Rise of AI Generalists

Traditional, software startups have clear roles: engineers code, designers design, and marketers bring in users. As companies grow, specialization is necessary because handling everything at once becomes overwhelming.

But now, AI tools like Cursor, V0, and ChatGPT are changing the game, allowing a generalist to do all these tasks much faster. (Check out my guide on how to vibe code for practical tips on using these tools effectively.)

Who Are Generalists?

A generalist is someone with foundational knowledge across different areas and the ability to adapt to different situations - my definition of a generalist is the same definition of a generalized specialist because I believe that depth of knowledge is also important to understand the big picture.

I chose to be a generalist because I wanted to be able to do everything and learn everything — I started with web development, explored quantum computing, learned UI/UX, GTM, and eventually moved into product management for early-stage startups. Knowledge maximization is a personal goal of mine.

The key trait of a generalist is a strong bias for action. They figure out ways to get things done, no matter what. Whether it’s building a product or marketing it, they’ll find a hack to make it work.

AI now enables generalists to do more in less time. While this might lead to more solo founders and one-person startups, I believe the real magic happens when two or more tech generalists team up. Their combined versatility allows them to switch roles and responsibilities as needed, creating a highly adaptable and efficient team.

My AI-Powered Coding Experiments

AI has significantly reduced the time needed to build SaaS products. I can now build an MVP in less than a day. The fastest I’ve built one? Around three hours!

Rubie

My cousin sells cakes on WhatsApp and markets through Instagram. I built Rubie to help her take orders easily. It was just a simple Link-in-Bio + WhatsApp message wrapper. Instead of reading documentation, I used ChatGPT and Claude to guide me!

Stack: Flask + Supabase → Later moved to Nuxt + Supabase

Pixi

Pixi was an API product that generated PDFs from website URLs or HTML + CSS files. I built it to try out Golang, and used Nuxt for an API management dashboard.

Stack: Golang/Gin + Nuxt + Supabase

Maki

Since writing Golang was easy, I built another tool—an email validation API—by repurposing the Pixi code. The entire project took just a day to complete.

Stack: Golang/Gin + Nuxt + Supabase

GTMGuy

GTMGuy was a GPT wrapper to automate my product management tasks. It took about a month to launch due to time constraints. It helped product teams write PRDs, conduct SEO audits, and plan A/B tests.

For marketing, I used AI to generate blogs and build internal links, which started bringing in organic users!

Stack: Nuxt + Supabase

Prepal

I played around with Whisper APIs in November and thought—why not build a mock interview tool for PMs and product engineers? Built a SaaS in a day and launched it on Product Hunt two days later!

Stack: Golang/Gin

Angloverse AI

Right after finishing Prepal, I had an idea to pivot the product to an AI-powered IELTS mock test SaaS. I pitched it to my friend, who runs Angloverse, and he loved it. Built the MVP in four hours, and they started using it internally. Now, a friend is working full-time on it!

Stack: Nuxt + JSON DB → Later moved to Supabase

Slate

I write a lot of markdown blogs, so I built a distraction-free, local-first markdown editor for myself in a day. Later turned it into a packaged product and launched it.

Stack: Nuxt + Electron

Pookie AI

Pookie is an AI-powered personal CRM that keeps track of interactions and helps recall them. Built the first version in three hours with Nuxt and SQLite, but ran into issues moving to Postgres. So, in January, I rebuilt it in under an hour using Django.

Stack: Django

8 Products from end of September 2024 to early January 2025

With AI, I built eight products in just three months, and two of them reached 100+ users in two months. Retention is another topic, but the speed of execution is what mattered here.

I don’t actively work on these products anymore, but I’m proud of what I built. Here’s a list of the things are / was live!

Other AI Workflows

Product management stuff

I’ve an internal version of GTMGuy that I use to help me with product management tasks! PRDs, Ideation, Brainstorming, Competitive Analysis, etc.

Startup Research

For KPH, I frequently connect with startup founders and need to conduct thorough research on both the founders and their companies.

To make this easier, I built a tool using Streamlit and Claude that scrapes websites and automatically generates a report.

These resports include the startup’s core business, competitive landscape analysis, and other key insights—especially helpful when preparing for next-day meetings.

Founder Intros

I introduce founders to angels and VCs. I built another app that processes call notes and startup details, then generates a memo for investor introductions.

Content, SEO and Copywriting

I scrape competitor websites, analyze keywords, and use AI to generate blogs addressing content gaps. This approach helped GTMGuy grow organically.

The Future of AI Generalists

AI will enable generalists to move faster from 0 to 1. AI-powered generalist founders will achieve more with fewer resources. Specialists might even hire generalists as “force multipliers.”

We’ll see more product engineers who can code, design, and market, and more PMs who can build MVPs and validate ideas quickly, Growth engineers coding and running experiments!

I’m excited to see how this evolves in the coming years!

Key Takeaways

1. AI is enabling one person to build and launch and grow products faster than ever
2. It is easy to learn and pick up any tech stack provided that you have foundational knowledge
3. Use AI to do the boring stuff, and focus on making the right decisions and executing it
4. Use unconventional hacks with tech and AI to grow your product

Key subjects that I want to learn more about in 2025

1. Micro economics
2. Neuroscience and psychology
3. More about math and physics because everything is an abstraction of math and physics