Salesforce unveils Headless 360, turning its entire platform into infrastructure for AI agents

Salesforce debuts Headless 360 agentic platform

Here comes 'enterprise vibe coding' as CRM giant aims to open development to anyone on the platform Salesforce has introduced what it calls Headless 360 at its developer event TDX, which starts today in San Francisco, designed to expand the reach of its app-building tools beyond traditional developers. The goal of Headless 360 is that everything on the Salesforce platform is now an API (application programming interface), MCP (model context protocol) server, or CLI (command line interface) command able to be called by coding agents, or by custom agents targeting specific customer requirements. The Salesforce platform includes CRM (customer relationship management), customer service, marketing, and ecommerce. The company also owns the Slack collaboration tool. Historically, the main UI (user interface) for Salesforce has been in the web browser, though it has always supported a comprehensive API. The company now prefers to talk about an "experience layer" where user interaction can be anywhere, including Slack, Teams, voice chat, ChatGPT, or a custom React application. Headless 360 means that agentic AI in any development tool - including Claude Code, Codex, Windsurf, or Visual Studio Code - can build applications that target the Salesforce platform. "The developer, the builder is talking to these tools, the tools are driving the Salesforce UI creation, configuration etc," said said Joe Inzerillo, Salesforce president of enterprise and AI technology. "We're trying to create this ecosystem where in the future most of the code is going to be written by the agents. "We see that internally in the way that we write things, already there are systems where the vast majority of code is written by the agent," he added. Agentforce Code, also known as Agentforce Vibes, is a browser-based IDE based on Visual Studio Code and is now available as part of the free Salesforce Developer Edition as well as paid subscriptions. There are new agentic integrations and it reflects the fact that some users will rely on agents to do the coding for them. Salesforce extensions, the Salesforce CLI, and organization metadata are all pre-configured. The default LLM (large language model) in Agentforce Code is Claude Sonnet 4.5. It has two modes - plan mode and act mode - and comes with a set of pre-defined agent skills for tasks such as creating custom tabs in a UI (user interface) or generating Salesforce flows. Despite the flexibility of Headless 360, Agentforce Vibes defaults to coding with Apex, the Java-like programming language which is customized for Salesforce apps. Salesforce has usage limits for its developer edition, set at 110 requests per month and 1.5 million tokens. These will refresh monthly until May 31, after which there is a final monthly allocation and no further refresh. Salesforce is keen for companies to build custom agents, rather than just using them to build applications. The definition language for this is Agent Script, which, like Apex, is customized for Salesforce. Agent Script will now be open source, Salesforce said at the TDX conference. However, the company also acknowledges that agents are "probabilistic, not deterministic," and that they "reason their way to unexpected outcomes," to quote the press release. Salesforce has a set of tools intended to control unwanted behavior, including a testing center, observability and session tracing, and the ability to define guardrails and explicit business logic for some operations via Agent Script. The company also announced the Slack Agent Kit, a collection of tools designed to bring agents on any platform into Slack with a chat UI. The story behind Headless 360 is that Salesforce has bought into the idea that most future coding will be done by agents rather than humans. The company said this is a response to customer demand. The initiative is also explicitly designed to enable non-programmers to build on the platform. "We want to expand the tent to bring in people that historically have not been part of the Salesforce ecosystem, that now are starting to build capabilities on Salesforce. Headless is a fundamental unlock that allows people to use our systems more effectively," said Madhav Thattai, EVP and GM of Salesforce AI. Most customers only use a small subset of the capabilities of the Salesforce platform, and per-user subscriptions are costly. What about the notion that with AI to assist the coding, companies can replace Salesforce with their own custom solutions built from scratch? "Maybe you could vibe yourself a SaaS application but who's going to maintain it?" said Thattai. "The notion that every company is going to build everything that they need to use themselves seems pretty crazy because it's a huge amount of expense, time, energy, and brain power that companies are focusing on things that aren't their core business." Other factors the company hopes will keep users on Salesforce include the built-in data structures and workflows that have evolved over the years for CRM, marketing, and other Salesforce use cases. Salesforce also argues that the platform's security features and trust boundaries can protect users from some of the risks of custom development, particularly when vibe coding means builders may not fully understand what they are creating. ®

Salesforce Announces Huge AI Initiative and Calls It â€~Headless 360’

