A public operating system for how I work — Metrics, Analysis, Action. How I use AI, how to work with me, and how you can write your own portable context so you can move conversations across Claude, ChatGPT, Gemini, and any agent.

AI won’t replace my job. It just made me untouchable.

What it’s actually done is automate reporting, creative strategy analysis, and data synthesis, putting more signal at my fingertips than ever before. For someone wired like me, that’s pure dopamine.

Moving faster. Making bigger calls with more confidence. Helping the brands I work with take calculated risks without the guesswork. And the ones leaning in? They’re winning.

Here’s what most DTC brands are missing right now:

While everyone scrambles to inflate creative output to keep up with Meta’s Andromeda update, the majority of testing budgets are being burned on concepts with zero data behind them. You’re not just losing money, you’re losing efficiency, and you won’t know it until it’s too late.

The same is true across other major channels. TikTok’s algorithm rewards volume and speed, but without a data-backed creative strategy you’re just feeding the machine and hoping. And organic? AI-generated content has flooded every feed and search result, meaning undifferentiated content is invisible now regardless of how much you post.

AI isn’t about doing more. It’s about thinking deeper.

Automate the work that doesn’t directly drive revenue. Free up your brain for the strategy that does. That’s how you stay relevant, not just in this moment, but in whatever comes next.

I run a small side project and kept noticing that agency owners in my network spent huge chunks of Monday manually pulling GA4 data and writing client reports.

I built a simple automation that does the following every Monday at 8am:

1. Pulls sessions, pageviews, and ad spend from Google Analytics

2. Sends the data to GPT-4o-mini with a prompt that writes a 3-paragraph performance summary

3. Emails the branded report directly to the client automatically

Here’s a real example output it generated this week:

“This week has shown a notable increase in overall website traffic, with sessions reaching 4,820 — up 23% from last week. On the advertising front, spend increased to £340 vs £290 the previous week, with 890 clicks from 45,000 impressions…”

The whole thing runs on n8n and costs about £0.01 per report to generate.

Happy to share more details on how I built it if anyone’s interested. Also turning it into a proper tool, if this is a problem you have, I’d love to hear how you currently handle reporting.

Lot of talk about how founders are trying to use AI. I see 3 buckets:

People who jump on every trend (complex N8N workflows, Claude Code) then move on to the next thing

People who always have Claude and ChatGPT tabs open, constantly copy-pasting to do random tasks

People who want to use AI but aren't sure how, want their teams to use it more but don't know where to start, not sure if they should tell clients they use it

Most fall into bucket 2.

They open ChatGPT, copy-paste their brand voice, paste the email they're replying to, paste the SOP for how they handle this situation, then ask it to help.


Heres what I do:

I stopped treating AI like a tool we go to when we need help and started treating it like a layer that sits on top of our operations.

Everything about our business lives in one place (Notion): strategy, client pipeline, SOPs, roles, meeting notes, marketing campaigns, brand voice, financials, all of it.

If its not in notion it doesnt exist.

All my business context is organized in one system, so AI isn't something I feed information to, it's something that already knows my business.


How it actually works:

1. AI agents that already have context

Built agents inside Notion that handle stuff we used to do manually.

One agent takes sales call transcripts, cross-references our sales process SOP, pulls prospect data, and writes a custom follow-up email in my voice within 10 minutes of the call ending.

Another agent watches our weekly metrics review meeting, extracts every number we mentioned (cost per lead, ad spend, appointments, pipeline value), and automatically updates our dashboard. No spreadsheets, no manual data entry.

These only work because the agents have access to everything: our SOPs, our meeting transcripts, our client data.

If that stuff was scattered across Google Drive and Slack we'd need some complex Zapier workflow that breaks every other week. Don't have the time or patience for that.


2. Infinite context without switching tabs

In Chat/Claude you're constantly reintroducing yourself to the AI. Here's my brand voice again, here's what we do again, here's how we handle this situation again.

Yes there are context windows. And yes, those windows run out.

In our setup I just ask: "Pull our LinkedIn SOP and draft a post about our new offer in my voice."

It references the SOP page, looks at past posts for voice, and drafts it. One query, full context.

Or: "What did we discuss in last week's leadership meeting about Q2 hiring?"

It pulls the answer from meeting notes without me telling it where to look.

I can use any AI model (Claude, GPT, Gemini) all inside the same system without switching tabs, no context window limits, no copying and pasting.


3. The system gets smarter automatically

Every meeting we run gets transcribed and saved: leadership meetings, client calls, team standups.

The more we use the system, the more it learns about us. Six months from now it'll know more about our business than it does today, automatically.

Why am i telling you this?

