The Builder Mindset in the Age of AI
People today view artificial intelligence in very different ways. Some are afraid it will replace their jobs. Others believe AI will soon do everything with a single click. A third group prefers to wait, hoping someone else figures out the right way to use it first.
But there’s another group — the Builders.
Builders understand that work is already changing. Instead of waiting or worrying, they actively design new ways of working with AI. They experiment, learn, and adapt early. These are the people shaping how modern work actually gets done.
Ramp belongs to this group.
From Ideas to Impact: How Builders Think
Rather than chasing perfect tools, Builders focus on building systems that evolve. They don’t expect AI to solve everything instantly. Instead, they treat it as a partner that improves over time.
At Ramp, this mindset led to a structured way of using AI that focuses on three key stages:
- Prompt
- Knowledge
- Workflow
Each stage builds on the previous one and moves teams closer to automation that actually works.
Step 1: Better Prompts Create Better Results
Most people are used to searching the internet with short, unclear phrases. That approach doesn’t work well with AI.
AI performs best when it receives clear goals, context, and constraints.
Ramp encouraged employees to practice writing better prompts by giving them easy access to AI tools. Over time, nearly all employees started using AI regularly—not because they had to, but because it genuinely helped them work faster and smarter.
One technique made a huge difference:
Instead of sending a rough prompt, users first asked the AI to ask them clarifying questions. After answering those questions, they let the AI rewrite the prompt more precisely. This loop dramatically improved output quality and helped employees think more clearly about what they actually needed.
Step 2: Centralizing Knowledge
Another major challenge for teams is scattered information. Important knowledge often lives across Slack messages, documents, dashboards, and internal tools. When AI pulls from disconnected sources, it often gives outdated or incorrect answers.
Ramp solved this by creating a centralized knowledge system. All critical information was stored in one place and connected to their AI tools.
What made this powerful was the feedback loop:
- Employees flag incorrect or missing information.
- AI drafts an updated version.
- A human reviews and approves it.
- The system improves continuously.
Instead of waiting weeks for documentation updates, knowledge stays current in minutes.
Step 3: Building Workflows That Scale
Good prompts and clean data unlock the final stage: automation.
With modern AI tools, teams can now connect multiple systems without heavy engineering work. Information flows in, AI processes it, and results appear exactly where they’re needed.
At Ramp:
- Product updates are automatically summarized and shared.
- Sales teams receive research and email drafts ready to review.
- Teams work in parallel instead of waiting on manual steps.
As a result, Ramp shipped more features in the first half of 2025 than in all of the previous year combined.
The Real Lesson
This isn’t just about tools — it’s about mindset.
Waiting for AI to become “easy” is a mistake. The real advantage comes from learning early, experimenting often, and building systems that grow with you.
The teams who practice now will move faster later.
The tools are already here. The question is simple:
How will you choose to build your future?