic list of names without justification. Example With +++Reasoning Decorator: “+++Reasoning Suggest a name for an AI YouTube channel.”→ The AI first explains its naming criteria (e.g., clarity, memorability, relevance) before generating suggestions. Key Prompt Decorators & Their Uses Decorator Function Example Use Case +++Reasoning Forces AI to explain logic before answering “+++Reasoning What’s the best AI model for text generation?” +++StepByStep Breaks complex tasks into clear steps “+++StepByStep How do I fine-tune an LLM?” +++Debate Presents pros and cons for balanced discussion “+++Debate Is cryptocurrency a good investment?” +++Critique Evaluates strengths/weaknesses before suggesting improvements “+++Critique Analyze the pros and cons of online education.” +++Refine(N) Iteratively improves responses (N = refinement rounds) “+++Refine(3) Write a tagline for an AI startup.” +++CiteSources Includes references for claims “+++CiteSources Who invented the printing press?” +++FactCheck Prioritizes verified information “+++FactCheck What are the health benefits of coffee?” +++OutputFormat(FMT) Structures responses (JSON, Markdown, etc.) “+++OutputFormat(JSON) List top AI trends in 2024.” +++Tone(STYLE) Adjusts response tone (formal, casual, etc.) “+++Tone(Formal) Write an email requesting a deadline extension.” Why Use Prompt Decorators? Real-World Applications The Future of Prompt Decorators As AI evolves, Prompt Decorators could: Conclusion Prompt Decorators offer a simple yet powerful way to enhance AI interactions. By integrating structured directives, users can achieve more reliable, insightful, and actionable outputs—reducing frustration and unlocking AI’s full 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

February 12, 2025in Artificial Intelligence, Technology

22Jan

Understanding AI Agents

Understanding AI Agents: How They Differ from Copilots and Assistants The AI landscape is evolving rapidly, with terms like AI agents, copilots, and assistants often used interchangeably. But what truly distinguishes them? This analysis clarifies their differences, maps them against real-world AI tools, and identifies gaps in today’s market. Why This Distinction Matters Understanding AI agent capabilities is crucial for: By 2025, AI agents are expected to become enterprise-ready, with the market projected to grow 45% annually, reaching $47 billion by 2030 (MarketsandMarkets). Microsoft CEO Satya Nadella even suggests that agentic applications could replace traditional SaaS. But what makes an AI tool an agent rather than just a copilot or assistant? Defining AI Agents, Copilots, and Assistants 1. AI Agents: Autonomous Goal-Seekers Gartner’s definition (2024): “AI agents are autonomous or semi-autonomous software entities that use AI techniques to perceive, make decisions, take actions, and achieve goals in their digital or physical environments.” Key capabilities:✔ Autonomy – Acts independently.✔ Goal-driven behavior – Works toward broader objectives.✔ Environmental interaction – Uses tools (actions), sensors (perception), and data retrieval.✔ Learning & memory – Adapts over time.✔ Proactivity – Acts on triggers, not just user commands. Example: Agentforce (Salesforce’s AI agent) autonomously creates marketing campaigns by analyzing CRM data. 2. AI Copilots: Collaborative Partners Microsoft’s perspective: “Copilots enhance decision-making by offering context-specific recommendations and work collaboratively with humans.” Key differences from agents: Example: Cursor (AI coding assistant) helps developers by auto-completing and refining code in real time. 3. AI Assistants: Task-Based Helpers Example: ChatGPT (basic version) answers questions but doesn’t autonomously execute tasks. The Agent-Copilot-Assistant Spectrum Feature AI Assistant AI Copilot AI Agent Autonomy ❌ No ⚠️ Semi ✅ Yes Goal-driven ❌ No ⚠️ Partial ✅ Yes Tools & Actions ❌ No ⚠️ Limited ✅ Yes Sensors/Triggers ❌ No ❌ No ✅ Yes Memory & Learning ❌ No ✅ Yes ✅ Yes Proactivity ❌ No ⚠️ Some ✅ Yes Current Market Gaps: Where AI Tools Fall Short Despite advancements, most AI tools today don’t fully meet agent or copilot criteria: 1. Most “Agents” Lack True Autonomy 2. Copilots Often Lack Memory 3. Assistants Dominate the Market Many popular AI tools (Grammarly, Canva AI, Remove.bg) are task-specific assistants, not true copilots or agents. The Future of AI Agents & Copilots Key Takeaways ✔ AI agents act autonomously, copilots collaborate, and assistants follow commands.✔ Today’s “agents” are semi-autonomous—true autonomy is still evolving.✔ Most AI tools are still assistants, with only a few (like GitHub Copilot) qualifying as copilots.✔ Memory, proactivity, and sensors are the biggest gaps in current AI offerings. For businesses and developers, this presents an opportunity: those who build true copilots and safe agents will lead the next wave of AI adoption. 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