A boneless 360 is kind of a high-effort, low-reward skateboarding trickâ€"a variation on an iconic move from 80s skateboarding that doesn’t actually look very cool in modern street skating, even though pulling it off is hard. A “Headless 360†is, perhaps, if your head fell off while doing a boneless 360, which is not inconceivable. It’s also Salesforce’s newly announced initiative to mash agentic AI into every corner of its product. According to VentureBeat, whose reporter Michael Nuñez reported on the announcement of Headless 360 from the TDX developer conference, Salesforce sounds like it’s attempting something one must admit is pretty ambitious: [The announcement of Headless 360] ships more than 100 new tools and skills immediately available to developers. It marks a decisive response to the existential question hanging over enterprise software: In a world where AI agents can reason, plan, and execute, does a company still need a CRM [Customer Relationship Management system] with a graphical interface? Salesforce's answer: No â€" and that's exactly the point. Last year, Salesforce CEO Marc Benioff claimed 30% to 50% of the work within Salesforce was being done by AI, and said, “All of us have to get our head around this idea that AI could do things that before, we were doing, and we can move on to do higher value work.†Judging from the name, it seems they've not only gotten their heads around it; they've twisted them 360 degrees, and they've tragically fallen off. To a large extent, Salesforce is supposed to automate businesses’ relationships with their customersâ€"tracking what they’re doing, and timing and executing follow up interactions. With Headless 360, it sounds like they want users to be able to take their hands off the wheel completelyâ€"sign up for Salesforce, and then, in theory, literally never log in again. Remember, Salesforce was one of the companies whose values dipped amid the SaaSpocalypse scare back in February. They are in a defensive position, making an argument for themselves as something that should continue to exist. Figuring out a way to use present-day AI across your entire flagship product does seem, in the short term, like a pretty high-effort maneuver. Let’s see if it’s also high-reward.

Salesforce launches Headless 360 to turn its entire platform into infrastructure for AI agents

