- The AI Marketing Advantage
- Posts
- 🎯 The Type of AI Agents That Print Money
🎯 The Type of AI Agents That Print Money
This Startup Nailed The AI Agent Formula
In partnership with
Today, we’re bringing you the latest in AI-powered marketing and business strategies. Here’s what’s inside:
🚨 AI Top Story: Forget general-purpose AI. This startup shows why going niche is where real traction lives.
🎥 AI YouTube Resource Of The Week: How to automate your entire content and SEO strategy using tools like Claude, n8n, and MCP.
💬 Killer Marketing Prompt: Uncover where an AI agent could take real work off your plate, and get the blueprint to build it.
🎯 One Quick AI Hack: A quick, actionable use case to experiment with OpenAI’s new GPT-4.1 model.
🌟 Creator Spotlight: Vaibhav Aggarwal shares a must-save resource for automating your workflows using open-source powerhouse n8n.
The Type of AI Agents That Print Money
This Startup Nailed The AI Agent Formula
There’s no shortage of talk about AI agents right now. Most of it sounds impressiv; AI that can talk, reason, automate. But a lot of it still feels like a work in progress.
What’s working now? Startups that go all-in on one problem and build something useful around it.
The AI startups seeing traction aren’t building general-purpose assistants. They’re picking one industry, learning the ins and outs, and designing agents that actually understand how the work gets done. Instead of trying to be everything to everyone, they’re going deep; and that’s where things start to click.
Take HOAi, for example. They’re building agents to help manage homeowner associations. It’s not a flashy market, but it’s full of the kind of tedious, back-and-forth work that’s tough to scale: tracking requests, coordinating follow-ups, managing approvals, and flagging issues that need human input. That’s where AI, done right, can quietly make a big impact.
HOAi didn’t try to plug AI into existing tools, they built a system from the ground up, designed specifically for agents to take on full workflows. Not just one-off tasks, but end-to-end processes that require context and a bit of decision-making along the way.
And instead of chasing traditional IT budgets, they’re going where the real operational pressure lives: labor. Labor budgets are bigger, less crowded, and tied directly to outcomes. When you can show that an agent reduces the workload or speeds things up, it’s not a hard sell.
That’s one of the big shifts behind these agentic AI businesses: Instead of automating for the sake of efficiency, these systems are built to handle the busywork, keep things moving, and let teams focus on what actually needs their input.
But solving a real problem isn’t always enough. HOAi understood that even the smartest agent needs users to succeed. They prioritised visibility early—making sure the product didn’t just work, but also reached the people who needed it by investing heavily into marketing and sales. In a space this crowded, discovery can be just as important as design.
All of this adds up to a clear takeaway: if you’re thinking about building with agents, or just trying to use them in a smarter way - start small and specific. Don’t aim to replace a whole department. Solve one hard problem really well, in one domain, for people who feel that pain every day. That’s where agentic AI starts to feel more like progress.
🧠 Agentic AI for dummies: 101 on how marketers can leverage on the trend - A straightforward intro to what agentic AI is and how marketers can start using it in real workflows.
🎯 Rethinking Meta Ads AI: Best practices for better results - Tips for getting better results from Meta’s ad tools when automation isn’t delivering.
🏢 Klarna CEO says AI helped company shrink workforce by 40% - Klarna says AI let them cut 40% of staff without slowing down—here’s how they did it.
🎓 Become a certified Generative AI Leader with a first-of-its-kind credential from Google Cloud. - Google Cloud now offers a credential for leaders who want to prove they can lead AI adoption, not just talk about it.
💻 OpenAI Releases GPT-4.1 in ChatGPT for Faster, Improved Coding - OpenAI’s update makes coding faster and more reliable in ChatGPT—especially for dev-heavy workflows.
VAIBHAV AGGARWAL - Master workflow automation with this all-in-one n8n guide—from setup to advanced AI agents.
Not Sure Where to Start with AI Agents? Start Here
Use this advanced prompt to uncover where an AI agent can drive the most impact inside your business, and get a step-by-step, real-world build plan to make it happen.
This prompt is designed for marketers, operators, founders, and builders who want more than vague suggestions. It guides the LLM to analyze your specific workflows, identify high-impact automation opportunities, and give you a detailed, tool-specific breakdown of how to build a working agent using only publicly known use cases and best practices.
You’ll customise it with your business context and tech stack, and in return, get a grounded, actionable roadmap for implementing a real agent that saves time, reduces manual work, or makes smarter decisions inside your team.
