My go-to AI prompt
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Just wrapped my National University of Singapore Marketing Strategy class.
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High-Impact AI Prompt Template
(Based on the way I actually worked this week.)
I am a [role] working on [task]. The output is for [audience]. I want to achieve [goal].
Here is the source content:
[Paste notes / screenshot / draft]
Rewrite this with:
• A friendly, concise, practical tone
• Short lines, easy to scan
• No jargon or fluff
• Clear sections and bullets
Do this task:
[Pick one: summarize, rewrite for newsletter, draft outreach, compress, propose ideas, explain simply, etc.]
Constraints:
• Keep it short
• Make it actionable
• Use examples
• Cut anything unnecessary
Then give me 2 variations to choose from.
The key to AI demand gen in 2025
Interview with John Tay, AI Marketing Manager at Riverside
1) When you look at AI adoption in high growth B2B startups & B2C teams, where do you see the biggest workflow gaps today?
Biggest workflow gap right now is the “noise” around AI.
There are just so many tools, tutorials, and “AI workflows” out there that teams often lose track of what they should actually focus on.
I’ve found it helps to anchor everything around one principle, which is to solve bottlenecks directly tied to revenue.
That’s been my north star whenever I build or refine a workflow.
Also a workflow doesn’t always have to be fully automated. Sometimes it’s semi-automated. Just a clear set of SOPs that the team can follow consistently within the LLM itself.
2) Which marketing or sales workflows have delivered the fastest wins from AI at scale?
The fastest wins from AI in marketing come down to three things:
Doing things faster
Doing more things
Doing things that weren’t possible before
Over the past few months, I’ve had the chance to deploy AI across both smaller businesses (mainly B2C) and larger organizations (mainly B2B).
And the way each uses AI is very different, due to the different bottlenecks that they have
For B2C teams, the biggest results came from cross-functional creation work:
Ad creatives (videos, images, copy)
Landing pages (and copy)
Email campaigns
In B2C, creation = revenue. How fast you produce, test, and iterate on creatives directly impacts how fast you grow.
This is because when you look closer at the bottleneck, it almost always sits inside the acquisition engine, specifically, creative generation.
Ad copy → ChatGPT / Claude (context-driven copywriting)
Static images & videos → Veo 3, Higgsfield, Nano Banana, Google AI Studio, FloraFauna.ai
3) For B2B teams, the bottleneck t is different. Usually, it’s demand generation. That’s where AI delivers the fastest leverage:
Automating lead sourcing and enrichment (using n8n, Clay)
Streamlining outreach workflows
Triggering outreach at the right time based on intent
If I could give a summary between B2C and B2B, it would be:
B2C: AI speeds up creation (what drives revenue)
B2B: AI scales demand generation (what fills the funnel)
4) How are you approaching change management so teams adopt AI without feeling overwhelmed or threatened?
I might not have the best approach to AI change management, but when I was doing fractional consulting, I always tried to make it a built-together process with the team.
Here’s how I approach:
I involve them early, map pain points together, and design AI use cases step by step so they feel ownership
The team defines what “better” looks like (e.g. less manual time, faster response, fewer revisions)
I start with short, low-stakes pilots. Usually 1-2 semi-automated workflows with clear success criteria
Co-create workflows together
Translate what works into SOPs. Every successful workflow gets documented into repeatable playbooks so adoption scales with the team taking ownership in the future
Before wrapping up, I also identify 1–2 people who can take ownership and keep improving the workflow after I’m gone.
It’s not a perfect approach, but it’s the one that’s consistently helped teams adopt AI with confidence and ownership.