Designing an AI Toolkit – Access to Impact
Designing an AI Toolkit – Access to Impact
May 15, 2026
At Seen Ventures, those questions became more than hallway chatter and we got to tackle it head-on. What follows is the inside story of that build, told through our collaboration with MISSION READY and rising UX talent Callaghan Dsouza.
When I joined Seen Ventures as an intern, I was excited to work on something “cool” with AI curating plugins, writing prompts, and building smarter workflows.
But what started as a simple task list turned into something much deeper.
I wasn’t just organizing tools. I was helping design a new relationship between humans and intelligent systems—one that demanded a complete shift in how I thought about design, intention, and behavior.
The Problem We Noticed
Across UX, BA, and Dev teams, one theme kept surfacing: “I’ve heard of these AI tools… but I’m not sure how they actually fit into my workflow.”
Interns/Students weren’t just confused about which tools to use—they were overwhelmed by:
- How to use them effectively
- When to trust the output
- Why the results often felt inconsistent
So we built something different: The Seen Ventures AI Toolkit.
A system not just a resource to guide AI adoption without the overwhelm.
Here’s what we focused on:
✔️ Prompt libraries with real use cases
✔️ JTBD-aligned flows tailored for Designers, BAs, and Developers
✔️ Role-specific pathways to reduce friction
✔️ A clean, friendly UI to encourage exploration—not confusion
Use Cases by Role:
Designers
Speed up wireframes with Figma AI plugins
Generate UX copy and user personas with ChatGPT
Visualise ideas using image generators
Business Analysts
Summarise interviews with QoQo.ai or Microsoft Copilot
Extract insights from transcripts using ChatGPT or Microsoft Teams
Map workflows in FigJam with AI features
Developers
Leverage Figma Dev Mode with AI-assisted code suggestions
Prototype with curated prompt templates
Bridge handoff gaps between design and dev
Design Trade-offs We Faced
With every decision, we had to ask:
- Do we offer every plugin or just the ones that actually work?
- Do we prioritize automation or creative iteration?
- Do we enforce structure or allow freedom to explore?
In the end, we chose focus over flash—because good design doesn’t offer everything. It offers what’s needed to move forward with confidence.
But Designing With AI Comes With Responsibility
When you give someone an intelligent tool, you're not just solving a task—you’re shaping behaviour.
That meant building ethics into the foundation:
- Transparency – Showing where AI outputs came from
- Critical Thinking – Encouraging iteration, not blind trust
- Human-first Design – Crafting prompts that inspired reflection
- Boundaries – Avoiding features that risked misinformation
Because AI is a co-pilot, not the creator. The responsibility still lies with the human.
What’s Inside the AI Toolkit:
- Curated AI tools by role (Design, Dev, BA)
- Real-world prompts and use cases
- JTBD workflows to reduce guesswork
- Onboarding for beginners with confidence
Why It Works
Because it wasn’t built around AI hype it was built around real user needs.
Using stakeholder interviews and the Jobs to Be Done framework, we mapped friction points across teams and matched them with tools that could truly help.
This is more than a toolkit. It’s a launchpad for productivity.
What I Learned
Designing for AI isn’t about building perfect tools. It’s about building trust, especially in moments when the system says:
"Here’s something new. What do you want to do with it?"
It’s about designing for the unknown, for iteration, and for human connection in an age of intelligence.
I’m grateful for what I’ve learned from this experience and if you're exploring how to bring AI into your workflow without losing clarity, creativity, or control, I’d love to chat.
Let’s keep shaping the future of AI one thoughtful, ethical interface at a time. Next step we can't wait to share the working version of the Seen Ventures AI toolkit with you in our next post.
