A lead comes in. No one opens a CRM. No one assigns it. No one follows up manually.
An AI agent reads it, qualifies it, drafts the outreach, and moves the next step forward inside the system itself. It doesn’t wait for direction. It works within the flow, alongside the tools teams already use.
TDX 2026 brings this shift into focus, where AI starts taking part in how enterprise work actually gets done, and where control, visibility, and trust begin to matter as much as capability.
TDX 2026 in San Francisco: A Full-Scale Developer Gathering
TDX 2026 brought the Salesforce ecosystem back to downtown San Francisco at Moscone West Convention Center on April 15–16, 2026. Positioned as a must-attend event for developers, it delivered depth with 400+ technical sessions, hands-on training, and 100+ demos and interactive experiences.
The audience ranged from developers and admins to architects, partners, and IT leaders, working across tracks focused on AI, data, vibe coding, and the core platform. A three-day Bootcamp at Salesforce Tower from April 12–14 added early access, giving attendees time with product experts before the main event began.
Major Announcements Setting the Direction for Enterprise AI
Salesforce introduced new tools to make AI agents practical in enterprise workflows.
AgentExchange Unifies the Agent Ecosystem
Salesforce introduced AgentExchange as a centralized marketplace that brings together AppExchange, Slack Marketplace, and the broader Agentforce ecosystem.
Instead of navigating separate environments, enterprise teams can access, deploy, and manage AI-driven solutions from a single, integrated layer across Salesforce and Slack.
Slack Becomes an Execution Interface
Work happens in Slack. Now, so do decisions.
Salesforce introduced new capabilities that bring AI agents directly into Slack, where teams already collaborate. Agents act alongside teams, not as separate tools, but as integrated participants in daily workflows.
Teams can trigger actions through Slackbot, deploy agents within minutes, and manage the entire agent ecosystem in one place. With Block Kit, interactions move from simple messages to structured, action-driven experiences.
Agentforce Experience Layer Powered by Headless 360
Interfaces are no longer the starting point. Experience is.
Salesforce introduced the Agentforce Experience Layer as the way AI-driven interactions are delivered across channels. It defines how agents present, respond, and interact with users across environments like Slack, voice, and WhatsApp. Instead of building separate front-end experiences, teams can create once and extend across surfaces.
Headless 360 powers what sits underneath.
Headless 360 opens up the entire Salesforce platform to AI agents through APIs, CLIs, and Model Context Protocol (MCP) tools, giving them direct access to data, logic, and workflows without being tied to a single interface.
Together, they create a connected system:
The experience layer controls how interactions appear across channels
Headless 360 enables agents to access and act on enterprise systems
Developers can build alongside AI using composable MCP tools
Experiences can be deployed wherever users already are
This structure separates experience from execution while keeping both connected through a unified system.
Explore how Tru supports enterprise teams with Salesforce Solutions designed for AI-driven workflows.
Agentforce Vibes 2.0 Makes Agent Building More Flexible
Agentforce Vibes 2.0 gives developers more control over how they build with AI agents.
Salesforce introduced two working styles:
Chat Mode for hands-on development
Planner Mode for larger tasks, where the agent plans and executes across multiple steps
The update also gives teams flexibility in how agents are powered. Developers can choose their agent harness, including options built on native SDKs from providers like Claude, OpenAI, Cline, and Maestra, with no vendor lock-in.
For enterprise teams, the bigger signal is control. Token management helps balance cost and execution. Discovery gives developers access to a growing library of rules, skills, commands, and subagents, making it easier to build, extend, and refine agent capabilities.
Work Modes Built for How Teams Operate
Agentic Mode: Executes tasks independently
Plan Mode: Breaks down tasks with developer review at each step
Ask Mode: Answers questions and supports decision-making
Debug Mode: Investigates issues and maps out fixes
Agent Script Brings Control to AI Agent Behavior
Agent Script introduces a structured way to make AI agents more predictable. Instead of relying only on natural language instructions, developers can define exact workflows using conditional logic, variables, and integrated data.
This allows teams to enforce critical steps, such as verifying customer data or checking conditions, without leaving it to interpretation. By combining generative AI with deterministic logic, Agent Script helps build agents that act consistently while still using AI for reasoning.
It also adds visibility into how agents operate, giving developers clearer insight into decisions and making it easier to refine performance over time.
What Enterprise Leaders Should Do Next
The announcements point to a practical shift in how enterprises approach AI. What matters now is how these systems are implemented, controlled, and applied inside day-to-day operations.
Embed agents in existing workflows: AI delivers value when it acts inside CRM, service and collaboration tools.
Treat data as a foundation: Headless 360 underscores that agents need structured, accessible data.
Adopt reusable agents: AgentExchange signals a move toward shared intelligence that shortens time to value.
Give developers control: Tools like Agent Script and Vibes 2.0 show that the future of AI is programmable and transparent.
Deploy AI agents across your workflows with our advanced AI Agent Development Services.
As AI Agents Take On Work, Who Holds Control?
As AI agents begin making decisions inside workflows, governance emerges as the real challenge. Enterprises must decide who sets rules, approves exceptions and maintains accountability. Probabilistic agents can create risk and inconsistency without oversight.
Tru’s AI Council helps organizations implement AI with end‑to‑end governance. We define decision frameworks, align data policies and set guardrails for autonomous actions. Our focus is transparency and accountability, enabling enterprises to build trust and adoption.
Conclusion
AI agents are moving into the core of enterprise systems, where decisions, actions, and outcomes connect in real time. TDX 2026 shows that the real advantage will not come from adopting these systems, but from how they are structured, governed, and applied inside everyday workflows. As agents take on more responsibility, enterprises will need to rethink ownership, control, and accountability at every level. The next phase of AI will be defined by one thing: how confidently organizations let these systems act on their behalf.
Build AI-Driven Salesforce Systems With Tru
Contact Our TeamReferences:
Salesforce. TDX 2026 Live Blog.
Salesforce. TrailblazerDX (TDX) Official Website.
Salesforce. TDX 2026 Session Catalog.
Frequently Asked Questions About Salesforce TDX 2026
Salesforce TDX 2026 took place on April 15–16, 2026, at the Moscone West Convention Center in San Francisco, with a pre-event Bootcamp held from April 12–14 at Salesforce Tower.
Key announcements included AgentExchange, Headless 360, Agentforce Experience Layer, Agentforce Vibes 2.0, and Agent Script. These updates focus on integrating AI agents into enterprise workflows with better control and flexibility.
AgentExchange is a centralized marketplace that brings together AppExchange, Slack Marketplace, and Agentforce. It allows enterprises to discover, deploy, and manage AI-driven solutions from a single platform.
Headless 360 is a framework that gives AI agents direct access to Salesforce systems through APIs, CLIs, and MCP tools. It enables agents to interact with data and workflows without relying on traditional user interfaces.
Agent Script improves AI consistency by allowing developers to define structured workflows using logic, variables, and data. This ensures critical steps are followed and reduces reliance on unpredictable AI responses.
