Meet Serena. From idea to syllabus in minutes
Serena is a generative AI-powered tool that helps instructional designers, and course creators turn learning needs into structured course blueprints—filling the gap between idea and content creation.
Ciao,
In this edition of Radical Curiosity, I’m sharing the story behind Serena, the AI-powered tool I’ve been building to help instructional designers go from learning needs to structured course blueprints. You’ll learn why I believe there’s an untapped segment in EdTech—and how we’re exploring it, one messy prototype at a time.
You’ll also find a behind-the-scenes look at how I created Serena’s voice and style guide—a practical approach if you’re a non-native English speaker or want your brand to sound more human and less like default ChatGPT.
Plus, my interview with Product Heroes (in Italian 🇮🇹), in which I discuss how AI transforms product management from roadmap planning to repetitive task automation.
Table of Contents
Meet Serena. From idea to syllabus in minutes
Writing with personality: How I created Serena’s Style Guide and Voice
Will AI replace Product Managers? (Interview in Italian)
Meet Serena. From idea to syllabus in minutes
Over the past 15 years, I’ve built my career around creating products and leading product teams. I’ve founded and sold two companies, and I’ve also had my share of failures. Today, I work as a temporary product leader, helping define product strategy, build product organizations, and hire, train, and mentor product managers and UX designers.
I’m radically curious, so I’ve always spent time studying, experimenting, and sharing what I learn. Staying up to date, testing new ideas, and participating in communities of practice isn’t just a habit—it’s essential to how I work.
That’s also why I’ve done a lot of corporate training and spent eight years as an adjunct professor of product management at Roma Tre University. Teaching has always been a passion of mine—it’s fulfilling, inspiring, and deeply impactful.
If you’ve ever designed a course, you know how time-consuming and complex it can be. That’s why, over the last nine months, I’ve been exploring how generative AI could help me create new types of learning experiences. It’s still a research and development project, but I believe strongly in its potential. That’s why I’ve decided to start building it in public.
Building in public is a powerful way to kick off a new project because it creates momentum, attracts early feedback, and builds trust. It turns the product journey into a shared experience, where others can contribute, challenge assumptions, and feel part of something from the very beginning. For me, it’s not just about visibility—it’s about learning faster, staying accountable, and connecting with the people who care most about the problem I’m trying to solve.
An untapped segment in EdTech worth exploring
Education is a vast and complex space. Many tools already help educators and instructional designers craft effective learning experiences. It spans all kinds of learning—formal and informal, for kids and adults, from classrooms to corporate training.
I believe there’s a meaningful gap in the learning ecosystem, one that agentic AI can effectively fill. It’s the space between the moment you realize someone needs to learn something and the moment you start producing training content. It’s the messy, strategic part when you must assess the training need, define the scope, articulate clear learning objectives, and craft a solid syllabus.
Today, this work still depends heavily on collaboration between two key roles: the subject matter expert, who brings the knowledge, and the instructional designer, who knows how to turn that knowledge into a structured, impactful learning experience. It’s a critical phase—where the groundwork shapes everything that follows—but it’s still managed through long meetings, shared documents, and a lot of back-and-forth. There’s very little dedicated tooling built for this stage.
Why? Because most tools are focused on what comes after you've already decided what to teach. You have authoring tools like Articulate, EasyGenerator, or iSpring Suite to build content. You have LMS platforms like Moodle, Docebo, or TalentLMS to distribute and track it.
But there’s a missing layer in the ecosystem—a tool that helps you go from a learning need to a structured course blueprint: a Learning Analysis & Design Platform (LeAD). This isn’t just a new spin on existing software. It’s something fundamentally new, made possible by generative AI. For the first time, AI can assist in the early design stages—supporting gap analysis, drafting learning objectives, and generating a well-structured syllabus. A syllabus that becomes a launchpad for the full learning experience, ready to be refined and built in any authoring tool.
If you look at guides like this one by Devlin Peck, you'll see plenty of tools for prototyping and authoring—but when it comes to the foundational design work, the only resource listed is a book. That gap says a lot.
The Analysis and Design steps in the ADDIE framework have traditionally been handled through emails, spreadsheets, and informal workflows.
It’s still too early to determine whether the Learning Design Platform could become a category of its own. But what’s clear is that major players in adjacent spaces are moving in this direction. Authoring tools like Articulate are adding AI throughout their workflows. Easygenerator has introduced an AI course builder. Even LMS platforms are getting involved—Docebo now includes AI-powered authoring, and TalentLMS claims its AI can “generate cohesive courses, so you don’t have to.”