Salesforce on Wednesday unveiled the most ambitious architectural transformation in its 27-year history, introducing "Headless 360" -- a sweeping initiative that exposes every capability in its platform as an API, MCP tool, or CLI command so AI agents can operate the entire system without ever opening a browser. The announcement, made at the company's annual TDX developer conference in San Francisco, ships more than 100 new tools and skills immediately available to developers. It marks a decisive response to the existential question hanging over enterprise software: In a world where AI agents can reason, plan, and execute, does a company still need a CRM with a graphical interface? Salesforce's answer: No -- and that's exactly the point. "We made a decision two and a half years ago: Rebuild Salesforce for agents," the company said in its announcement. "Instead of burying capabilities behind a UI, expose them so the entire platform will be programmable and accessible from anywhere." The timing is anything but coincidental. Salesforce finds itself navigating one of the most turbulent periods in enterprise software history -- a sector-wide sell-off that has pushed the iShares Expanded Tech-Software Sector ETF down roughly 28% from its September peak. The fear driving the decline: that AI, particularly large language models from Anthropic, OpenAI, and others, could render traditional SaaS business models obsolete. Jayesh Govindarjan, EVP of Salesforce and one of the key architects behind the Headless 360 initiative, described the announcement as rooted not in marketing theory but in hard-won lessons from deploying agents with thousands of enterprise customers. "The problem that emerged is the lifecycle of building an agentic system for every one of our customers on any stack, whether it's ours or somebody else's," Govindarjan told VentureBeat in an exclusive interview. "The challenge that they face is very much the software development challenge. How do I build an agent? That's only step one." More than 100 new tools give coding agents full access to the Salesforce platform for the first time Salesforce Headless 360 rests on three pillars that collectively represent the company's attempt to redefine what an enterprise platform looks like in the agentic era. The first pillar -- build any way you want -- delivers more than 60 new MCP (Model Context Protocol) tools and 30-plus preconfigured coding skills that give external coding agents like Claude Code, Cursor, Codex, and Windsurf complete, live access to a customer's entire Salesforce org, including data, workflows, and business logic. Developers no longer need to work inside Salesforce's own IDE. They can direct AI coding agents from any terminal to build, deploy, and manage Salesforce applications. Agentforce Vibes 2.0, the company's own native development environment, now includes what it calls an "open agent harness" supporting both the Anthropic agent SDK and the OpenAI agents SDK. As demonstrated during the keynote, developers can choose between Claude Code and OpenAI agents depending on the task, with the harness dynamically adjusting available capabilities based on the selected agent. The environment also adds multi-model support, including Claude Sonnet and GPT-5, along with full org awareness from the start. A significant technical addition is native React support on the Salesforce platform. During the keynote demo, presenters built a fully functional partner service application using React -- not Salesforce's own Lightning framework -- that connected to org metadata via GraphQL while inheriting all platform security primitives. This opens up dramatically more expressive front-end possibilities for developers who want complete control over the visual layer. The second pillar -- deploy on any surface -- centers on the new Agentforce Experience Layer, which separates what an agent does from how it appears, rendering rich interactive components natively across Slack, mobile apps, Microsoft Teams, ChatGPT, Claude, Gemini, and any client supporting MCP apps. During the keynote, presenters defined an experience once and deployed it across six different surfaces without writing surface-specific code. The philosophical shift is significant: rather than pulling customers into a Salesforce UI, enterprises push branded, interactive agent experiences into whatever workspace their customers already inhabit. The third pillar -- build agents you can trust at scale -- introduces an entirely new suite of lifecycle management tools spanning testing, evaluation, experimentation, observation, and orchestration. Agent Script, the company's new domain-specific language for defining agent behavior deterministically, is now generally available and open-sourced. A new Testing Center surfaces logic gaps and policy violations before deployment. Custom Scoring Evals let enterprises define what "good" looks like for their specific use case. And a new A/B Testing API enables running multiple agent versions against real traffic simultaneously. Why enterprise customers kept breaking their own AI agents -- and how Salesforce redesigned its tooling in response Perhaps the most technically significant -- and candid -- portion of VentureBeat's interview with Govindarjan addressed the fundamental engineering tension at the heart of enterprise AI: agents are probabilistic systems, but enterprises demand deterministic outcomes. Govindarjan explained that early Agentforce customers, after getting agents into production through "sheer hard work," discovered a painful reality. "They were afraid to make changes to these agents, because the whole system was brittle," he said. "You make one change and you don't know whether it's going to work 100% of the time. All the testing you did needs to be redone." This brittleness problem drove the creation of Agent Script, which Govindarjan described as a programming language that "brings together the determinism that's in programming languages with the inherent flexibility in probabilistic systems that LLMs provide." The language functions as a single flat file -- versionable, auditable -- that defines a state machine governing how an agent behaves. Within that machine, enterprises specify which steps must follow explicit business logic and which can reason freely using LLM capabilities. Salesforce open-sourced Agent Script this week, and Govindarjan noted that Claude Code can already generate it natively because of its clean documentation. The approach stands in sharp contrast to the "vibe coding" movement gaining traction elsewhere in the industry. As the Wall Street Journal recently reported, some companies are now attempting to vibe-code entire CRM replacements -- a trend Salesforce's Headless 360 directly addresses by making its own platform the most agent-friendly substrate available. Govindarjan described the tooling as a product of Salesforce's own internal practice. "We needed these tools to make our customers successful. Then our FDEs needed them. We hardened them, and then we gave them to