Because most companies chase the next shiny AI tool thinking that's the answer.

But if your business data is scattered across ten different places, AI will always feel like extra work.

The companies winning with AI aren't using the latest trend, they're the ones who built a foundation first. They organized their business into one system, then layered AI on top.


The hard part:

This requires actually organizing your business first. You can't skip to the AI layer if your operations are chaos.

But once it's built, you stop being the human who explains context to AI fifty times a day and AI becomes something that actually knows how your business works.

I broke down the full setup (how the agents work, how the context system is structured, how it learns over time) in this video if you want to see exactly how it's built.

I run a small B2B agency and was trying to automate most of my work, writing ad copy, creating social content, get insights from performance data faster

so three months ago I decided to test every AI marketing tool that promised to "save time" or "automate" something meaningful

I spent $1,847 and gave each one a real 4-week trial on active campaigns

The pitch is always the same: AI writes your copy, designs your graphics, analyzes your data, generates insights- you just review and publish

that's not how it actually works, and I'm gonna be specific about why most of these tools are time-sinks pretending to be time-savers

Profound ($600/month): I tested it because my CMO saw a demo and it looked incredible. The dashboard is genuinely beautiful. I ran an analysis of our top-performing campaigns and it spit out attribution models that looked scientific. Then I manually checked the numbers and they didn't match our actual conversion data. Spent 8 hours trying to understand their methodology before support went silent when I asked direct questions. Killed after week 2.

Canva Magic Studio ($13/month): This one actually worked, but not how I expected. I thought I'd describe a campaign and it would auto-generate everything. In reallity it's a much better design tool than Canva was before, with some smart templates. But I still had to brief it properly, review every output, and fix copy. Time saved: maybe 20 minutes per week if I'm generous. Still paying for it because the design quality is legit, but it didn't change my life tbh

HubSpot's AI Features (included): The subject line generator works okay for email. The content assistant is surface-level. If you're already paying for HubSpot, sure, click the AI button- but it's not a reason to use HubSpot

Notion AI ($10/month): This one surprised me. I actually use it every day for things that aren't "AI magic." I use it as a CRM, a content calendar, and yeah, sometimes the AI fills in database fields or generates first drafts. Never once saved me hours. But the system itself (Notion, not the AI) reduced context-switching because everything lived in one place

Zapier (free tier): This is the one that actually moved the needle for me. It connected my existing tools so I wasn't manually copying data between systems. One workflow: new lead in my form, auto-filled contact in Notion, auto-triggered email sequence. Setup took 90 minutes and saves maybe 5 hours per month, pretty good!

Ryze AI ($49/month): They promise "AI that watches your ad campaigns and gives advice." What you get: alerts when performance drops, and a chatbot that gives obvious advice. Is your CTR down? "Try improving your ad copy or targeting." Unsubscribed after the trial

AI tools save time at the margins, not the fundamentals

they make a small job slightly faster. They don't eliminate 4 hours of work

the real time-saver was hiring a part-time person to do data entry and basic copywriting ($1,200/month)

that moved the needle way more than all six tools combined. But that's the honest conversation nobody has because there's no commission on recommending hiring someone

Over the past few months I’ve been using AI a lot more in my day-to-day work in performance marketing.

Not for content. Not for gimmicks.

Mostly to improve the quality of my thinking.

I’ll run allocation decisions through it before I move budget.
I’ll pressure-test incentive models.
I’ll use it to sanity-check attribution logic.
Sometimes I’ll rewrite an exec update three different ways until it’s tighter.

The biggest benefit hasn’t been automation. It’s clarity.

It forces sharper framing.
It challenges assumptions.
It makes iteration cheaper.

I’m curious how other growth leaders are using AI in practical ways — especially in paid acquisition or forecasting.

Where for you has it genuinely improved decision-making?

Every founder and marketer needs to set up AI workflows in 2026.

Not optional anymore.

The people who figure this out first are going to have an absurd advantage over everyone else.

I recorded a full walkthrough of the setup I use to run most of my marketing.

Ads, SEO, emails, community, thumbnails, dashboards. I'll show you how all of it works and how you can set it up yourself.

AI automation earns its place in my workflow in areas where human review remains part of the process. Research, drafting, reporting, brainstorming, synthesizing data, and building first versions of things that I evaluate before anything goes live. That's where I get the efficiency gains without gambling on my client's business.

The marketing automation tools that worry me are those marketed specifically on the promise of removing human judgment from the loop.

For many of my clients, my judgment, based on years of experience working in highly sensitive and regulated niches, isn't a bottleneck; it's the service they're expecting.

#marketing #ai #openclaw