Everyone seems to recognize the potential of generative AI in the early stages of learning design. But based on my own experiments, most of the current solutions are still far from delivering real value. They often conflate course design with content generation—skipping the hard part: truly understanding the learners, defining meaningful learning goals, and crafting a coherent instructional flow.
Together with a friend, we believed we could do better. So we built an MVP to explore this space and test whether generative AI could help create high-quality course syllabi tailored to specific learner profiles and goals. The results were promising—and that’s how Serena began to take shape.
What instructional designers are saying
Around the same time, I started sharing some early thoughts on Serena with the instructional design community—particularly on Reddit—and had the chance to engage in thoughtful conversations with instructional designers and course developers who were already experimenting with generative AI in their workflows.
There’s clearly some skepticism. And, understandably so. Many fear AI could eventually displace roles like theirs, especially if tools are positioned as "automating" instructional design. But at the same time, others are embracing it—openly and skillfully. They use tools like Gemini, Claude, and ChatGPT to draft learning outcomes, create instructional scripts, generate quizzes, role-play interactions, and even reduce reliance on time-constrained subject matter experts. One user said, “I use Gemini daily in my work now and wouldn’t want to give it up.”
Even more interesting is that these professionals aren’t waiting for a dedicated platform—they’re building prompts, workflows, and little assistants. One designer put it best: “AI won’t replace instructional designers—IDs who know how to use AI will replace those who don’t.”
At the same time, there’s a shared frustration: the analysis and design phases are often rushed or neglected due to time pressure. Content needs to go out fast, and the deeper thinking gets compressed or skipped. Many expressed hope that AI could help here—as long as a human stays in the loop to guide, refine, and contextualize.
And that’s exactly the space I believe Serena belongs in—not to replace the designer but to work alongside them so they can bring more of their skill, judgment, and creativity to a part of the process that has always deserved more time, not less.
The embarrassing prototype
It’s still pretty rough—the UI needs a complete redesign, and we’re the first to admit it’s “embarrassing.” But after countless iterations, it’s finally starting to work the way we intended.
That moment when a user said, “That’s a good syllabus—I could definitely use this as a starting point,” was huge for us. It didn’t come easy. One of the biggest challenges was getting the LLM to generate a complete syllabus without repeating the same concepts over and over. Solving that, after hours of refining prompts and engineering the workflow, felt like a real breakthrough.
Serena is the first tool designed to turn learning needs into course blueprints—before you ever open an authoring tool.
We’re still early, and Serena is far from perfect—but the potential is real. And we’re not building it alone. If you’re an instructional designer, course creator, or educator who’s ever wished for more clarity before creating, more structure before designing—we’d love your input.
Writing with personality: How I created Serena’s Style Guide and Voice
If you’ve ever tried to write content for your brand as a non-native English speaker, you know how challenging it can be. Even with great ideas, tone and clarity can slip. That’s where a well-defined voice becomes more than just branding—it becomes a tool for consistency, confidence, and authenticity.
For Serena, I wanted the writing to feel warm, clear, and quietly confident. Not too corporate, not too casual. The default style of ChatGPT is helpful but can be a bit generic. I wanted to shape a voice that reflected Serena’s values: thoughtful, collaborative, and grounded in real-world learning design.
So, I used the following technique.
Step 1: Analyzing Brand Voices with ChatGPT
I started by analyzing how ChatGPT describes the voice and tone of other brands. The prompt was straightforward:
You are a brand manager analyzing the style and voice of [brand name]. Review content from their website, blog, and marketing materials, then summarize your findings
I repeated this for several brands—Airbnb, Stripe, Notion, Asana, and Headspace—to observe the language ChatGPT uses to describe tone, sentence structure, rhythm, and formality. This gave me a clear sense of how certain traits relate to brand perception.
Then, I began shaping Serena’s style using that same logic.
Step 2: Crafting the Serena Voice Prompt
I wrote a custom prompt that reflects Serena’s tone and voice. It wasn’t a one-shot job. I iterated several times, refining until the content felt just right—something I could imagine Serena “saying.” I used the method I described in this article: The Art of AI Prompting: Refining Instructions for Precision and Control.
Here’s the core of the Serena-style prompt I developed:
You will write content according to this styleguides
Serena – Brand Style & Voice Guide
Brand Essence
Serena is more than just an AI-powered tool—it’s a companion for instructional designers, helping them craft better courses with ease. It embodies expertise, warmth, and collaboration, creating a space where professionals feel empowered and supported.