our customers," he told VentureBeat. In other words, Salesforce productized its own pain. Inside the two competing AI agent architectures Salesforce says every enterprise will need Govindarjan drew a revealing distinction between two fundamentally different agentic architectures emerging in the enterprise -- one for customer-facing interactions and one he linked to what he called the "Ralph Wiggum loop." Customer-facing agents -- those deployed to interact with end customers for sales or service -- demand tight deterministic control. "Before customers are willing to put these agents in front of their customers, they want to make sure that it follows a certain paradigm -- a certain brand set of rules," Govindarjan told VentureBeat. Agent Script encodes these as a static graph -- a defined funnel of steps with LLM reasoning embedded within each step. The "Ralph Wiggum loop," by contrast, represents the opposite end of the spectrum: a dynamic graph that unrolls at runtime, where the agent autonomously decides its next step based on what it learned in the previous step, killing dead-end paths and spawning new ones until the task is complete. This architecture, Govindarjan said, manifests primarily in employee-facing scenarios -- developers using coding agents, salespeople running deep research loops, marketers generating campaign materials -- where an expert human reviews the output before it ships. "Ralph Wiggum loops are great for employee-facing because employees are, in essence, experts at something," Govindarjan explained. "Developers are experts at development, salespeople are experts at sales." The critical technical insight: both architectures run on the same underlying platform and the same graph engine. "This is a dynamic graph. This is a static graph," he said. "It's all a graph underneath." That unified runtime -- spanning the spectrum from tightly controlled customer interactions to free-form autonomous loops -- may be Salesforce's most important technical bet, sparing enterprises from maintaining separate platforms for different agent modalities. Salesforce hedges its bets on MCP while opening its ecosystem to every major AI model and tool Salesforce's embrace of openness at TDX was striking. The platform now integrates with OpenAI, Anthropic, Google Gemini, Meta's LLaMA, and Mistral AI models. The open agent harness supports third-party agent SDKs. MCP tools work from any coding environment. And the new AgentExchange marketplace unifies 10,000 Salesforce apps, 2,600-plus Slack apps, and 1,000-plus Agentforce agents, tools, and MCP servers from partners including Google, Docusign, and Notion, backed by a new $50 million AgentExchange Builders Initiative. Yet Govindarjan offered a surprisingly candid assessment of MCP itself -- the protocol Anthropic created that has become a de facto standard for agent-tool communication. "To be very honest, not at all sure" that MCP will remain the standard, he told VentureBeat. "When MCP first came along as a protocol, a lot of us engineers felt that it was a wrapper on top of a really well-written CLI -- which now it is. A lot of people are saying that maybe CLI is just as good, if not better." His approach: pragmatic flexibility. "We're not wedded to one or the other. We just use the best, and often we will offer all three. We offer an API, we offer a CLI, we offer an MCP." This hedging explains the "Headless 360" naming itself -- rather than betting on a single protocol, Salesforce exposes every capability across all three access patterns, insulating itself against protocol shifts. Engine, the B2B travel management company featured prominently in the keynote demos, offered a real-world proof point for the open ecosystem approach. The company built its customer service agent, Ava, in 12 days using Agentforce and now handles 50% of customer cases autonomously. Engine runs five agents across customer-facing and employee-facing functions, with Data 360 at the heart of its infrastructure and Slack as its primary workspace. "CSAT goes up, costs to deliver go down. Customers are happier. We're getting them answers faster. What's the trade off? There's no trade off," an Engine executive said during the keynote. Underpinning all of it is a shift in how Salesforce gets paid. The company is moving from per-seat licensing to consumption-based pricing for Agentforce -- a transition Govindarjan described as "a business model change and innovation for us." It's a tacit acknowledgment that when agents, not humans, are doing the work, charging per user no longer makes sense. Salesforce isn't defending the old model -- it's dismantling it and betting the company on what comes next Govindarjan framed the company's evolution in architectural terms. Salesforce has organized its platform around four layers: a system of context (Data 360), a system of work (Customer 360 apps), a system of agency (Agentforce), and a system of engagement (Slack and other surfaces). Headless 360 opens every layer via programmable endpoints. "What you saw today, what we're doing now, is we're opening up every single layer, right, with MCP tools, so we can go build the agentic experiences that are needed," Govindarjan told VentureBeat. "I think you're seeing a company transforming itself." Whether that transformation succeeds will depend on execution across thousands of customer deployments, the staying power of MCP and related protocols, and the fundamental question of whether incumbent enterprise platforms can move fast enough to remain relevant when AI agents can increasingly build new systems from scratch. The software sector's bear market, the financial pressures bearing down on the entire industry, and the breathtaking pace of LLM improvement all conspire to make this one of the highest-stakes bets in enterprise technology. But there is an irony embedded in Salesforce's predicament that Headless 360 makes explicit. The very AI capabilities that threaten to displace traditional software are the same capabilities that Salesforce now harnesses to rebuild itself. Every coding agent that could theoretically replace a CRM is now, through Headless 360, a coding agent that builds on top of one. The company is not arguing that agents won't change the game. It's arguing that decades of accumulated enterprise data, workflows, trust layers, and institutional logic give it something no coding agent can generate from a blank prompt. As Benioff declared on CNBC's Mad Money in March: "The software industry is still alive, well and growing." Headless 360 is his company's most forceful attempt to prove him right -- by tearing down the walls of the very platform that made Salesforce famous and inviting every agent in the world to walk through the front door. Parker Harris, Salesforce's co-founder, captured the bet most succinctly in a question he posed last month: "Why should you ever log into Salesforce again?" If Headless 360 works as designed, the answer is: You shouldn't have to. And that, Salesforce is wagering, is precisely what will keep you paying for it.

