Spoiler: If your lead gen still relies on guesswork and long-form Sundays in Notion, you’re playing the game in hard mode. Spoiler: Welcome to the midway point of 2025. Here’s what we’ve learned so far in this year of marketing distruption with tech and AI. Smart marketers aren't “creative geniuses.
They’re systems designers using
AI agents as collaborators. Smart marketers aren't “creative geniuses. They’re systems designers using AI agents as collaborators. AI agents This isn’t a future pitch. It’s a now reality. In this piece, I’ll break down some key points we’ve learned in the marketing trenches. Are you ready to take action? The shift from human-led to AI-assisted marketing stacks
A 3-step real-world framework to implement right now
Toolkits you can plug in to go from chaos to compounding ROI The shift from human-led to AI-assisted marketing stacks AI-assisted marketing stacks A 3-step real-world framework to implement right now 3-step real-world framework Toolkits you can plug in to go from chaos to compounding ROI The Problem: Marketing Is Too Damn Manual Every marketing task has become a time sink: Cold outreach? 2 hours per 10 contacts.
Landing pages? Multiple drafts + “waiting on design.”
Persona research? Mostly intuition and vibes. Cold outreach? 2 hours per 10 contacts. Landing pages? Multiple drafts + “waiting on design.” Persona research? Mostly intuition and vibes. Good luck scaling that. But here’s what’s wild: most of these can now be automated,
templatized and personalized. But here’s what’s wild: most of these can now be automated, automated, templatized and personalized. templatized and personalized. And without losing quality. Heck, you don’t even have to code. You just need to know what to automate, and what to human. Shift: From Crafting to Orchestrating Let’s be honest — ChatGPT isn't “replacing marketers.”It’s justreplacing lazy a*s marketers who write like 2016 Facebook ads. replacing lazy a*s marketers who write like 2016 Facebook ads Here’s what actually matters now: Orchestration of inputs and tools


Framework thinking


Understanding the compounding nature of good data + good prompts
Because “garbage in, garbage out” holds true even in AI. Orchestration of inputs and tools Orchestration of inputs and tools Framework thinking Framework thinking Understanding the compounding nature of good data + good prompts
Because “garbage in, garbage out” holds true even in AI. Understanding the compounding nature of good data + good prompts Because “garbage in, garbage out” holds true even in AI. The 3-Step AI Marketing Stack (Used by a Real Solo Founder) Let’s look at a playbook from a real founder in B2B coaching who turned a chaotic funnel into a compounding flywheel. playbook It’s like turning spaghetti code into a sleek API stack. Step 1: Insight Mining with GPT + Reddit + Product Reviews Step 1: Insight Mining with GPT + Reddit + Product Reviews Pull raw customer language from niche forums, review sites or your own call transcripts. Prompt Example: “Summarize top frustrations and desires of [persona] based on [X subreddit / Trustpilot / app reviews]. Break into fears, desires, and ‘stuck points.’” “Summarize top frustrations and desires of [persona] based on [X subreddit / Trustpilot / app reviews]. Break into fears, desires, and ‘stuck points.’” Output? Clear value props. Ad copy gold. Output? I wanted to know the frustrations of crypto traders based on the subreddit cryptocurrency. Have a look at the video to see the results from this prompt: https://youtu.be/3Ktx_pBp9_U?embedable=true https://youtu.be/3Ktx_pBp9_U?embedable=true Step 2: Asset Generation with Copy.ai + Notion AI Step 2: Asset Generation with Copy.ai + Notion AI Take insights, feed into AI content tools. Generate: Generate: Landing pages for 3 persona variants
Email drip sequences
LinkedIn carousel posts (seriously — it writes and outlines slides too) Landing pages for 3 persona variants Email drip sequences LinkedIn carousel posts (seriously — it writes and outlines slides too) Each variant gets A/B tested. Each variant gets A/B tested. Human touch comes last, not first. Step 3: Outreach at Scale with Clay + Lavender Step 3: Outreach at Scale with Clay + Lavender Plug in your CRM. Clay enriches contact data (title, city, tech stack). Lavender.ai rewrites your outreach with tone, brevity and personalization. | Working with a new client, we quickly tuned it to outperform their agency. Result: 50%+ open rates, 20%+ reply rates in under 2 hours of setup. Result: Your Stack (mid-2025 Edition) Research: ChatGPT, Poe, Claude, Perplexity
Content: Jasper, Copy.ai, Notion AI
Outreach: Lavender, Instantly, Clay, Apollo
Automation: Zapier + Webhooks + GPT Assistants
Ops/Infra: Airtable, Webflow, Super.so Research: ChatGPT, Poe, Claude, Perplexity Research Content: Jasper, Copy.ai, Notion AI Content Outreach: Lavender, Instantly, Clay, Apollo Outreach Automation: Zapier + Webhooks + GPT Assistants Automation Ops/Infra: Airtable, Webflow, Super.so Ops/Infra Mix. Match. Ship. Bonus Dev Layer: Codex Turns Content into Code into Conversion OpenAI Codex is the quiet powerhouse that turns “AI-generated ideas” into real, executable systems. real, executable systems. I like to think of Codex as the bridge from prompt → code → campaign. bridge from prompt → code → campaign Let’s say you want to: Scrape Hacker News titles
Auto-generate tweet hooks
Send to Buffer or Ghost via API Scrape Hacker News titles Auto-generate tweet hooks Send to Buffer or Ghost via API Here's a simplified Codex-powered script: import requests
import openai

