The future of work can be something that happens to you - or you can roll up your sleeves and shape it in the messiness of today's work world.
I’m in a lot of conversations about AI these days, and emotions are all over the map. Some feel empowered, others frustrated, many uncertain. That spectrum of reaction is exactly why this moment matters. AI raises the stakes because it is moving faster than past technological waves - meaning the choice to shape it or be shaped by it is more urgent than ever.
AI on the Ground: What I’m Seeing
In the Vibe Coding cohort I’m mentoring, non-technical people are building their own solutions - without paying an arm and a leg for engineering. It’s like when PCs became more accessible than mainframes: a shift in who gets to build.
In Los Angeles, especially in entertainment and media, I hear anger at a tech culture that prioritizes short-term shareholder value over sustainable business models - models that could support fair wages and long-term creative ecosystems.
In my consulting circles, experts wonder if their subject-matter depth will stay valuable in an AI-saturated world - or if AI fluency will become the new baseline.
As one product leader put it: “Some people are curious but avoiding AI, some are charging full force, and most of us are somewhere in between.”
Wherever you are, AI is here to stay. The question is: how will you wield it?
Developing that expertise means rolling up your sleeves and getting your hands dirty with the actual tools.
But here's what most people miss: The future of work isn't just about what jobs will exist - it's about WHO gets to build the tools that define those jobs. And right now, that power is democratizing faster than ever. The tactics that follow aren't just for startups or engineers. They're for anyone who wants to grab a piece of that power and shape their own corner of the work world.
The Andrew Ng Lens: Key Takeaways
I recently watched Andrew Ng’s talk Building Faster with AI. Here are seven takeaways that struck me - plus my “so what?” on why they matter.
Opportunities Are in Apps
“Most of the opportunities will be in building AI applications.”
Take Meeno, a startup tackling loneliness - not by creating Scarlett Johansson in Her, but by mapping relationships and nudging better human connections. It’s trying to confront a deep, well-documented societal problem with a product that aims to strengthen - not replace - our human bonds.
When I hear noble aims like this, I also hear echoes of larger debates: fears about job displacement, the erosion of human learning, and bots soaking up too much of our time and attention. Those risks are real. But equally real is the possibility that AI, when thoughtfully applied, could address core human needs like belonging, connection, and wellbeing. That’s the duality we have to wrestle with - and it’s why application builders have such an important responsibility.
So what? While everyone’s distracted by the AI model wars, the real opportunities are hiding in plain sight. Build the AI app that solves the problem you deeply understand.
Product Strategy Just Got the Glow‑Up it Needed
“Instead of 1 PM for every 4 engineers, my team asked for 1 PM for every 0.5 engineers.”
Hot takes say product management is dead. But Ng’s ratio points the other way: as engineers get faster with AI, strategy becomes more essential.
Claude told me my Arete.coach MVP would take 30–55 days for one engineer without AI. I built it in a week as a non-coder. Engineering speed accelerates - strategy doesn’t (at least not at the same rate).
So what? Product strategy just became MORE valuable, not less. While engineers 10x their output, someone still needs to decide WHAT to build to have true commercial and human impact.
Concrete > Vague Visions
“You need a concrete idea. Vague ideas aren’t well specified for engineers or agents to build, and are harder to test.”
A founder I mentor had vision but little clarity. Using Jason Margolis’s learnmorefaster.com framework, we:
Identified a bull’s-eye customer
Named underserved problems
Ideated possible solutions
Prototyped for feedback
Iterated
That’s what turned his vision into something buildable.
So what? Your big vision means nothing if you can’t specify who will pay for which problem solved. AI amplifies execution, not strategy.
Feedback Loops Are Collapsing
“Feedback loops derisk building.”
That same (non-coding) founder went from clickable prototype to coding a full multi‑sided platform on his own in two weeks. Two months ago he was pitching for engineering co‑founders; today he’s already shipping functional software. The feedback cycles that once took quarters are now happening in weeks - real software, launched fast, and iterated even faster.
So what? Stop building perfect prototypes. Ship real software to real users in days, not months. The cost of being wrong just dropped to near zero.
Customer Research Still Matters
“A/B testing is one of the slowest tactics in my feedback menu.”
