Email Marketing Specialist | Scaling Businesses One Email At The Time 📈

I don’t like to advertise this fact, but I’d do this job for free.

Starting my career in email marketing seemed like a mismatch at first, given my bachelor's degree in Ecology. But life has a funny way of leading us down unexpected paths, and I quickly realized I had a natural talent for writing copy. This talent then spilled over into strategy and automation, and before I knew it, I was helping brands not just communicate but truly connect with their audiences through email.

One of my key strengths is spotting the untapped potential in both brands and people. I bring those hidden strengths to the forefront, making sure each email resonates with the right audience at the right time.

Maybe it’s time I toot my own horn a bit. As I usually say, "Email marketing works—when done right, that is."

- Generated over $74,000 for a client in the gaming industry, with 75% of revenue coming from automated flows and the rest from targeted campaigns.

- Increased email revenue by 44.68% for a client, with a 159.41% increase in form submissions through a new pop-up strategy and better A/B testing.

- Drove $349,230.52 in revenue for a brand, with 89% of that revenue coming from email automation.

- Helped a fashion brand grow revenue by 34.7%, reaching $375,818 in just nine months. Email open rates hit 58.16%, and click rates improved to 10.65%. SMS campaigns alone generated $211,904 during this period.

- Boosted form submission rates by 216.53% for a client, directly increasing lead generation and revenue.

- Helped a business generate $19,755.90 from a single email campaign, contributing to total revenue of $92,980.85 in just four months.

- Took an e-commerce brand from the ground up, increasing its revenue from $24,847 to $40,131 through engaging email campaigns and improved email strategies.

Enough of the boring numbers for now. Let's close out this "about" section.

When I’m not busy “emailing,” you’ll probably find me experimenting with new recipes in the kitchen or listening to some dope music (or both).

Reach out if you want to talk about email marketing, e-commerce, or pool (the one you play with a cue stick, not the swimming kind).

Stefan Boskovic

Your business is eating up all your time, but you can't just keep hiring people. You're overwhelmed by technology and feel like you're not leveraging it properly. So, you're looking to adopt AI. "How can we leverage this?"That's typically how the conversation starts, but technology itself is not the solution.People imagine developing and running products with half the time they are putting in today. They want to make informed decisions in days, not weeks. They want to run 20+ experiments per month instead of 2 per year. All of that is doable, but it doesn't necessarily require the latest tech or a hard push for AI adoption. In areas where you can use AI and it makes sense to do so, you still have a lot of transformation work to do. Let's talk and I'll show you how you can improve your workflows and processes.---Past customers:McKinsey, Amazon, Google, Facebook, SAP, Maersk, TUI, Standard Bank, DB, Haniel, Haufe, TUI, Mercedes, Volkswagen, Sanofi, Zurich, Deutsche Bank, +30 more. Happy to provide a full list and examples. ----------Customers I helped had the following challenges:☒  Manual production of products &amp; services, with no established systems ☒  Products that don't perform and lack an effective product strategy☒  Inefficient product development and delivery processesHere is how I helped them:☑︎  Build semi-automated systems that create new products and services reliably☑︎  Develop high-performing products with an effective product strategy☑︎  Introduce best practices in product operations

ahmet acar

I built a team of AI agents that documents an entire company without asking a single employee to write anything.

No wiki. No Notion templates. No “please update the process doc” Slack messages that everyone ignores. No SOO gathering dust. 


Here’s the problem with company documentation: it’s always a project. 

Someone gets assigned to write it, they do a half-decent job, and within three months it’s already wrong. The company moved on. The doc didn’t.

So I designed something different. 

A living system. Six AI agents that work together, each with a specific job, running continuously in the background.

The Crawler watches every document, spreadsheet, and shared folder in real time. 

The Mapper connects them by inferring which files are playbooks, which are decision tools, which are artifacts nobody uses anymore.