# Get top Hacker News stories
res = requests.get('https://hacker-news.firebaseio.com/v0/topstories.json')
top_ids = res.json()[:5]

# Generate tweet hooks with GPT
for id in top_ids:
    story = requests.get(f'https://hacker-news.firebaseio.com/v0/item/{id}.json').json()
    prompt = f"Write a viral Twitter hook for: {story['title']}"
    response = openai.Completion.create(
        engine="text-davinci-003",
        prompt=prompt,
        max_tokens=50
    )
    print(response.choices[0].text.strip()) import requests
import openai

# Get top Hacker News stories
res = requests.get('https://hacker-news.firebaseio.com/v0/topstories.json')
top_ids = res.json()[:5]

# Generate tweet hooks with GPT
for id in top_ids:
    story = requests.get(f'https://hacker-news.firebaseio.com/v0/item/{id}.json').json()
    prompt = f"Write a viral Twitter hook for: {story['title']}"
    response = openai.Completion.create(
        engine="text-davinci-003",
        prompt=prompt,
        max_tokens=50
    )
    print(response.choices[0].text.strip()) Now imagine that running daily. With Zapier, CRON jobs, or your own AI ops agent. Codex Unlocks “Marketing Engineering” This is the future: Non-devs use ChatGPT and WordHero or Jasper to generate messaging
Devs (or advanced marketers) use Codex to connect APIs, trigger campaigns and personalize flows at scale Non-devs use ChatGPT and WordHero or Jasper to generate messaging Devs (or advanced marketers) use Codex to connect APIs, trigger campaigns and personalize flows at scale No more “waiting on dev.” Codex gives marketers their own deployable backend. Final Warning “If the rate of internal change is slower than external change, the end is near.”– Jack Welch (and probably your ghosted leads) “If the rate of internal change is slower than external change, the end is near.”– Jack Welch (and probably your ghosted leads) Don’t get buried under a stack of Google Docs and "pending review" Trello cards. The future of marketing isn’t genius. It’s systems thinking + AI fluency. systems thinking AI fluency PS: I’m building a live AI marketing agent that could re-engage dead leads, qualify them and turn them into appointments, and turn them into sale. Plus it can audit your CRM to give a projection on potential results. Want access? Hit me up @normbond or drop #LEADGEN in the comments.

The is an opinion piece based on the author’s POV and does not necessarily reflect the views of HackerNoon.

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AI Marketing Tools in 2025: Ship Faster, Convert Better, Sleep More

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