Most of my pre-AI career was in videography, with editing as my strongest creative asset throughout. I successfully negotiated the painful transition from analog to digital video.
As a video editor, I turned raw footage, audio, and graphics into stories. My go-to editing software was Apple Final Cut Pro. I used Sony and Canon cameras, Electrovoice, Sony and Sennheiser mics. I also had a music composition app, a few Adobe graphics tools, did some color correction, and created special effects outside of FCP. I used these tools for hundreds of projects without ever writing a line of code. Truth be told, I didn’t even know there was code. The technology was invisible to me; I focused on the creative outcome.
Software development is undergoing a similar transition, thanks to GenAI. Marketers have already slapped it with the catchy but vague nom de guerre: vibe coding.
Since I lived through that shift long before AI arrived, I recognized that vibe coding brings the same dynamic to software development. You select platforms and tools that will produce your vision from the words you use to describe it.
Need an automated workflow, go to Zapier. Want a pitch deck? Run it through Gamma. I created two basic contact management tools, one in specialty app Lovable and the other with ChatGPT 5. The jury is still out as to which I prefer. (I won’t call either one a CRM. It’s not full-featured but tracks my calls just fine.) There’s no shortage of sources recommending apps. Seek and you shall find. Beware though, some of the recommendations aren’t what they’re cracked up to be, and some have disappeared. AI is still the Wild West.
When Process Becomes Product
AI vendors, and even most developers, talk about architectures, benchmarks, and AGI as if it’s the holy grail. Impressive, yes. But the deeper shift happens when those capabilities land in the hands of non-technical people.
Instead of writing line after line of computer code, you describe what you want, AI builds it, and you refine. The skill moves from syntax to problem framing and iteration.
Generative AI changes the balance of skills inside an organization. People who once needed specialists to execute an idea now deliver high‑quality drafts, prototypes, and analyses themselves.
The apps and services available to non-technical people aren’t as easy as some would have you believe. God knows, there are enough online ads promising an overnight fortune if you use their secret sauce. In reality, unless you know your way around app development, you’ll run into detours, dead ends, and black holes. But like in video editing, the fun comes from finding a direct, elegant, and effective solution.
Real-World Small Business Case Studies
When a business tackles the task effectively, the rewards are measurable and pleasurable. Since I focus on small businesses, success stories in this domain pop up in my feeds. (By the way, I wrote an app to manage my feeds.) Here are three examples. These aren’t Fortune 500 stories; they’re small businesses finding practical wins with AI, which makes them all the more relevant to hands-on operators.
Amarra (Special-Occasion Dresses)
This small New Jersey-based dress distributor used a Large Language Model (LLM) for product descriptions, reducing content creation time by 60%, and deployed an AI-powered inventory system that cut overstock by 40%. AI handles 70% of customer inquiries via chatbots. The team refines content to preserve brand voice and keeps systems in sync through continuous tweaking.
Happy & Glorious (Gift Shop, Canterbury, UK)
With just two part-time employees, this retailer used an LLM to kickstart product descriptions and blog posts. The store owner refines every text to retain her personal voice. AI serves as a "mini‑me" helping overcome writer’s block with high quality—but always under her control.
Creativity (Gift Shop, Norfolk, UK)
Another small retailer piloted AI suggestions embedded in social media platforms for tagging and post ideas. Sales of Jellycats soft toys “went crazy” when using AI-promoted posts. Even so, the owner remains selective about how deeply AI enters her business.
These cases mirror the same dynamic as video editing and vibe coding: non-technical people using powerful tools to speed up creation, always with a human filter in place.
Guardrails That Keep Execs Comfortable
This post is aimed at hands-on types; Sales Directors, Marketing Directors, Product Managers, and Business Unit Leaders, people on the front lines of making businesses hum.
These hands-on people report to CEOs, COOs, CMOs, and other C-suite leaders who are responsible for the overall strategy and fit. Empowerment doesn’t mean abandoning control. Without alignment with governance, brand, and compliance, GenAI introduces risks: rogue messaging, off-brand content, and broken promises.
The winning model accelerates review rather than removes it. AI delivers 80% complete drafts, and human specialists handle the final 20%—the validation, polish, alignment that protects the brand and ensures consistent quality.
Frontline leaders drive the action, but without C-suite buy-in and company-wide coordination, even the best ideas stay on the shelf where they belong.
The Bottom Line
Like the shift from analog to digital video, GenAI doesn’t just speed up production. It changes who can contribute and how fast ideas become reality.
Organizations that pair this accessibility with the right guardrails—preserving brand integrity, ensuring compliance, and delivering on promises—win. The real competitive edge is speed and capability, maintained through alignment with governance, brand, and compliance.
Just as digital editing democratized filmmaking, GenAI democratizes technical capability. The winners will be those who harness that speed with discipline.