In this Dreamforce 2025 keynote analysis, theCUBE’s John Furrier is joined by analysts George Gilbert and Gemma Allen to unpack Salesforce’s next leap into the agentic enterprise era. The trio breaks down how Agentforce, Salesforce’s unified platform for intelligent agents, combines real-time Data Cloud context, Slack as the agent surface and integrated governance through MuleSoft to transform AI hype into operational reality. Gilbert explains why this moment may mark the biggest enterprise software shift in 50 years – unifying customer data, actions and observability under one stack.

The discussion explores Agentforce’s fourth release, new Command Center capabilities and the rise of “Datadog for agents” observability that captures reasoning traces and decisions for real-time analysis. They dive into how Agentforce and Data Cloud bridge business and IT roles, enabling organizations to deploy agents faster while maintaining guardrails around data, actions and governance. Allen offers a grounded view from Wall Street, emphasizing how enterprise buyers are shifting from AI demos to measurable business outcomes, while Furrier highlights the ecosystem effect that keeps Salesforce’s innovation grounded in customer reality.

From Klarna’s early agentic success to Dell’s new supply chain use case, the conversation captures Salesforce’s evolution from customer 360 to a full-scale data infrastructure and enterprise application platform company. It’s an essential watch for anyone tracking how data, trust and automation are converging into the next generation of enterprise productivity.

In this Dreamforce segment, Salesforce leaders Jayesh Govindarajan, executive vice president of software engineering, and Christophe Coenraets, senior vice president of technical audience relations, join theCUBE’s John Furrier and George Gilbert to unpack how enterprise-grade “vibe coding,” grounded in trust, security and governance, is reshaping developer productivity. The discussion dives into the craftsmanship required to take agents from demo to production, including context engineering, persona design and an emerging agent development life cycle spanning Studio, Testing Center and Agent Observability. Govindarajan shares adoption momentum and lessons from getting agents reliably into production with the right balance of determinism and creativity, while Coenraets explains how enterprise vibe coding aligns generated code with org metadata, validation rules and security models.

The conversation also explores Agentforce in action – highlighting role-based workflows, deterministic orchestration via an agent scripting language and “fleets of agents” coordinating across sales and service tasks. Real-world patterns come to life through examples like a Williams-Sonoma “sous chef” agent moving from creative recipe assistance to transactional commerce, and through developer-facing extensions such as MCP resources for external data and actions. The team closes by framing the shift to conversational UX as a default experience and connecting it to Salesforce’s data foundation with Data 360 – all pointing to how agentic automation becomes reliable day-two operations.

At Dreamforce, Paul Tatum, executive vice president of global public sector solutions at Salesforce, joins theCUBE’s Gemma Allen and George Gilbert to unpack how AI and agents are moving from experiments to mission impact in government. Tatum explains why agencies are leaning in responsibly – spurred by recent U.S. AI directives and RFPs/RFIs that now mandate AI capabilities – while still insisting on standards, compliance and security. He shares real-world citizen-service pain points (think CMS.gov/IRS.gov “help” pages and 4,000-page Medicare/Medicaid policy PDFs) and how Agentforce plus large language models can read policies, ground responses and augment overworked civil servants for faster, more consistent adjudication, always with a human in the loop.

The discussion explores Salesforce’s approach to scaling the “agentic enterprise” in the public sector: start from existing systems of record on Salesforce and surround them with agents, use Data Cloud’s “zero-copy” data fabric to harmonize siloed information without multi-year migrations, and prioritize trust and governance with FedRAMP accreditation covering the full Agentforce stack, Data Cloud and the trust layer, including SLAs for vulnerability remediation. Tatum predicts the government will become the largest user of agentic technology because public policies are published and machine-readable, making this a compelling arena to measure what’s production-ready, how adoption happens internally vs. externally, where approvals remain essential and where early automation can relieve backlogs before tackling edge cases.

In this Dreamforce interview, James Watson, vice president of customer excellence at Smartsheet, joins theCUBE’s Gemma Allen and George Gilbert to break down how AI is transforming enterprise support operations – moving from reactive break-fix to proactive, predictive service. Watson details Smartsheet’s “front door / back door” approach: automated deflection for common questions and AI-assisted research for agents. He shares concrete outcomes including cutting complex case triage from six hours to six minutes, handling ~30% year-over-year growth in support volume without headcount increases and boosting deflection from 32% to 60%. The discussion also covers responsible AI adoption, reducing agent attrition (~20% to 6%) through better tools and engagement and early pilots for predictive maintenance across Smartsheet “constellations” of data nodes.

The conversation connects to theCUBE’s broader Dreamforce angles around agentic automation and trust. Watson explains how Smartsheet trained and continually QA’d models (from early Einstein AI work through Agentforce), using both structured knowledge and large volumes of unstructured historical cases, with human-in-the-loop review to prevent hallucinations and refine prompts, terminology and data sources. He highlights how Agentforce 360 and tighter context accelerate high-quality responses and enable more proactive, value-adding customer interactions – turning support insights into cross-sell, up-sell and training opportunities. Watson also cites a survey of 25,000+ customers reporting more than four hours of weekly productivity gains with Smartsheet, even before bringing these new agent capabilities into the workflow.