Use with ChatGPT-4o for optimal output.
Prompt:
You are an expert in agentic AI, automation architecture, and business workflow design. I want you to help me identify where an AI agent would drive the most value in my business, and then give me a clear, factual, step-by-step breakdown for how to build and deploy that agent using proven practices.
You may only base your recommendations on real-world use cases, examples, and public documentation from trusted sources (e.g., case studies, developer docs, tool documentation, or published builds). Do not make up agent ideas, use cases, or speculative features. If something is not commonly done or documented, say so.
👇 Use this context to tailor your response:
Business Info:
Type of business: [Insert company/industry]
What we do: [Brief description of services/products]
B2B, B2C, or internal team use: [Pick one]
Our Current Workflows:
[List 3–5 workflows or recurring tasks you use, e.g., lead scoring, client onboarding, ticket triage, social posting, CRM updates]
[List tools/platforms involved: e.g., Airtable, Slack, Google Sheets, Notion, Salesforce, Intercom, Zapier, n8n]
Where We’re Feeling Pain:
[Share specific friction points—slow handoffs, too many manual steps, inconsistent follow-up, duplicated tasks]
[Mention any team roles heavily involved in these workflows]
⚙️ Our AI/Automation Stack (if any):
[List any LLMs, AI tools, or automations already in use: ChatGPT, Claude, Zapier, Make, LangChain, n8n, Retool, etc.]
Based on the above, do the following:
1. Identify the Best Workflow for Agentic AI
Choose one workflow from the list that is factually known to be effective when powered by AI agents.
Reference a real-world example, public use case, or well-documented application to justify the choice.
Explain the business value: time saved, better decisions, reduced workload, etc.
2. Describe the Ideal AI Agent Design
Detail the role of the agent: where it starts, what data it uses, how it makes decisions, and where outputs go.
Define the agent’s purpose using real examples (e.g. a support ticket triage agent using OpenAI + Intercom).
Specify whether this should be a chat-based agent, backend worker, automation node, or something else.
Recommend platforms and tools that are commonly used for this use case—no speculation.
3. Give a Factual, Step-by-Step Build Plan
Create a clear plan to build a working v1 of the agent using best practices. Your steps should be:
Ordered and numbered (Step 1, Step 2, etc.)
Based on real features from tools like OpenAI, Zapier, n8n, Make, LangChain, etc.
Supported by examples or documentation links where applicable (optional)
Include:
Setup steps (APIs, triggers, credentials)
Workflow logic and data mapping
How to incorporate reasoning or LLM logic
Testing and error handling
Deployment and monitoring
Tips for optimizing and scaling later
Make this accessible for non-developers who use no-code or low-code tools.
4. Recommend a Follow-Up Roadmap
Suggest one natural extension of this agent (v2 idea)
Note what performance signals to track (e.g. saved time, reduced errors, increased throughput)
Mention any tools or skills the user might want to explore next
Keep your tone clear, concise, and focused on delivering practical, real-world value. No fluff, no filler—just what works, based on what’s been done.The Simple AI Stack Behind Vibe Marketing
This video breaks down how to automate your entire content and SEO strategy using tools like Claude, n8n, and MCP - no coding needed.
Learn how to find high-intent keywords, generate blog posts, social content, and dashboards, and turn it all into a repeatable system you can copy and deploy fast.
Easily Turn Screenshots Into Strategy with GPT-4.1
OpenAI just dropped GPT-4.1, which is now faster, more accurate, and with advanced visual reasoning. That means you can upload charts, dashboards, and screenshots, and get real insight back.
A great way to put this to work is to upload your latest social, ad, or email analytics visuals, then prompt:
Review these performance screenshots. Summarise key trends, identify what’s overperforming or underperforming, and suggest how we should adjust our overall strategy next month—include audience focus, content themes, opportunities to double down on, and any blind spots we might be missing.GPT-4.1 will turn your raw performance data into a clear, strategic game plan—no spreadsheet wrangling required.
Bonus: Ask it to format the output as a Slack update, team summary, or slide deck outline.
How to access:
In any ChatGPT chat (Plus, Pro, or Team), click the dropdown at top labeled GPT-4. You’ll now see both GPT-4.1 and GPT-4.1 mini as options.
Singlehandedly Depleting OpenAI’s processing power 🤩
O
How did we do?How did we do with this issue of the AI Marketing Advantage. |
 | Your AI Sherpa, |
Reply