Volume 343, Issue 3 · 6 articles from 2 issues
Salesforce Platform Winter '27 adds headless agent workflows, MCP Risk Scores and governance for agent-generated code.
Salesforce highlights the top development and security features in the Salesforce Platform Winter '27 release, rolling out after Dreamforce, including the Agentic Developer Lifecycle for provisioning, testing and deploying headless agent workflows without a UI.
MCP Risk Scores automatically flag and block high-risk third-party MCP servers.
The release also adds compliance and audit controls to govern agent-generated code end to end, plus a Headless Experience Layer for universal UI.
Salesforce argues AI fluency is now baseline for early-career hires, while soft skills are what set candidates apart.
Salesforce says AI fluency is no longer a differentiator for early-career talent but a baseline expectation, citing its Futureforce Emerging Talent Playbook finding that early-career professionals are four times more likely to use AI daily and deliver results faster.
With everyone using the same tools, the post argues soft skills such as interpersonal connection and strategic thinking are what turn AI output into business impact.
It also describes reverse mentorship, in which early-career hires help close AI fluency gaps across teams.
A jargon-free primer explaining what a CRM is and how AI makes it accessible to non-technical small business owners.
Salesforce's small business blog offers a plain-language explanation of customer relationship management software for business owners who are not technical experts, arguing that the boom in AI has made business technology easier to understand and use.
The post breaks down what a CRM does at its core without technical jargon or buzzwords.
It points readers to further resources on getting started with CRM in a small business.
Salesforce security explains how it triages the flood of vulnerability findings that frontier models and agentic harnesses now surface.
Salesforce's security team says frontier AI models combined with an agentic harness now surface more real, exploitable findings than engineering teams can absorb, and because discovery has accelerated faster than the rest of the lifecycle, the hard question has moved downstream to prioritization.
Validation still depends on environment access, credentials and expert judgment, and remediation follows established engineering processes.
The post describes how Salesforce decides which findings deserve engineering attention and on what timeline.
Salesforce's Hunter is an outbound sales agent in Sales Cloud that plans pipeline work, personalizes outreach and asks reps for approval.
At Dreamforce, Salesforce introduced Hunter, an outbound sales agent for Sales Cloud that turns sellers' goals into plans by finding accounts and contacts, personalizing outreach, preparing follow-ups, and creating and updating opportunities.
It learns a team's sales motion from calls, emails and notes, works within existing permissions and approval rules, and keeps memory on accounts, contacts and opportunities, while showing its reasoning and asking for approval on judgment calls.
It also studies the patterns behind the strongest deals.
ZoomInfo, Demandbase and Apollo are flagship data partners supplying verified company and contact data, intent signals and buying-group information.
Salesforce argues consumers' personal AI agents will add more contact center traffic than they remove.
Salesforce says consumers are handing tasks like cancelling subscriptions and booking reservations to personal AI agents.
Many of these tasks can be done through websites, APIs or a business's own agent, but some still require a call.
Personal agents may lack the full customer relationship or hit security checks meant to block bots.
Salesforce argues that because agents never tire of waiting on hold, they will drive more contact center traffic than they offset.