Then comes The Interviewer, not showing up cold asking “tell me about your workflow.” It arrives already knowing what it doesn’t know. It’s read the spreadsheet. It sees the columns. It asks: “Who acts on the Status column and what triggers a change?” That’s a 30-second answer instead of a 30-minute meeting.

The Reconciler catches contradictions. Person A says approvals go through finance. Person B says they go to the CEO. The policy doc says neither. It flags, clarifies, and produces one canonical version.

The Decay Monitor tracks how fast each piece of knowledge changes. Your mission statement? Check it annually. Your pricing sheet? Watch it weekly. It learns the rhythm of your company and triggers refreshes before things go stale.

The Advisor stays quiet until you ask. Then it draws on the full knowledge graph to answer: “How do we actually handle X?” It also provides confidence scores that distinguish between what’s verified, what’s inferred, and what nobody has confirmed yet.

The result is a second brain for your company. 

New hires onboard against a real-time map. Leaders get clear answers about how things actually work versus how the org chart and SOPs say they should.

Every company has two operating systems: the official one and the real one. This system surfaces both.

I’ve packaged this as a Claude-powered plugin you can deploy inside your own company.

It’s also what I use to build a second brain into my company from day 1. It took 2 months to build and get right. 

If you want the full setup, drop a comment below and connect with me. I’ll send it over.

Agency Advocate. AI Strategy + Architecture + Agents. Fractional CAIO for SMB

No alternative text description for this image

I don't understand why people want to hire me for stuff they can get on youtube for free. Here are a few channels and tutorials on AI in business. Watch & learn.

These are Claude specific:
https://lnkd.in/dcmT25GX
https://lnkd.in/dBvdwevG
https://lnkd.in/dNxUEHPk

and there are tons more. 
Just skip all the courses & trainings. 
Watch youtube. Apply. Watch again.

I have analyzed 500+ Claude skills and built out 35 Claude Skills based on the best practices. In 7 ready to use bundles. Let me know if you're interested:

Ready to just download and install the plugins. Guides for install, customization, support all included. 

Will continuously update these. If you're interested in getting early access to these products, let me know.

I'm using this in my org & also sharing these with customers.

AI-native Agency. AI Strategy + Architecture + Agents. Fractional CAIO / CPO for SMB in Manufacturing, e-commerce, Financial Services

If you’re over 40, you have spent your career with work that computers couldn’t do yet.

That changed. 

But you haven’t changed yet. The org chart, department, and management still operate as if computers are still just a tool. 

The entire machine called company has been a system for organizing people to do work that machines hadn’t yet learned to do.

Management was a workaround. 

You needed managers because you needed people doing tasks had to be orchestrated. 

You needed people because most work couldn’t be done another way.

Last week, I was sitting on my couch working. After dumping my files and context into Claude Cowork with Opus 4.6, I left to do some chores and forgot to turn off the machine. 

When I came back, it had built 30 hours of my work in 1h of compute.

I had tried stuff like this with models in the past and they failed.

But it’s just gotten better. 

Something is happening that isn’t just hype. You can already see it in SaaS but it’s now going into other areas of knowledge work. 

We talk, speculate, and ramble  about all of this here a lot. 

But unless you try to leverage the tech and see what that does, it’s hard to get what’s happening.

AI Strategy, AI Advisory, AI Agents, fractional CAIO for SMB

Run an AI on your desktop to work with the documents, reports, and notes lon your computer. 

You could use Claude Cowork, but this will cause you to spend $200 per month on the subscription. 

This alternative provides the same at 1/10th the cost - or even for free if you invest some time into it. 

The open source model Qwen Code can do the same thing. 

Qwen reads files, acts on them, and produces finished outputs — without you lifting a file. 

Ask it to turn a folder of meeting notes into a proposal, condense a 40-page report into a two-page briefing, or restructure an email thread into an action plan. 

It works with what you already have.

The tool runs from your computer using plain English instructions, so there’s no learning curve beyond describing what you need. 

You do need to understand how markdown files work, how to instruct it and set context, how LLM work in general etc. 

But that’s 8-10h of focused time. Once you have the basics it’ll take you another 40-80h of use to get it done well. 

