Future on Salesforce: Smarter AI-Native Applications

Enterprise apps are evolving from reactive systems of record to proactive, AI-augmented engines of decision-making. At the heart of this transformation lies a critical shift: your CRM isn’t just storing data-it’s activating it across channels, roles, and real-time workflows.

If you're building on Salesforce, the shift is already underway.

Recent advancements in Data Cloud, Apex/API control, and Lightning Web Components (LWCs) are giving developers the tools to build intelligent, composable, and context-aware applications. Paired with generative AI and Agent force capabilities (which we explored in detail in our Agent force blog), these new features mark a pivotal moment in CRM development.

This blog takes you beyond the surface to explore how Salesforce’s latest tooling helps developers and architects build smarter—from integrating unstructured data and mobile personalization to designing AI-native frontends and tightening Apex governance.

Data Cloud: Turning Customer Data into a Real-Time AI Engine

1. Vector Databases: Making Your Data Work Like an AI

Salesforce’s new vector database integration introduces semantic search and retrieval-augmented generation (RAG) into the Salesforce ecosystem.

Why it matters:

• Store unstructured data like reviews, chats, documents, and notes
• Use semantic similarity to surface the most relevant context not just keyword matches
• Power smarter GenAI experiences that are grounded in actual customer language

Pro Insight: Traditional relational search works well for structured CRM data, but semantic vector databases unlock relevance in open-text formats. You’re no longer matching fields you’re understanding intent.

Real-world application: A support center embeds vector search into its knowledge base, enabling AI agents to retrieve past resolutions even when they are phrased differently. A query like “error on save after merge” might match “merge conflict resolution for save issue,” even if those exact words never appear.

Getting Started:

• Enable vector support in Data Cloud.
• Use embeddings from a pre-trained model (e.g., Salesforce’s built-in) or bring your own.
• Store embeddings alongside raw data objects.
• Create prompts that include top-N matches using external object references.

2. Mobile App Activation: Your Data, Delivered at the Edge

Data Cloud now enables event-driven, personalized experiences on mobile and web apps. Whether you're delivering support, marketing, or commerce experiences, this bridges the gap between central data and edge engagement.

Use Case: A healthcare app utilizes a patient’s latest activity and appointment history to provide contextual nudges, such as confirming upcoming visits or scheduling wellness follow-ups based on behavioral and geographic triggers.

Implementation Highlights:

• Set up streaming connections between Data Cloud and mobile app data layers.
• Use platform events or outbound messages to sync context changes.
• Combine with Experience Cloud for seamless UX.

Pro Tip: Focus on latency optimization. Use Data Cloud’s real-time segments and mobile SDKs to serve decisions in under 100ms when possible.

Apex & API: Building Clean, Modern, and Maintainable Codebases

3. API Version Enforcement: A Crucial Shift Toward Modernization

Salesforce’s planned deprecation of API versions 21.0 to 30.0 forces developers to rethink legacy integrations. While daunting, it’s a major step toward a cleaner, future-ready codebase.

What to do now:

• Run the Event Log Browser to audit calls to deprecated endpoints.
• Identify integrations by package or middleware.
• Plan updates using the Version Retirement Dashboard.
• Refactor with REST or GraphQL where available.

Pro Insight: API modernization isn’t just technical—it’s strategic. The fewer brittle endpoints you maintain, the more agile your release cycles become.

Recommended Workflow:

• Isolate API usage by version across all environments.
• Refactor in sandboxes and validate in test environments.
• Leverage Postman collections or CLI tools for regression testing.
• Document API version compliance in your internal developer wiki.

4. Smarter Apex Workflows and Observability

Apex is more testable and observable than ever—without adding complexity.

Key Enhancements:

• Integration with Salesforce CLI test runners
• Improved Apex log readability and metadata indexing
• Extended support for enforcing test coverage on CI/CD triggers

Use Case: A financial services company introduces Apex telemetry to monitor approval process automations. When a bug occurs in production, the team isolates the issue to a recent API change detected by Apex coverage deltas.