January 22, 2025in AI Tools, Data, Enterprise, Salesforce

07Nov

AI for Product Builders

Practical AI for Product Builders: Beyond the Hype Cutting Through the White AI Noise AI dominates tech conversations—yet much of the discussion feels abstract. What’s often missing is a practical guide for integrating AI into real products. How can AI: ✔ Enhance user experiences?✔ Enable new capabilities?✔ Improve existing features (faster/cheaper/better)?✔ And—just as importantly—when shouldn’t you use it? As product and UX professionals, we solve user problems with the best tools available. AI expands that toolkit in surprising ways. This guide breaks down key techniques so you can confidently say: AI Basics: What We’re Really Talking About Large Language Models (LLMs) = Word Prediction Engines When people say “AI” today, they usually mean LLMs—the technology behind ChatGPT, Claude, Gemini, and others. How they work: Comparison: An huge team of forgetful interns. Each time you chat, you’re talking to a new intern who reads the previous conversation before responding. Key limitations: Moving Beyond Chatbots Chatbots were the first wave of AI products, but conversational interfaces aren’t always the best solution. Example: AI Image Editing Problem: You generate an image of a cat in a café but want to tweak one poster. ✅ GUI + AI (e.g., Photoshop Generative Fill) ❌ Chat-only (e.g., ChatGPT + DALL-E) Lesson: Direct manipulation (GUI) + AI > Chat-only interfaces for many use cases. The AI Toolbox: Key Techniques 1. LLM Prompting What: Basic text-in, text-out AI (like ChatGPT). Best for: Limitations: 2. Image Generation What: Models like DALL-E, Imagen, Midjourney create images from text. Best for: Key Insight: 3. Structured Output & Tool Use Problem: Raw LLM output is messy for apps. Solution: Force responses into predefined formats (e.g., JSON). Example: Tool Use: Lets LLMs “choose” next actions (e.g., search orders vs. ask clarifying questions). 4. Embeddings What: Convert text into numerical vectors (“meaning coordinates”). Why it matters: Use cases: 5. Retrieval-Augmented Generation (RAG) What: Combine LLMs with your own data. How it works: Benefits: When Not to Use AI Red Flags in AI Product Design 🚩 “We need an AI strategy” → Focus on user needs, not tech for tech’s sake.🚩 Sparkly “AI” buttons → AI should feel seamless, not tacked-on. Remember: Many “smart” features (e.g., Apple’s “Magic” tools) don’t require AI. The Path Forward AI enables new possibilities, but great products still solve real problems. Use these tools to: AI isn’t magic. But used thoughtfully, it can help build products that are. 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

November 7, 2024in AI Tools, Data, Enterprise, Technology

13Jun

Building Trust in AI-Powered CRM

Building Trust in AI-Powered CRM: The Key to Successful Adoption Why Education and Trust Matter in AI-Driven CRM To maximize the benefits of AI-powered CRM systems, organizations must focus on two critical pillars: Despite growing AI adoption, Forrester’s research reveals significant gaps: 1. The AI Knowledge Gap 2. Trust Barriers in Generative AI Top concerns delaying genAI adoption:🔒 Security risks – Fear of leaking customer PII or confidential data⚖️ Compliance risks – Potential violations of GDPR, CCPA, or copyright laws✍️ Output reliability – AI-generated content may be misleading or inaccurate “Deploying unchecked AI responses can damage brand credibility. Human oversight remains essential.” 3. AI-Powered CRM: Security as a Competitive Advantage Businesses prioritize vendors who proactively address: How to Build AI Confidence in Your Organization For Employees ✔ Role-based AI training – Tailor education to sales, service, and marketing teams✔ Hands-on sandbox environments – Let teams test AI tools risk-free✔ Clear guidelines – Define approved vs. restricted AI use cases For Customers ✔ Transparent data policies – Explain how AI improves their experience✔ Opt-in controls – Let users manage data-sharing preferences✔ Human-AI collaboration – Ensure sensitive interactions always have human review The Path Forward While AI-powered CRM adoption continues rising, trust remains the differentiator. Companies that:✅ Invest in AI education✅ Prioritize responsible data practices✅ Choose vendors with robust security …will gain a competitive edge—turning AI skepticism into customer and employee confidence. Ready to implement AI-powered CRM the right way? Let Tectonic lead the way! 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