That’s just a few months of deliberate use vs losing hours each day on menial work. 

Qwen is free for up to 2,000 requests per day — no subscription, no formatting work, no manual assembly.​​​​​​​​​​​​​​​​

A request doesn’t equal tokens. While Claude constantly blocks me from continuing because it runs out of daily tokens, Qwen processes individual requests, never mind the token count.

You don’t want to be a freelancer. But you don’t want to be a hire. There’s a middle ground:

Enter the fractional executive. 

LinkedIn profiles mentioning “fractional” roles went from 2,000 in 2022 to 110,000 in 2024. 

Looking at these profiles in my network, I noticed one thing:

These are people who chose to multiply their impact across companies.

What do you think?

Will we see more people with fractional roles?

My kids are 6 and 8. Their teachers still create lectures and learning assets by hand. Meanwhile, this medical doctor created 450 lectures in 2 weeks.

Of course, AI is only able to repurpose existing patterns and doesn't produce anything truly original as of yet. But even if that is the case in our lifetime...

What will my kids look forward to when their education system forces them to create things that AI tools can create faster and better at scale?

We're not teaching kids calligraphy anymore, or learning through memorization and recitation of ancient texts. 

Though maybe we should, as these train skills we no longer have. Some might argue we don't need these anymore. People are certainly focused more on building out their second brain than their first one.

Then again, schools, vocational programs and even corporate trainings might catch up on this and identify the skills truly useful in the future while teaching people how to approach learning and work in a world where automated systems are possible.

A professional services company asked me to run a few workshops and trainings for them on AI inside their company. I did and received crickets.

Every time I asked a question... I got silence.

There was an obvious disconnect between leadership and the operative teams. This isn't atypical, actually. But it's hard to discover until you actually engage with the company. 

That's why I like to do kickoff workshops and introductory sessions. These tell me more than the various statements about having data, having introduced AI systems, or having scoped out use cases. 

If you ask any department which problems they face, which tasks are manual and repetitive, how they documented their processes and what their metrics and data look like, you should be able to get clear answers.

If that's not the case, that's a red flag. The customer isn't as ready for AI adoption as they think they are, so they need to build some foundations first. Those foundations are NEVER just getting an AI tool. 

They're typically about organizing your files, mapping your business processes, documenting them and setting up your systems so that using AI and automation tools will solve problems, not increase them.

For instance, if you have a CRM with spotty data, gaps in customer records, a bloated database with slow response times, so that it is actually a bottleneck, and then feed 100x of leads into it from one day to the other...

All you do is break the system.

And thats where 90% of companies actually are. They're not ready for what's possible, they try it anyway, the pilots fail or break existing processes. 

The result? 

Everyone is frustrated.

So before you rush to slap AI into your organisation, ask yourself whether you've done the homework to put some foundations in place. If not, do that first.

agency: the ability to act willfully, make choices, and exert power to bring about change. unfortunately, the systems we created increasingly work against that

Viktor Frankl emphasizes the human freedom to choose one's attitude and response to any situation, regardless of external circumstances.

You find this in the stoics and various other philosophies as well.

But agency isn't something you just have.
It is something you have to continuously work on.

Make no mistake - the way current AI systems are created intentionally strips your agency away from you. So you have to consciously work on it.

A future where AI agents and Robots do everything for you is only partially utopian. The other part is where you are no longer able to act willfully.

All AI providers build trainings now. Here are some Claude Courses.

Claude Courses
→ https://lnkd.in/dATha-b9

Claude Skills
→ https://lnkd.in/dSfrH5jP

Claude Agents
→ https://lnkd.in/dzhCk7e7

What other resources are you using? Claude, Gemini, Qwen… post them below.

Agency Advocate. AI Strategy, Advisory, and Agents. Fractional CAIO for SMB

Companies looking to adapt to AI are facing a Legacy Trap.
This hits business owners who became successful over the past 30 years.

It is the moment a successful business owner realizes that the very expertise, systems, and reputation they spent decades building are now the thing most at risk from AI.

