I’m sure there’s some fancy triangle or quadrant framework out there that lays out the "perfect future-proof AI skill stack". After mucking around with AI for a few years, here's where I'd start if I were just beginning.

I'm pulling together the nuts and bolts of these skills together in a longer, more detailed format, with practical steps. But for now, I wanted to share these thoughts and see what feedback comes of it...

1. AI Fluency

This is the new digital literacy. Everyone throws the term around, but what it really means to me is: “Can you work with AI like it’s a co-worker, not a magic trick?”

Most people think AI Fluency is something to do with Prompt Engineering. This is true to an extent, and it's a component. To me it's more about knowing:

  • what the AI is good at

  • how to steer it properly

  • how to use it across your actual work

  • how to critique and improve what it gives back

It’s less “what’s the best prompt for LinkedIn content” and more “how would I get these AI tools and assistants to research, draft, rewrite, summarise, and package something so I don’t spend 4 hours on it”.

Tools to Build Fluency:

  • ChatGPT (GPT-4o) for general use, comms, research, structure

  • ChatGPT (o3) for problem solving, analysis and reasoning

  • Claude Sonnet 4 for creative writing

  • Claude Opus 4.1 for big document breakdowns (or when you want more nuance)

  • Perplexity for research and source checking

  • NotebookLM is in a league of its own for organising and reasoning over large sets of information

  • Custom GPTs and Claude Projects to save recurring tasks and train them on your tone/process

  • Anthropic’s AI Fluency course is actually solid if you want a framework (Delegation, Description, Discernment, Diligence)

  • Gemini and ChatGPT’s Deep Research agents are, for me, the most underappreciated way to let AI run wild across the internet and dig up everything on a topic

  • Wispr Flow is my pick when I want to use and feel AI in a completely different way. The accuracy is unparalleled

Daily Practice:

  • Improve answers by building on them step by step

  • Ask the AI to respond as a different person or role

  • Try tricky questions to see where it struggles

  • Check answers using another AI or trusted source

  • Start with a broad question, then narrow it down

  • Ask for the same answer in list, table, or paragraph form

  • Take a great answer and figure out what prompt made it

  • Keep a list of prompts and ideas that worked well

This is about building muscle memory. You get fluent by actually using it.

2. AI Automations and Workflows

If AI Fluency is about working faster, automations are about not needing to work at all for certain stuff.

This is where the time compounding starts. You build something once that saves you time every day.

For me, it’s been a combo of:

  • pull files from gmail and store them in google drive automatically

  • generate weekly reports and summaries without manual work

  • rename and format documents the same way every time

  • clean up and organise email newsletters

  • synthesise youtube videos into key points and store them in notes

  • summarise email newsletters into short, actionable takeaways

  • create documents and folders automatically from form submissions

  • sync information between notion, google sheets, and slack

  • save linkedin and online research into a template with pre-filled interview questions

  • push meeting notes from slack into a searchable second brain

  • send reminders or alerts when key files or emails arrive

Tools to use:

  • Relay.app: epic UI, dead simple to use, great for structured workflows

  • n8n: flexible, can do nearly anything, requires 10% level of coding knowledge

  • Claude:

  • Make: solid drag and drop builder, better UX than Zapier

  • Gmail filters, Google Scripts: don’t overlook the basics

Things to Automate First:

  • Folder/file creation

  • Inbox clean-up and tagging

  • Document parsing (e.g. pull text from invoices, contracts)

  • Notifications + reminders

  • Meeting notes → summaries → tasks

You’re focused here on wiring things together rather than being a developer

3. Vibe Coding

Vibe coding = building scrappy, useful tools without waiting for a developer.

The name’s a bit silly, but it fits. It’s coding by feel. You describe what you want, AI gives you a starting point, and you fiddle until it works.

You don't need to know Python. But if you can:

  • explain a problem well

  • follow logic

  • edit what AI gives you then you’re 90% of the way there.

Things I’ve Vibe-Coded (or helped others create):

  • tracking expenses on holiday by auto logging purchases from bank emails into a travel budget sheet

  • building a tool to track investment performance from bank exports

  • making a doc parser that pulls key fields from documents into a table

  • building a persona builder for work projects

  • creating an audio and video file converter for different formats

Stack for Vibe Coding:

  • lovable, bolt: quick way to spin up simple apps without heavy lifting using natural language

  • google’s ai studio builder: easy to prototype ai features and connect them to tools

  • cursor: above my level, but I’ve hacked together an agent or two before throwing in the towel with it

  • kiro: ai-native ide that turns prompts into structured code, specs, and tests so vibe coding ends up clean and production ready. Above my paygrade

  • chatgpt, claude, or chatprd: great for helping with prds, breaking down prompts, and making vibe coding in the above builders more efficient

Vibe coding is about removing blockers for microservices or microsaas. You can build dashboards, calculators, tools, or internal scripts without needing a dev team. And when something breaks, you can read the error message and figure out how to fix it. That’s the real flex.

These Skills Stack Together

These three skills aren’t separate. They compound.

Fluency helps you think. Automation helps you scale. Vibe Coding helps you ship.

The people who build these are the ones who reduce their reliance on everyone else. You don’t have to ask the data team. You don’t need to wait for dev. You don’t need to brute-force through work manually. You can just do the thing.

Why It Matters in NZ

Kiwis are already generalists. Most of us grew up figuring things out ourselves. These tools are more tools for the toolkit, helping keep pace with global tools.

You can solve problems faster. You can ship ideas by yourself. You can run a business, side hustle, or internal ops stack without asking for help.

If you're feeling behind, just start with one:

  • Write a better prompt and improve the output

  • Pick a workflow to automate

  • Use AI to build a scrappy tool

Written by Mike

Passionate about all things AI, emerging tech and start-ups, Mike is the Founder of The AI Corner.

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