June 13, 2024in AI Tools, Data, Generative AI, Laws

08Jun

Salesforce Experience Cloud

Experience Cloud: Elevating Digital Experiences Salesforce Experience Cloud stands as the quintessential tool for constructing versatile platforms that facilitate engagement with your business by customers, partners, and employees alike. Whether you aim to establish portals, forums, websites, or help centers, Experience Cloud empowers you to create these directly within the Salesforce platform, ensuring seamless integration with all your CRM data. Operating on a low-code platform, it provides the capability to effortlessly design stunning platforms through intuitive drag-and-drop functionality. Introducing Experience Cloud Experience Cloud serves as the ultimate platform for nurturing customer relationships and propelling revenue growth. With its array of pre-built apps, intuitive drag-and-drop tools, and low-code web capabilities, it enables the creation of captivating digital experiences with ease. Yes, Salesforce Community Cloud is now rebranded as Salesforce Experience Cloud, reflecting the platform’s expanded functionalities beyond traditional community-building features to encompass a broader spectrum of digital experience creation tools. Effortless Creation Empower your team to swiftly iterate and develop secure, immersive digital experiences using pre-built apps and low-code web tools. Data Excellence Leverage connected data and AI-driven processes to deliver personalized content, fostering stronger relationships by ensuring a single, reliable source of truth. Team Collaboration and Customer Clarity Unify your teams and provide your customers with a clear pathway forward by delivering seamless journeys across various domains, including sales, service, marketing, and commerce. Key Features Optimize your return on experience by rapidly deploying personalized digital experiences that seamlessly span multiple channels. Illustration: Easily build platforms such as a consumer help center using intuitive low-code blocks, shown in a phone view. Craft Your Experience Design the perfect experience tailored to your needs, whether it’s for tablets, mobile devices, or desktops. Experience Cloud’s builder and consumer views provide the flexibility you need. Start Building Your Experience What type of experience are you aiming to create? Experience Cloud offers a wide range of possibilities, from crafting a comprehensive help center to developing engaging mobile applications. Salesforce Experience Cloud: Transforming Digital Experiences Salesforce Experience Cloud empowers you to craft branded digital experiences, facilitating seamless information sharing and collaboration with essential stakeholders in your business processes, whether they are customers, partners, or employees. Whether you label it as a portal, help forum, support community, or otherwise, an Experience Cloud site serves as a central hub for engaging with the individuals vital to your organization. Required Editions and Versatility Available across both Salesforce Classic and Lightning Experience, Experience Cloud is accessible in Enterprise, Performance, Unlimited, and Developer Editions. You have the flexibility to create multiple sites tailored to different purposes within your organization, seamlessly transitioning between them. Understanding the Basics and Planning Your Implementation Experience Cloud offers a suite of flexible, robust features that enable you to design digital experiences and branded environments for various stakeholders. Whether it’s a portal, help center, or mobile app, you can customize your site with minimal code or opt for a programmatic approach. Before diving into development, it’s advisable to plan meticulously, considering the specific features required to achieve your desired site functionality and productivity. Setting Up and Configuring Your Org Prepare your Salesforce org for Experience Cloud sites by completing essential tasks in Salesforce Setup, ensuring seamless integration with customer- and partner-facing platforms. From enabling digital experiences to configuring org settings, proper setup is crucial for a successful implementation. Building and Customizing Your Site Choose from a range of preconfigured templates to kickstart your site creation process. Customize your site to align with your organization’s unique requirements and branding. Ensuring Site Security Protect your Experience Cloud site by enabling clickjack protection, user authentication, data encryption, and safeguarding against malicious resources. Leverage various settings and permissions to maintain data security and privacy for both your organization and its customers. Deploying and Managing Your Site Test your Experience Cloud site thoroughly in a sandbox environment before deploying it to production. Use change sets or Metadata API for seamless migration between orgs, considering factors such as complexity and ALM model. Utilizing Reporting and Considerations Leverage reporting tools to gain insights into site performance and member engagement trends. Consider various factors, such as site management and moderation, when creating and managing sites with Experience Cloud. Salesforce Experience Cloud Developer: A Quick Overview A Salesforce Experience Cloud Developer is responsible for designing, developing, and maintaining web applications on the Salesforce Experience Cloud platform. They collaborate with cross-functional teams to define and implement features and functionality, ensuring scalable and reliable backend systems support web applications. 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

June 8, 2023in Data, Enterprise, Salesforce, Salesforce Experience Cloud

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