Salesforce TDX 2026 - why Salesforce's Headless 360 announcement at TDX is really about operating model transformation

After sitting through the keynote at Salesforce's developer conference, TDX, in San Francisco I was a little shell-shocked. There were lots of announcements, several detailed demos, and a whole litany of product names and technical features I tried - and failed - to hold in my head. But after some time to reflect I realized that none of it mattered. Because what Salesforce really announced at TDX was not a list of product updates, but just how serious it is about transforming for the agentic era. The backbone of the keynote was ostensibly a new platform called 'Headless 360' - an infrastructure that makes Salesforce's portfolio of data sources, actions, and tools available via APIs, MCP servers, and skills. All without any hint of a user interface. As Joe Inzerillo, President Enterprise & AI Technology, put it: Every one of these [Salesforce] systems is represented in these endpoints. And these endpoints are what you're going to use - or more accurately, agents working on your behalf are going to use. On the surface, that reads as a technical move. A more flexible way to integrate existing functionality into new systems - and agents - so that you can extend and build on the platform. But in my opinion, that's not really the story at all - not by a long way. Instead I view this refactoring as evidence that Salesforce is serious about the shift it is evangelizing towards the agentic enterprise - and that it is basically showing its customers what that shift looks like in very real - and very concrete - terms. Not because it is adding agents, but because it is restructuring itself to be legible to them. And Headless 360 is the mechanism for doing that. Historically, Salesforce functionality has been consumed via applications. Users log in, navigate screens and follow predefined flows. And so it has been forever, pretty much. Even as Apex, AppExchange and Lightning - for example - extended the scope of the platform over time, the center of gravity remained the same. Salesforce was a place where people went to do their work. But headless removes that assumption by exposing the capabilities that sit behind those applications directly - which means data can be retrieved, actions invoked and processes triggered without going through the interface. Flipping it from an integrated work surface to a set of tools through which work can be facilitated. By exposing its capabilities via Headless 360, Salesforce is making them legible to agents, effectively reprogramming its operating model rather than its products. It is making its fundamental capabilities available in ways that don't require a human. It is, bluntly, re-optimizing its platform for agents, not people. Because agents don't need applications and they don't move through screens or follow prescribed flows. They consume context, identify what needs to be done, and then select capabilities as tools to act. Which only works if those capabilities are exposed in a form they can actually use. Seen through that lens, the rest of the keynote becomes easier to interpret. Vibe coding, agent builders, Claude Code integration, testing frameworks, deterministic harnesses and marketplaces are all interesting. But in the grand scheme of things they feel like a side-show - tools to help customers amplify the value of Salesforce's new operating model. Because as I have previously argued, if agents are going to matter, they will not all sit inside the enterprise. They won't stay bounded to a single system, a single organization, or even a single industry. They will roam freely and act on behalf of customers. They will reach into your infrastructure to facilitate partner actions. Effectively they will integrate context across organizational boundaries in pursuit of their owners' intent, rather than being constrained to the rigid workflows of a single enterprise. Inzerillo was also explicit on this point: I think one of the things about agents is they hate boundaries. Agents do not like to stay in the silo. They want to talk to each other. They want to talk to endpoints. What means is that the challenge is no longer just to build agents that can navigate internal systems, but to make those systems accessible to agents that the enterprise does not necessarily control. And Salesforce's move is a concrete example of that idea in practice. Because its platform is - in effect - also its business, changing how that platform is exposed is equivalent to changing how it operates. It is therefore a meaningful step in transforming its core operating model for an agentic era. Headless 360 is, in that sense, Salesforce's version of an operating model transformation - one in which it is refactoring itself so that its capabilities can be discovered and used as part of a broader ecosystem. It is signaling its belief that future upside will come from being an anchor within a wider ecosystem, rather than simply a provider of applications, positioning itself as a central hub through which agent-driven work can be assembled. That has clear strategic logic. Because if the interface layer fragments - as agents take on more of the work of navigating systems - then the value of applications declines, which represents a direct threat to an application-centric company. But it also shifts value toward companies that hold valuable context and action - but only if those capabilities can be accessed in the right form. So Headless 360 looks to me like a fundamental move by Salesforce to make its capabilities legible - and in doing so cement its continued relevance in a world of agentic ecosystems. For its customers, however, the company is also offering a valuable example of what it means to become an agentic enterprise - one which may be uncomfortable once they recognize it. Because today most enterprises are not even thinking of re-configuring themselves in this way. Their capabilities remain embedded in applications, distributed across teams, and often only partially defined. They rely on people to bridge the gaps - to interpret context, navigate systems and connect actions - and in that environment it might be easy to add agents as interface, but it is much harder to make agents part of the underlying infrastructure. Which means the problem - once seen in this context - is less one of data and more one of operating debt. You can shuffle your data around as much as you want, but unless you make real capabilities - ones that make sense to agents - the foundation of your operating model, you will always struggle to adapt. Data quality has to be viewed through that lens, not in the abstract. Which is why the most interesting thing about the first day of TDX for me was not the specific tools that were announced, but the practical demonstration of what Salesforce is doing to itself. A shift which is showing, whether the audience fully recognizes it or not, what operating model transformation looks like during the move to an agentic era. Not a shift toward more automation layered on top of existing systems, but a restructuring of those systems so that their underlying capabilities can be exposed, understood and invoked as part of a wider ecosystem. For other companies, the challenge is to work out what that means in their own context. What are their discrete capabilities? Where do they sit? How are they defined? And how would they need to be exposed for an agent to use them? Because if not all future agents will work for your enterprise, then your enterprise will need to be able to work with agents that are part of something larger than itself. Which means the real heart of the transformation to the agentic enterprise isn't, in fact, building agents.