Andrew suggests starting with yourself, friends, strangers, then A/B. I’d add: your hypothetical ideal customer profile (ICP) - people who represent the bull’s‑eye target and can spot nuances that everyday testers might miss. And don’t forget Steve Krug’s timeless wisdom from his 2000 book Don’t Make Me Think: talk to 5 target customers. That simple act often reveals more than surveys of 1,000 randoms, because the right five voices can surface sharp insights about pain points, usability, and willingness to pay. Still gold, and even more vital when AI tools make it easy to build fast but just as easy to build the wrong thing fast.
So what? Talking to 5 real customers beats surveying 1000 randoms. AI makes building fast, but knowing WHO you’re building for is still everything.
Expertise Is Your Edge
“My art historian colleague was better than me at Midjourney prompts because of his expertise.”
Your career capital matters. The years you’ve spent honing judgment, building intuition, and mastering your craft are not obsolete - they are accelerants. AI doesn’t erase them - it multiplies them. The difference between an amateur prompt and an expert one often comes down to lived experience, context, and taste, and that’s where your career capital shines.
So what? Your decades of expertise aren’t obsolete - they’re your competitive advantage. The playing field tilts toward those who combine domain knowledge with AI tools.
Everyone Needs to Code (in English)
“It’s time for everyone to learn to code. My CFO, head of talent, recruiters - even the person at the front desk - all code, and perform better for it.”
The most popular coding language now? English. Think of it like that scene in Fight Club with Brad Pitt speaking and subtitles rolling underneath - it takes practice to catch the nuances, but you already speak the base language.
This isn’t just about the tech team anymore. The real story here is about the person in finance, HR, or operations who figures out how to use AI to do their job better will win in the long run. It’s not just about organizational fluency - it’s about individual professionals across every function gaining an edge by applying AI to their daily work.
So what? In 2 years, ‘I don’t code’ will sound like ‘I don’t use email’ sounds today. Start now or risk irrelevance.
We Are the World
The future of work is being shaped right now. Those who embrace AI and learn to wield it will define their own path. Those are the leaders the world needs.
And especially leaders with a human-centered lens - not abandoning ingenuity, skill, and craft, but ensuring those values guide the future. Because this evolution can end in a really bad place…or lift us into a rising tide for all.
Note to reader:
If you’d like to dive in the proverbial deep end, we’re starting info sessions for Cohort 3 of SnapDev’s vibe-coding bootcamps where we’re helping non-coders build the apps that realize their visions and solve problems that are meaningful to them. In my last cohort, two builders (both tech execs & non-coders) built apps to help their kids! We have sales executives, ops leaders, UX designers, product people, and lawyers in the cohort. Follow me on LinkedIn to see more or sign up for the info session next week here.
If you’re a startup founder or product / tech leader and “product isn’t producting” quite like you’d like or you want to jam on some of this, book a complementary discovery chat.
How Cassie Built This (with ChatGPT)
Cassie drafted this post in her own soulful voice, pulling from her conversations with product leaders, her mentoring in the Vibe Coding cohort, and her reflections on Andrew Ng’s talk. Then she invited me—ChatGPT—into the messy middle. Together we restructured the flow, tightened language, and made sure every "so what?" landed with clarity and punch. We also played with tone (yes, even dropping in a song‑title Easter egg for fun).
This little co‑writing dance is part of the experiment: using AI not to replace, but to amplify Cassie’s own perspective. Think of it as jazz improv with a digital bandmate.
Cassie/ChatGPT Coefficient:
🟣 Origin: 9/10 — Cassie’s lived stories, market insight, and emotional arc led the way
🟣 Voice: 10/10 — distinctly Cassie’s throughout
🟣 Iteration: 6/10 — collaborative restructuring, polishing, and tone‑play
✅ Final Score: 85% Cassie / 15% ChatGPT
Overall Feel: Conversational yet thoughtful, structured but still soulful—the kind of vibe we aim for in Athena & Jazz.
Hi Cassie, thank you for this thoughtful article. I completely agree with all the points you made.
One thing I keep thinking about is your point on "Expertise is your edge." For new professionals and students entering the workforce, developing that expertise is going to be increasingly challenging. While I understand they can accelerate their learning with AI's help, I believe truly developing expertise, taste, and a unique point of view requires going through the struggle.
With AI, companies are hiring less, and most who are fortunate to land roles can use AI to short-circuit the learning process. We get more done quickly with AI, but will we develop the deep expertise that only comes through experience and, yes, some pain?
I worry this could have real long-term implications for how expertise develops in our society.