Getting Started with Tooling:

• Install the latest DX plugins in VS Code.
• Use sfdx force:apex:test: run for batch validations.
• Visualize test failures alongside linting reports.
• Enforce minimum coverage via GitHub Actions or CircleCI.

Lightning Web Components: Building UI That Understands Context

5. Custom LWCs for AI Workflows: Frontends that Think

Custom LWCs that integrate with AI workflows give developers unprecedented control over UI logic.

Key Features:

• Context-aware inputs that evolve based on agent feedback
• Dynamic rendering for decision trees and smart suggestions
• Seamless integration with backend AI via pub/sub messaging

Use Case: A travel insurance portal uses custom LWCs to guide agents through AI-recommended claim resolutions. As the user interacts, the UI evolves, offering additional document requests, call scripts, or escalation flows all powered by Agent force in the background.

Developer Tips:

• Use Lightning Messaging Service for agent<>component communication.
• Design component state to accept dynamic JSON schema definitions.
• Use conditional rendering blocks for adaptive UX.

6. Lightning Type Bundles: Define Once, Render Everywhere

Lightning Type Bundles let you formalize how data and UI co-exist. This new abstraction layer helps define:

• Field-level behaviors
• Contextual display logic
• Renderers tied to persona, device, or locale

Use Case: A manufacturing company builds reusable bundles for order intake. Whether used in a B2B portal, field agent tablet app, or AI agent UI, the bundle ensures consistent logic and experience.

Why It Matters: In multi-channel environments, maintaining consistent business logic across UIs is hard. Bundles provide structure, validation, and scalability.

Pro Tip: Pair type bundles with unlocked packages to distribute across sandboxes and teams.

Bringing It All Together: Architectures That Scale

Example 1: Service Console with AI-Augmented Decisions

• Data Cloud pulls customer history, CSAT scores, and active contracts
• Vector DB surfaces similar issues from the past
• Agent force recommends next actions and generates suggested replies
• LWC component displays all this in a single panel
• Apex logs track usage for compliance

Impact: Reduced handling time, improved first-call resolution, measurable agent productivity gains.

Example 2: Mobile Shopping with Real-Time Personalization

• Shopper launches a mobile app
• Data Cloud provides in-store context and behavior history
• AI agent builds a dynamic shopping journey
• External Object prompt queries product reviews from a third-party API
• Custom UI renders tailored bundles with call-to-action buttons

Impact: Increased cart value, lower bounce rate, stronger mobile conversion.

Developers: It’s Time to Build with Context

What defines this evolution isn’t just new APIs or shiny tools—it’s that your app stack now understands context.

With the right architecture:

• Data Cloud powers real-time decisions
• Apex & API enforcement ensure stability and trust
• LWCs and Lightning Types deliver intelligent UIs
• And Agent Force turns logic into smart, responsive action

Together, this forms a complete loop: sense, decide, act, and adapt.

Whether you're in retail, healthcare, finance, or public sector—this is how Salesforce wants you to build.

Learn More: Full Summer ’25 Feature Coverage

Looking for the complete release breakdown—including Einstein Copilot updates, Service Cloud enhancements, and platform-wide changes? We’ve got you covered: What’s New in Salesforce Summer ’25

FAQs

1. How will AI-native Salesforce apps improve business outcomes?

They deliver faster decisions, real-time personalization, and automation that reduce costs and drive growth.

2. What should CIOs prioritize when adopting Salesforce AI?

Strong data governance, API modernization, and aligning AI with customer experience goals.

3. How does Salesforce Data Cloud support smarter apps?

It unifies customer data, adds vector search, and enables real-time actions across channels.

4. Why is Salesforce retiring old API versions?

To modernize integrations, improve security, and encourage REST/GraphQL adoption.

5. What role do Lightning Web Components (LWCs) play in AI workflows?

They power adaptive UIs that adjust dynamically based on AI insights and context.