Salesforce bets on conversation as the new interface for developers - SiliconANGLE

Salesforce bets on conversation as the new interface for developers Salesforce Inc. wants to make conversation the interface for developers, bringing agents to the foreground with a "headless" version of its platform designed to let humans and artificial intelligence build from nearly anywhere. The new capacity, dubbed Headless 360, will usher in a new paradigm for the company. Every capability in Salesforce's platform is accessible via application programming interfaces, Model Context Protocol tools for connecting models to data and tools, or the command line. That means humans and artificial intelligence models alike can build on them and compose apps across platforms with far fewer constraints. According to the company, this opens a whole new horizon. It also means developers can bring their favorite coding agents from any vendor to the party, including Claude Code, Cursor, Codex and Windsurf. AI also opens up the possibility of prompting ideas and generating code from within chat interfaces such as Slack, mobile, ChatGPT, Claude, Gemini, Teams or any client that supports MCP. To support those possibilities, Salesforce introduced a new way to build agents with Agentforce Vibe 2.0, an artificial intelligence builder that brings agent development natively into the Salesforce platform with multimodel support, including Claude Sonnet and GPT-5. It also provides a development partner that understands business logic, not just code. On top of that, developers will gain full control over the user interface, including native React support, a popular open-source JavaScript library designed for building user interfaces. That will allow them to create fully custom experiences from scratch that are fast, interactive and lively. The company said one enterprise customer saw Agentforce adoption jump from 22% to 78% in six weeks. The agent did not change; the experience did. In addition to evolving Vibe, Salesforce is also launching Testing Center, which is designed to reveal logic gaps, policy violations and inconsistent outputs before they reach users. With Custom Scoring Evals, developers can measure how something performed, not simply whether it ran or failed. They can set a series of standards and evaluate how well those standards were met, rather than relying only on pass-fail criteria. After launch, Observability and Session Tracing will make it possible to see not only what happened in production, but why. When an agent drifts off-task, Salesforce said it will help teams get to the root cause in hours rather than weeks. A/B testing is also rolling out, allowing multiple agent versions to run against real traffic at the same time for more data-driven testing and decision-making. In addition to the company's agentic AI announcements, Salesforce also announced a major expansion to Agent Fabric, the company's trusted agent control plane for companies building multivendor agentic networks. Agent Fabric now brings automated discovery, agent authoring and centralized large language model governance for orchestration. That allows handoffs, model selection and decision-making to happen within enterprise boundaries, with cost and risk optimized without sacrificing speed or quality. Salesforce said the new paradigm for controlling multivendor agent workforces often comes down to having a single "lead" agent that orchestrates the broader labor force. In practice, that can mean a central model overseeing handoffs, coordinating smaller models for reliability and speed, managing costs and token limits, and identifying optimized routes.

Salesforce shifts to API-first future with Headless 360

Salesforce unveiled "Headless 360," its most ambitious architectural transformation in 27 years, aiming to make every capability in its platform accessible via APIs, MCP tools, or CLI commands for AI agents. This initiative arrives in response to significant concerns in the enterprise software sector about the potential obsolescence of traditional SaaS models in light of AI advancements. The company introduced over 100 new tools and skills for developers as part of this initiative at its TDX developer conference. Salesforce's decision to overhaul its platform for AI integration began two and a half years ago, emphasizing the need for a system that operates without the constraints of a graphical user interface. Jayesh Govindarjan, EVP of Salesforce, highlighted that the transformation is informed by lessons learned from deploying AI agents with enterprise customers. "We made a decision two and a half years ago: Rebuild Salesforce for agents," Govindarjan said. This reformation seeks to expose Salesforce's full capabilities to make the platform programmable and accessible from any point. Headless 360 consists of three main pillars. The first, "build any way you want," provides over 60 new Model Context Protocol (MCP) tools and more than 30 preconfigured coding skills, granting external coding agents full access to the Salesforce platform's functionalities. Developers can now create applications directly from any terminal without needing Salesforce's IDE. The second pillar, "deploy on any surface," introduces the Agentforce Experience Layer, which enables agents to function across multiple platforms -- including Slack, Microsoft Teams, and ChatGPT -- without specific coding for each surface. Presenters demonstrated deploying an experience across six surfaces without writing dedicated code for each interface. The third pillar, "build agents you can trust at scale," features new lifecycle management tools that include testing, evaluation, and orchestration. A new open-source programming language, Agent Script, is now available, designed to define agent behavior deterministically and enhance system stability. Salesforce is also shifting its pricing model from per-seat licenses to a consumption-based model for Agentforce. This adjustment reflects the company's recognition that as agents perform the bulk of the work, traditional user-based pricing is no longer applicable. Salesforce's open ecosystem strategy supports integration with major AI models from OpenAI, Anthropic, and Google Gemini. The introduction of the AgentExchange marketplace unifies thousands of applications and frameworks underpinned by a $50 million initiative to support builders. The company emphasizes that the AI agents designed to potentially supplant CRMs are now being utilized to enhance its own capabilities. "The software industry is still alive, well and growing," Salesforce co-founder Marc Benioff remarked previously, positioning Headless 360 as a critical effort to assert Salesforce's relevance in a rapidly evolving technological landscape. Parker Harris, Salesforce's co-founder, succinctly questioned, "Why should you ever log into Salesforce again?" indicating that the platform's future may depend on user accessibility without traditional login requirements, fostering a new operational paradigm for enterprise solutions.