In this Dreamforce interview, Rahul Auradkar, executive vice president and general manager at Salesforce, joins theCUBE’s John Furrier and George Gilbert to unpack how Salesforce is operationalizing the agentic enterprise. Auradkar explains why “the AI revolution is a data revolution,” detailing Data 360 as the foundation that unifies context across structured and unstructured data – spanning Data Cloud, Tableau, MuleSoft’s Agent Fabric and (pending regulatory approval) Informatica. He shares how “intelligent context,” semantic understanding of documents, NL2SQL and policy-based data governance (tagging and masking) enable agents to act with precision. The discussion explores agent-to-agent governance via MuleSoft, governed enterprise search across sources such as Slack, Google and email, and the interoperability path using A2A and MCP so heterogeneous agents can work together under consistent controls.

The conversation dives into real-world progress and lessons. Auradkar cites Salesforce’s own help agent answering ~1.8M customer questions in under eight months and a small-footprint Data 360 deployment at MIMIT Healthcare saving over $1.5M annually. He addresses “agent exhaust” (telemetry and traces) feeding back into Data Cloud for continuous improvement, why context can trump sheer data volume (“needle in the haystack” and data fluidity), and how open standards plus an ecosystem – including Snowflake – accelerate time-to-value. Looking ahead, Auradkar outlines the expected benefits if the Informatica acquisition closes (catalog/metadata, MDM and governance) saying customers should see some immediate value alignment and deeper product integration on roughly a one-year horizon, all in service of measurable customer outcomes.

In this Dreamforce segment, Jesse Elizondo, assistant city manager for the City of Kyle (TX), joins theCUBE’s John Furrier and Gemma Allen to share how a fast-growing municipality is using Salesforce CRM and AI to transform resident services. Elizondo explains how Kyle scaled from a small town to ~70,000 residents and why public sector work (cyclical processes and abundant public information) is a natural fit for AI. He details how the city stood up a full-service 311 in six to eight months, then layered an AI system on top so residents can submit service requests 24/7 – even after call centers close.

The conversation dives into how an internal “brain stem” built from resolutions, ordinances, fees and even council-meeting captions empowers human call takers to resolve complex questions in one call (e.g., Wi-Fi tower rollouts). Elizondo outlines the leadership-driven culture change, security guardrails for sensitive data, measurable efficiency gains – such as cutting “what time is the pool/library open?” calls – and why consolidating siloed software and roles helped the city save more than the total 311 implementation cost. Set against the agentic AI momentum at Dreamforce, this is a candid look at what’s working now in the public sector, and how cities can “punch up” with AI to improve customer experience and accelerate projects.

In this Dreamforce segment, PepsiCo leaders Dave Dohnalik (senior vice president of technology strategy and enterprise products) and Johannes Evenblij Garza (senior vice president of global sales and marketing transformation) join theCUBE’s John Furrier and George Gilbert to share how a decade of AI work and a 10+ year Salesforce partnership are converging with Agentforce. They outline unifying ~100 contact centers on one system and consolidating data for a 360° customer view across more than 6 million customers who reach billions of consumers weekly – shifting from reactive service to proactive, “next best action” engagement.

The conversation breaks down the operating model: roughly 50/50 traditional ML and agents working with humans, frontline reps using mobile “digested briefs” to tailor assortments and promotions and automation removing routine work so teams can focus on higher-value tasks. They also detail five foundational bets over the past five years – enterprise data standards/quality, a strengthened transactional backbone, forward-leaning cybersecurity, simplified apps and platform standardization – that enable agents end-to-end across make-move-sell.

PepsiCo shares adoption lessons (e.g., suggested orders often taking ~10 cycles to fully land) and why they pivoted from scattered POCs to growth-anchored use cases. Developer response has been enthusiastic, with agents offloading repetitive tasks and unlocking more “brain cycles” for impact as deployments expand from Latin America and North America into Europe.

In this Dreamforce interview, Raphaelle d’Ornano joins Holger Mueller with theCUBE’s John Furrier and Gemma Allen to unpack Salesforce’s agentic roadmap and what it means for the enterprise. The discussion probes how Agentforce, real-time Data Cloud context and Slack as the primary surface come together under trust and governance – plus where gaps remain (from background business processes to ERP and supply chain). d’Ornano argues Salesforce should move beyond the “CRM” ticker and be recognized as an agentic orchestration platform, while Mueller pushes back that agents still rely on SaaS APIs and that Salesforce is expanding as a platform-and-apps company. You’ll hear candid takes on what’s production-ready, where customers are actually building and why execution, not just naming, will determine outcomes.

The conversation dives into observability and analytics for agents, the pace of customer-built agents (including pre-briefed upgrades), and the practical realities of “vibe coding” inside complex enterprises where human-in-the-loop and approvals remain key. The guests explore Slack’s role as a context engine and moat, real-time data patterns (latency, zero-copy claims, SLAs), and the emerging sprawl of data lakehouses. d’Ornano shares a Wall Street lens for separating AI enablers from AI adopters and her “AI optionality” framework for identifying orchestrators vs. the bypassed – alongside a nuanced view of “AI bubble” vs. “AI circularity” and market reactions to high-profile partnerships. The segment closes with letter grades for the keynote (ranging from B+ to A-) and a look at how category lines are being redrawn as agentic automation becomes routine business labor.