Brand Personality
Knowledgeable, but not academic – Serena speaks with the confidence of an expert but without jargon or pretentiousness.
Warm and welcoming – The tone is friendly and personal, making users feel part of a close-knit group.
Supportive and encouraging – Instructional designers are not just customers; they are co-creators shaping the future of learning.
Curious and open-minded – Serena embraces new ideas, feedback, and innovation, constantly evolving with its community.
Tone of Voice
Serena’s voice should reflect a blend of expertise and personal storytelling. Given its strong connection to the founders, especially Nicola Mattina, the messaging should feel:
Authentic and personal – Sharing real challenges, lessons learned, and behind-the-scenes moments of building Serena.
Conversational and relatable – Avoiding overly technical or corporate language. Instead, speaking like a mentor or peer in a university lounge.
Community-driven – Encouraging discussions, inviting participation, and making users feel like they belong to something bigger.
Storytelling Approach
Founder-led narrative – Nicola’s journey, insights, and hands-on experience in product design and EdTech will be central.
User-centric stories – Featuring instructional designers’ challenges and successes with Serena.
Behind-the-scenes content – Sharing the ongoing development, challenges, and decisions that shape Serena.
Brand Lexicon
Use language that feels natural, professional, but friendly:
Instead of “AI-driven automation for course creators”, say “Serena helps you design smarter, faster, and with confidence.”
Instead of “users”, say “members” or “our community” to reinforce the sense of belonging.
Instead of “customer support”, say “we’re here to help” or “let’s figure it out together.”
Community-First Mentality
Serena is a place, not just a product. The messaging should make users feel like they are part of an evolving knowledge hub.
Encourage engagement – Ask for feedback, showcase members' work, and create opportunities for discussion.
Recognize contributions – Highlight community insights and ideas that help shape Serena.
Content Style
Newsletter & Blog: Thoughtful, reflective, mixing Nicola’s personal experiences with practical insights.
Social Media: Casual and engaging, using direct questions, behind-the-scenes stories, and community shoutouts.
Product Copy: Clear and concise, but with a reassuring, encouraging tone.
Example Messaging
Warm & Welcoming
“Hey, we’ve been thinking a lot about how AI can actually support instructional designers—not replace them. That’s why we built Serena. Think of it as your brainstorming partner, your course co-creator, your extra set of hands when you need them.”Founder Storytelling
“When we first started building Serena, we kept asking ourselves: what do instructional designers actually need? I’ve spent years working in product design, and I know that the best solutions come from conversations. That’s why we’re building Serena alongside you—our community.”Community-Focused
“Serena isn’t just software. It’s a space where instructional designers share ideas, test new approaches, and shape the future of learning. Join us—we’d love to have you.”
This prompt now lives inside a custom GPT we use as a publishing assistant.
Step 3: Writing with ChatGPT, the Right Way
Every time I write content for Serena, I follow a two-step process:
Use ChatGPT as a co-pilot, not a ghostwriter.
I never start with “Write me a…”. Instead, I explain the context and what I’m trying to achieve. Then, I write the first draft together with ChatGPT, refining as we go. I ask it to critique what we’ve written, challenge the tone, or suggest alternatives. This back-and-forth is where the real value lies.Polish with the custom GPT style guide.
Once I’m happy with the draft, I pass it through our custom GPT, which includes Serena’s voice and tone. This helps ensure consistency across everything we publish, from blog posts to interface copy.
Why It Matters
This might sound like extra work, but it’s made content creation faster, not slower. The results feel more aligned with Serena’s personality—approachable, insightful, and designed for humans.
If you’re building a product and struggling with writing that feels “too AI” or “too stiff,” give this method a try. A bit of intentionality goes a long way.
I’d love to hear how you approach voice and tone—especially if you’re working with AI tools. Have you crafted your style guide? Are you using a similar process or experimenting with something completely different?
Feel free to share your thoughts or tips—I'm always learning, and your insights could also help shape how Serena grows.
How AI is changing Product Management (in Italian 🇮🇹)
I had the pleasure of chatting with Marco Imperato, founder of Product Heroes, about how generative AI and intelligent agents are transforming the role of product managers.
We talked about roadmaps, discovery, automation, mindset, skills, and why I believe AI isn’t just a tool—it’s a true paradigm shift for those of us working in product. The interview is in Italian, but I’m exploring ways to dub it in English soon.
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Nicola