{"id":95728,"date":"2026-09-24T08:00:00","date_gmt":"2026-09-24T15:00:00","guid":{"rendered":"https:\/\/www.salesforce.com\/?p=95728"},"modified":"2026-09-23T15:05:20","modified_gmt":"2026-09-23T22:05:20","slug":"five-dreamforce-2026-takeaways","status":"publish","type":"post","link":"https:\/\/www.salesforce.com\/news\/stories\/five-dreamforce-2026-takeaways\/","title":{"rendered":"Five Big Ideas Coming Out of Dreamforce 2026"},"content":{"rendered":"\n

In the leadup to Dreamforce 2026, dozens of announcements<\/a> outlined what enterprises look like when software meets AI, but the event itself filled in the picture. Organizations are being transformed. Ways of working within them are transforming just as quickly. To see how headless architecture, Slack Code, purpose-trained models, and more are going to shape the future, read on for the most compelling takeaways from Dreamforce 2026.<\/p>\n\n\n\n

1. Software used to make you come to it. Now it comes to you. <\/strong><\/h2>\n\n\n\n

The way people interact with enterprise applications hasn\u2019t really changed for decades, said Khushwant Singh, SVP of Product Management for Platform, at the AIforce Keynote<\/a>. \u201cYou open an application, you navigate to the right page, you complete the task … and you do that all over again.\u201d<\/p>\n\n\n\n

AI inverts that: Agents don\u2019t need a screen. They need the capabilities beneath the screen \u2014 the APIs, metadata, business semantics, permissions, and governance that Salesforce has spent 27 years building. And now with AIforce, all those capabilities are available to agents through any AI interface \u2014 no need to log into Salesforce at all. \u201cAgents need a different entrance into the enterprise,\u201d Singh said. \u201cThat\u2019s why we opened up Salesforce and all of its trusted capabilities to any AI, any interface, any agent, without requiring a Salesforce UI.\u201d<\/p>\n\n\n\n

\u201cOther software companies, they think their product is the UI,\u201d Patrick Stokes, Salesforce President of Applications and Marketing, said during the Main Keynote<\/a>. \u201cAt Salesforce, our product is the trust that all of you, our customers, put into us to hold your data, to hold your workflows, your business processes, your permissions, your security rules. That is the Salesforce product.\u201d<\/p>\n\n\n\n

Giving agents direct access to the information and metadata inside Salesforce unlocks tremendous value and powerful new ways of working. For one thing, you no longer have to know how to use Salesforce to use Salesforce. Building an app or updating a record used to require specialized training. Now, it\u2019s available to anyone via natural-language prompt, making the power of the platform accessible to a new generation of builders. <\/p>\n\n\n\n

And those builders can now tap into the entire platform, pull out the relevant information and functionality, and create custom interfaces that give them everything they need and nothing they don\u2019t. That\u2019s because AIforce turns all the metadata that admins and developers have encoded inside Salesforce over the last 27 years \u2014\u00a0the definitions of objects, fields, relationships, permissions, and business logic \u2014 into composable elements. So those same underlying capabilities can now be built into dynamic, intelligent, open, and composable AI interfaces without rewriting the core business logic. As Salesforce Chair and CEO Marc Benioff put it in his keynote presentation, \u201cYou\u2019re going to see AI interfaces that are dynamic and intelligent, that are composable and alive. \u2026 The interface itself is alive.\u201d

Read what<\/a> they\u2019re<\/a> saying<\/a>.<\/p>\n\n\n\n

2. Purpose-trained models provide rightsized intelligence for every task.<\/strong><\/h2>\n\n\n\n

You can certainly use a slotted screwdriver to twist in a crosshead screw, but a Phillips performs better because it\u2019s made specifically for the job. That\u2019s the thinking behind Koa, Salesforce\u2019s first purpose-built CRM reasoning model. Through a partnership with NVIDIA, Koa is built on the NVIDIA Nemotron 3 Super architecture, and it\u2019s optimized specifically for enterprise tasks.<\/p>\n\n\n\n

One of the reasons Salesforce partnered with NVIDIA for this project is that Nemotron is pretrained on datasets that have clear provenance \u2014 training data that is open and available for review<\/a>. \u201cIt\u2019s not a dataset that\u2019s been scraped from somewhere,\u201d said Jayesh Govindarajan, EVP of Salesforce AI and Agentforce, at a press Q&A session. \u201cYou could check what data it was pretrained on, which is really important.\u201d Then, Salesforce created synthetic simulation environments for over 14 industry personas across sales, service, marketing, and commerce to simulate real-world user interactions. This leveraged decades of Salesforce\u2019s business context on CRM workflows without using any private customer data \u2014 a level of expertise no general-purpose model can match. <\/p>\n\n\n\n

As Govindarajan and Silvio Savarese, EVP and Chief Scientist of Salesforce AI Research, wrote<\/a>: \u201cWe know what a service escalation looks like from the inside, what qualifying a lead actually involves, what \u2018resolved\u2019 means when a customer is on the other end. That \u2026 is exactly what we could give Koa.\u201d<\/p>\n\n\n\n

In internal pilots<\/a>, Koa proved 14% better than internal benchmarks at retaining context during complex, lengthy, multi-turn conversations. It delivered 15% more relevant answers to end users and was 11% more precise in executing the correct tool calls, meaning autonomous agents make fewer mistakes and resolve tasks faster.<\/p>\n\n\n\n

Read what they\u2019re<\/a> saying<\/a>.<\/p>\n\n\n\n

3. Slack is the front door to the enterprise. <\/strong><\/h2>\n\n\n\n

\u201cThere\u2019s a new work operating system for the AI era, and that is Slack,\u201d said Rob Seaman, EVP and GM of Slack, at the Slack Keynote<\/a>. \u201cIt\u2019s the only place where AI becomes multiplayer.\u201d In Slack, teams can work together with AI in shared channels, where agents can also connect with all the conversational context inside Slack, as well as the data, agents, and workflows inside Salesforce. Without that shared interface, AI stays stuck in \u201csingle player\u201d mode, where one person queries a model in an isolated terminal. The individual learns; the organization doesn\u2019t. Bring agents into Slack instead, and intelligence compounds in the open.

Agents can read across channels and DMs; act on Salesforce data; and even help teams write, review, and ship code together, turning what used to be a single\u2011player sport into a multiplayer one. Decisions become visible, reusable, and improvable by the whole organization. \u201cYour company becomes smarter, and your company moves faster,\u201d Seaman said.  <\/p>\n\n\n\n

This multiplayer dynamic is already reshaping software engineering. With Slack Code, developer teams can collaborate with coding agents directly in shared channels instead of separate environments. Because the work happens in public, nontechnical staff like marketers and product managers can review the builds and guide the project alongside engineers without needing specialized developer tools. As Slack CMO Ryan Gavin explained during the session, \u201cWe are in the age of builders, and we need to turn everyone in our companies into builders.\u201d<\/p>\n\n\n\n

Read what they\u2019re<\/a> saying<\/a>.\u00a0<\/p>\n\n\n\n