In a recent LinkedIn post, Ashleigh Early shares her experience with the rapid evolution of Artificial Intelligence, highlighting the challenge of keeping pace with new tools and workflows. Early describes a recent conversation that left her feeling significantly behind in her understanding of the AI landscape.
“I took my foot off the AI gas for three months. Client work. Travel. Life. You know the drill. Then I had a call with a friend who’s deep in the weeds… building, automating, orchestrating all the things. And in under an hour, I felt like I’d fallen six months behind.”
This sentiment underscores a growing concern within the business and technology sectors: the sheer speed at which AI capabilities are advancing. Early, who has been actively involved in AI for over a year, including prompt engineering and workflow automation, found this recent interaction to be a stark reminder of the dynamic nature of the field.
The Need for Continuous Learning in AI
Ashleigh Early emphasizes that the rapid development in AI necessitates a proactive approach to learning and adaptation. The pace of innovation means that even those actively engaged in the space can feel overwhelmed.
Rebuilding a Foundational Understanding
Following this wake-up call, Early explains her strategy for re-engaging with the AI world. She is focused on identifying what is currently practical and beneficial.
“So I started rebuilding my baseline. What’s good. What’s real. What’s useful 𝘳𝘪𝘨𝘩𝘵 𝘯𝘰𝘸.”
This approach involves a deliberate effort to filter through the noise and focus on tangible applications and effective tools. Early’s initiative to re-establish her understanding highlights a common challenge for professionals navigating emerging technologies.
Leveraging Curated Resources
To aid in this process, Early points to a specific upcoming event designed to provide a concise overview of AI tools relevant to Go-To-Market (GTM) teams. She expresses enthusiasm for a 30-minute showcase featuring five curated AI tools, emphasizing its efficiency and lack of extraneous information.
“Perfect. BackEngine’s putting it on next week. I’ll be there watching, scribbling & updating my “what’s possible” radar.”
Early frames this event as an ideal opportunity for anyone feeling the pressure to “know more by now.” She is also working behind the scenes with the team at BackEngine, hinting at future insights related to their work.
Community Engagement and Knowledge Sharing
Beyond her personal efforts and attendance at events, Ashleigh Early actively seeks input from her network. She invites her connections to share their own AI-related creations, workflows, or discoveries.
“And if you 𝘩𝘢𝘷𝘦 built something cool — a workflow, a win, a weird AI hack — drop it below. I’m rebuilding my mental map. Help me fill it in!!!”
This call for community contribution reflects Early’s understanding that collective knowledge sharing is crucial in a field that evolves as rapidly as AI. By soliciting these insights, she aims to broaden her perspective and encourage a collaborative approach to mastering the latest AI advancements.
📝 About This Content
This article is based on insights shared by Ashleigh Early on LinkedIn.
📅 Originally posted on November 6, 2025 | View original post on LinkedIn →