Salesforce TDX 2026 - headless thinking for the Agentic Enterprise era as developers face the shift from determinism to probabilism

When Salesforce co-founder Parker Harris asked earlier this month why anyone should ever log into Salesforce again, it was a comment that caught the eye. It was also unlikely to be the end of the story, of course, as attendees at this week's TDX developer conference in San Francisco are about to find out. Meet Headless 360, the follow-through on Harris' tease. This is based on the first premise that for the past quarter of a century, using Salesforce meant working inside Salesforce. But with today's push towards the Holy Grail of the Agentic Enterprise, that's a limiting factor, reckons the firm, going so far as to assert that if a platform requires humans to click through UIs or write code directly to make progress, it is not ready for the Agentic Enterprise. As per the launch blah blah, Salesforce Headless 360 provides: ...the capabilities your agents need most, exposed as an API, MCP tool, or CLI command so humans and agents can build, act, and deliver experiences on any surface. Instead of burying capabilities behind a UI, expose them so the entire platform will be programmable and accessible from anywhere It also brings three new innovations: ● New MCP tools and coding skills that give your coding agent full access to your platform. ● A new experience layer that renders rich, native interactions across every surface, from Slack to Voice to WhatsApp. ● New tools that give you control over how agents behave in production, before launch and after. The life of a developer has come a long way since he learned waterfall development, says Joe Inzerillo, President of Enterprise and AI Technology at Salesforce. That meant big, long planning cycles and detailed specifications before you ever broke ground. It was slow and slow doesn't fit today: Now we've got to the era of agentics, the speed limit is insane. We're now going really fast. What used to be weeks is now in some cases hours. We have digital labor and humans doing things. There's also a big shift going on that will get a lot of air time over the next two days at TDX, that between determinism and probabilism, he argues: Typically the vast majority of developers, the vast majority of trailblazers, were developing deterministic experiences. You can put in some input, you can define how you want that input modulated or enhanced, and it got some output, You could do that every day, and one plus one was always equal to two, no matter what you did, no matter what day you did it on. It was incredibly deterministic. But we start to talk about agents, and agents are not software. Agents are something else. They're also not human. We have to be careful not to completely anthropomorphize them, but what they are is a much more probabilistic, stochastic system that means that you can't necessarily put in the exact same input and get the exact same output every time. That requires different tooling, a different development cycle. It's really important to bear that in mind as we start to think about building deterministic experiences, building probabilistic experiences, and we're going to be using AI and agents to do both of those things. Hence, the Headless 360 platform, he says: This is really leaning into the fact that coding engines have just gotten really, really good. You can sit down and give [one] a detailed list of instructions and have it go to town writing code for you. It used to be that a lot of processes were [restricting] development, or administrative resources. Now the limit is almost your imagination. It's humans and agents working together to build those deterministic systems like we have in the past, and human and agents working together to build other agents, which is another experience in the mix. But it's really important to have the core values and capabilities of Salesforce integrated into all this, he adds: It's not just tools it's actually more of a development environment and a development philosophy that we're also trying to export to our partners and Trailblazers. If we look at the way that you would typically develop code in a deterministic flow, you generally build, you then evaluate, make sure it's good, you deploy it, and then you make sure it's good in production. That's kind of the cycle. There's a bunch of tooling that we have now released that's either in pilot or going GA right now to help support these functions, building with agents, having agents help you build an agentic experience, and not just our agents, but the whole universe of agents. But when you turn your attention towards building a agentic experience, that. set of tools isn't sufficient. You need other tools that are really designed for the development of agentic experiences. He cites experimentation and control-and-orchestrate as two big areas that are new ground to be covered: When you think about probabilistic experiences, it's really hard to know just in the testing phase whether or not this agent is actually getting better or worse when you're making changes. So part of the way that you have to do that is you test your way into it with A/B experimentation. So, here's my agent in production, here's my agent that I made a tweak on, is that agent better or worse? You really need to see that happen in production, with real traffic and real humans that that agent is talking to, to know that it's good. When you're doing the observe cycle, you also have to control and orchestrate the agents. Ultimately, it's not going to be a single agent that's in your organization or serving your enterprise. It's going to be multiple agents. Understanding how those agents interact is a super-important part of the agentic development life cycle. We can't just ship these agents and hope they work together. We have to think about how they're going to talk together. When this agent gets a question that it doesn't know the answer to, how does it talk to another agent? When people are trying to do a job, what agent should they be going to? How do we want to put that front and center in front of folks? He concludes: We need to let people build the way they want to build because everybody's going to have a slightly different set of requirements. Everybody's going to have a slightly different set of working, so we want to put out tools that help, that guide people into a life cycle that we know will be successful. But we also want to inter-operate. Ian Thomas is on the ground at TDX this week and he'll be reporting back on the vibe from the developer community to this shift in messaging from Salesforce. More to come.

