Picture a race car flying down a country highway, only to find itself stuck behind a tractor. The car\u2019s engine is spectacular. But it can\u2019t go any faster than the tractor.<\/p>\n\n\n\n
That\u2019s what many companies encounter, often without realizing it, when they build with AI. They drop an agent into one step of a workflow, and everything before and after it still moves at the speed of the organization around it. The agent finishes in seconds. Then the work waits for a review, a handoff, or a change request.<\/p>\n\n\n\n
This is why you hear that 95% of companies aren\u2019t getting value from AI. The value gets trapped at every human-scale step the agent has to wait on.
Think of reasoning across every client health conversation that\u2019s ever happened, searching 27 years of Salesforce data, and getting an answer. That\u2019s work no human can do, but if you make one step agentic, the step after it has to be agentic, too. If it isn\u2019t, you\u2019re stuck at human scale, behind the tractor, and that\u2019s where ROI stalls out. <\/p>\n\n\n\n
The fastest way to become an agentic organization is to create a secure and governed open environment where everyone has the opportunity to build. At Salesforce, 74% of employees have used or interacted with an agentic coding tool like Claude Code or Codex at least once, and usage among nontechnical employees is up to 66%, more than triple the usage in Q1. Most of them can\u2019t write code, but they\u2019re willing to experiment with telling a machine what they need.<\/p>\n\n\n\n
But if the right methodology and infrastructure aren\u2019t in place, everyone building everything everywhere can be an insecure nightmare. An agent without the right guardrails can be wrong (and confidently so), and it will act on that error at machine speed. IT also still needs to own trust, integrity, and compliance. IT still needs to own the systems of record and the data semantics, such as what a customer is or what revenue means. You can expose all of that through APIs and MCPs, because we\u2019re no longer building only for people. We\u2019re principally building for agents<\/a> that people will use outside of IT control\/build\/own.<\/p>\n\n\n\n That\u2019s why we\u2019ve developed something we call Rapid Innovation Squads, or \u201cRIS\u201d for short.<\/p>\n\n\n\n In early 2026, my team and I realized that agentic transformation goes far beyond the tooling. I found myself asking: What if a product person didn\u2019t have to talk to a business person, who then talks to engineers? What if they could all be one small team, building the solution together, with no program and no baked product requirements document? How much faster could humans and agents go together, with the right structure, guardrails, and tools, while keeping things secure? What would it look like to rebuild our teams, processes, and systems for an agentic scale? <\/p>\n\n\n\n The RIS recipe is simple. It starts with an opinionated and empowered business stakeholder, someone who owns a problem and has strong views on how to solve it. Then you bring in agentic builders. That might be one, two, or five people, but the team is as small as possible. You also shrink the problem to its smallest useful form.<\/p>\n\n\n\n The daily rhythm looks like this:<\/p>\n\n\n\n The payoff is speed. Partnering with an opinionated stakeholder gets you decisions about 10 times faster. Pair that with agentic coding tools, and you get outcomes about 30 times faster. Think about speed as a proxy for value delivery if you are doing it right.<\/p>\n\n\n\n At Salesforce, SMB sellers were juggling multiple tools and losing time to context switching. Buying signals \u2014 website visits, usage spikes, renewal windows, and more \u2014 were scattered across systems, and the team wanted a persistent surface, inside Slack, that consolidated all of those signals into a clear daily work list. Instead of handing a 12-month project plan to engineering, however, we took the problem to a three-person RIS squad that worked in a 24-hour loop of plan, build, swarm, review, and ship and delivered the Sales Signals Slack app<\/a> in days. A traditional project plan would have stretched the project across months. The app has already generated 28,000 opportunities.<\/p>\n\n\n\n Other RIS projects follow the same pattern: small teams, short timelines. For example, our solution engineers used to spend two to three hours a week logging their activity, and the process was prone to mistakes. In less than four weeks, a three-person squad (one business leader and two agentic builders) shipped a new Slack Skill that scans an engineer\u2019s calendar, Slack data, and Salesforce systems to essentially pre-fill a timesheet for confirmation and approval by the engineer. The sprint got the tool built 70%\u201380% faster than if they had used a traditional Agile process, adoption is at 80%, and 23,000 weekly activities are now logged automatically. <\/p>\n\n\n\n Our legal department has seen similar success. The teams routed and triaged about 39,000 cases a year, and it used to take about 20 minutes to route each one to the right attorney. Worse, sometimes those routings were duplicative, causing attorneys to waste time working on a case someone else was already addressing. A small squad combined deterministic rules with Agentforce to route cases almost instantly, saving $350,000 a year, a 70x return that paid for itself within a month. The agents also de-duplicate cases in flight, and they remember who has worked on what across the full history to refine which attorney a case goes to. The result is routing that\u2019s almost three times better at picking the right lawyer on the first try.<\/p>\n\n\n\nHow RIS works<\/strong><\/h2>\n\n\n\n
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RIS at Salesforce<\/strong><\/h2>\n\n\n\n