Trailhead has been one of the biggest parts of the Salesforce ecosystem for over a decade. For many people, it was their first proper introduction to Salesforce, giving them a free and relatively simple way to learn new skills, earn badges, and get hands-on with the platform.
Trailhead is still widely used today, but there does seem to be a growing question around just how useful it actually is. Some Salesforce professionals argue that it has become bloated and difficult to navigate, while others feel that the content simply doesn’t go deep enough to prepare people for real-world Salesforce work.
So what actually happened to Trailhead, and where does it fit into learning Salesforce in 2026?
Where Have We Got to With Trailhead?
When Trailhead launched back in 2015, it offered something quite distinct at the time. Salesforce professionals could learn about the platform for free, work through modules at their own pace, and earn badges along the way. Features like Trailheads Playgrounds and, later, Superbadges also gave people a way to actually get into Salesforce and try things out for themselves.
And despite some of the criticism it gets today, Trailhead is still very popular. Salesforce says the platform now has more than 11 million learners globally, while our recent Salesforce Architect Survey found that 66.1% of respondents still use Trailhead to upskill. In fact, it was the most popular learning resource among those surveyed, ahead of self-study, release notes, and professional development through work.
So the current issue isn’t around whether people have stopped using Trailhead, but whether the experience is as useful as it once was, especially for someone trying to work out what they need to learn.
This was something Salesforce MVP Daryl Moon highlighted when I spoke to him about this topic. He believes Trailhead still has “massive value” for people with only a few years of experience, particularly when they want to explore features that they don’t get the chance to use in their daily job. It can also be useful for experienced professionals looking to pick up adjacent skills, such as an admin learning more about business analysis development.
But there is now an enormous amount of content to work through compared to previous years. For a complete beginner new to Salesforce, that can make knowing where to start difficult. As Daryl told SF Ben, Trailhead can sometimes feel like a “maze of modules”, where learners may need more guidance to map out a path that actually makes sense for them.
There are also questions around depth – Trailhead is very good at explaining what a Salesforce feature does and giving you an intro to how it works, but that isn’t quite the same as knowing how to implement it in real life.
Daryl used Forecasting as an example of this. Trailhead can teach someone how it works and provide some examples, but it is then much harder for it to teach the nuances, common problems, best practices, and so on.
So, while it is still a useful place to learn Salesforce, completing modules and earning badges is only one part of becoming genuinely good at using the platform.
How Does Trailhead Survive the AI Era?
The other big question for Trailhead is how it fits into an era where AI can explain almost anything on demand. If someone doesn’t understand a Salesforce feature today, they can ask ChatGPT, Claude, or another AI tool to explain it, simplify it, provide an example, and then answer any follow-up questions.
That doesn’t necessarily make Trailhead less useful, but it does change what people need from it. Trailhead still has the advantage of being an official and structured Salesforce learning platform, and more importantly, it gives people somewhere to actually practice what they’re learning rather than just reading an AI-generated answer.
Salesforce is already bringing AI into the Trailhead experience. The Trailhead Learning Agent, for example, is designed to help users find relevant content based on their goals and experience. This could address one of Trailhead’s biggest problems, with AI essentially helping learners navigate the huge amount of content that has built up over the years.
But the biggest potential opportunity is to learn further into hands-on learning. Daryl said Trailhead is best used to learn the basics before taking those skills elsewhere.
After completing modules on Forecasting, for example, he recommends setting up a dev org or sandbox and actually building with it, researching problems in the community, and looking for best practices that aren’t necessarily covered by Trailhead.
One recent Architect Survey points in a similar direction, with 53.2% of respondents saying gaining hands-on experience was an effective way to ensure career progression. AI use is also already almost universal among the architects surveyed, with 96.7% using it either regularly or occasionally.
Trailhead probably doesn’t need to compete with AI as the place where every Salesforce question gets answered. Its value could increasingly be in giving people the foundations and somewhere to practise, before real projects, communities, mentors, and AI help them go deeper.
Final Thoughts
It’s unlikely that Trailhead’s popularity is suddenly going to disappear, but the questions being raised about it are important. Is there enough depth for Salesforce professionals to develop the skills they actually need in the modern ecosystem, or has Trailhead become better suited to filling gaps and teaching the basics?
In an AI-driven Salesforce world, it probably makes sense to view Trailhead as more of a stepping stone. Learn the foundations, explore features you haven’t used before, but then try to get hands-on with real projects and real-world problems as quickly as possible. That experience is difficult for any collection of modules and badges to replicate.
There is still plenty of untapped potential here too. Salesforce could take the Trailhead Learning Agent much further, potentially turning it from an assistant that helps people find content into something closer to an AI mentor that guides people through their Salesforce careers. If AI develops in the way we expect it to, who knows where it could go next.