Salesforce Bets On AI Agents With 'Headless 360' Debut Amid Software Stocks Sell-Off - Salesforce (NYSE:C

From UI-First CRM To Agent-Driven Infrastructure Headless 360 exposes Salesforce's Customer 360 stack through APIs, MCP tools and CLI commands, enabling AI agents to operate without traditional interfaces. The release includes 60+ MCP tools and 30+ preconfigured coding skills, designed to give agents direct access inside developer environments such as Anthropic's Claude Code and Anysphere's Cursor. A new Agent Fabric layer adds governance and deterministic orchestration across multi-vendor AI deployments. Bulls vs. Bears: AI Catalyst Or SaaS Disruption Risk The rollout comes amid broader skepticism toward software equities as investors reassess whether AI will replace or commoditize traditional SaaS offerings. The debate has intensified as hedge fund managers and analysts warn of margin compression and structural disruption across enterprise software. In contrast, OpenAI COO Brad Lightcap said incumbents like Salesforce retain structural advantages in data, distribution and enterprise integration, supporting a longer-term bull case. OpenAI's Greg Brockman said the world is transitioning to a "compute-powered economy," reinforcing Salesforce's shift toward AI-agent infrastructure built on scalable enterprise compute and workflow automation. Stock Performance Salesforce has a market capitalization of $167.27 billion, with a 52-week high of $296.05 and a 52-week low of $163.52. The large-cap stock is down 28.55% year to date. Price Action: According to Benzinga Pro data, Salesforce closed at $181.22 on Thursday, up 2.04% on the day. Benzinga's Edge Stock Rankings indicates CRM stock has a negative price trend across all time frames. Photo Courtesy: Shutterstock Disclaimer: This content was partially produced with the help of AI tools and was reviewed and published by Benzinga editors. Market News and Data brought to you by Benzinga APIs To add Benzinga News as your preferred source on Google, click here.

Salesforce Introduces Headless 360 to Enable Agent-Driven Operations Without Browser Access

Agentforce Vibes 2.0 brings that same power natively inside Salesforce, adding full org awareness from the start, multi-model support including Claude Sonnet and GPT-5, and an AI development partner that understands your business, not just your code. The DevOps Center MCP brings that same programmatic access into your CI/CD pipeline. Natural Language DevOps means you can describe what you want to deploy and let your agent handle the execution. The build loop that used to require context-switching across four different tools now happens inside one connected experience -- cutting cycle times by as much as 40%. And for developers who want full control over the visual layer, native React support means you can build completely custom interfaces and experiences with all the platform power underneath. Any design language, any interaction model, any brand expression. "As a dev team lead, I've seen firsthand how Agentforce Vibes is supporting our Salesforce development. It's been especially valuable for speeding up day-to-day tasks like metadata updates and quick tweaks, reducing manual work and boosting efficiency. We primarily use it for repetitive, time-consuming work, from config analysis and metadata adjustments to generating boilerplate code, tests, and handling small refactors or pre-deployment checks. Vibes acts as a strong assistant that streamlines our workfiows, and we're excited to see how it evolves and drives even greater impact over time." -- Adones Guerra, Tech Lead, Grupo Globo