I'm not talking about "disruption" btw. 
I don't think that's what's happening right now.

Disruption happens to industries. 
The Legacy Trap happens to people. 

Specifically, to the 52-year-old who owns that midsized logistics company, has a reputation that opens doors, and a son or daughter waiting in the wings. But who is now quietly wondering whether what he's handing over will still be worth anything in seven years.

Imagine spending thirty years mastering calligraphy, building a school, earning a name, and planning to pass the school to your child. 
Then the printer is invented. 
The business still exists. 
The reputation exists. 
Value changed. 

The business still runs:

1) the business owner's competitive advantage is largely tacit. It lives in judgment calls, relationships, and intuition accumulated over decades. 

2) The owner has too much to lose to experiment recklessly, which means they move slower than the market. The trap is that their greatest asset is exactly what AI transfers best to competitors who have none of the history.

3) AI doesn't just automate. It can make tacit expertise legible and replicable at scale by anyone. Sure, there's quality differences but that's initially irrelevant.

That's the reality of second-generation business succession in an AI economy right now. And AI consultancies & agencies are swarming these companies like vultures trying to push them into "AI transformation".

But here's the thing:

Over decades, these business owners built agency over their business.

If they can adapt the nature of their business to AI while retaining agency,
they'll have an advantage over competitors who slap AI on everything.

So here's how to escape the legacy trap:
1) create clarity over your agency
2) document & map out your systems
3) spring cleaning: clean data, simplify systems, remove workarounds
4) modernize and migrate infrastructure
5) upskill your people in tool use (like actually know how to use office)
6) clarify decisions and ownership at team level (nr 1 applied everywhere)
7) done with the above? now you're ready for AI adoption, create a roadmap

Don't let anyone sell you on shoving some AI tool down people's throats until you have done 1 - 7 first.

If you own a business or consult owners, how are you approaching this?

We're entering an attention recession. 
For the past 30 years, attention = digital business. This might be ending now.

Herbert Simon gave it the intellectual foundation in the 1970s, and the tech industry turned it into gospel: human attention is scarce, therefore valuable, therefore worth capturing, optimizing, and trading. Build platforms that maximize time-on-site. Measure success in eyeballs. Monetize the gaze.

Goldhaber in his 1997 Wired article "The Attention Economy," stated that attention will rival (and lead to) material wealth. Today, of course, people like Gary Vaynerchuk are great at beating the attention drum.

But Simon also stated that "a wealth of information creates a poverty of attention." That's where we are now. 

Ironically, this recession was triggered by the "attention is all you need" research paper. It's what created transformer architectures. The foundation of genAI today.

But a theory built on scarcity breaks the moment scarcity disappears.
In this case, by becoming non-existent.

Noone can pay attention anymore.

The attention economy framework never accounted for: "what happens when the cost of producing content collapses to near zero?"

When supply permanently outstrips demand in any market, the price of the commodity deflates. We didn't just oversupply content. We broke the pricing mechanism for attention itself.

That's why all platforms are adjusting their algos now.
And that's why everyone is pushing shortform content. 
More stuff in smaller increments.

In a recession, the rules of value creation invert. 
What worked during the boom actively destroys value during the bust.

In the attention economy, the winning strategy is capture. 
More impressions. More reach. More surface area. Volume = good.

In the attention recession, captured attention = worthless. 
A million views on a platform built for distraction generates no durable value. Engagement without a relationship is useless. There are views, but no trust. 

If captured attention is deflating, the response isn't to capture more of it. 
That's the equivalent of printing money to solve inflation.

The counter-strategy is:
Depth > breadth, trust > traffic, and identity > impression.

The more I work creating AI agents, the faster I run out of tokens. 

The things do actually work (though it takes time to figure it out).

It can create havoc and security problems (you need to be super careful). 

But a lot of knowledge worker tasks can be replaced (surprisingly well).

So, now… tokens. 

What’s the solution here?
Open source models?
Small models?

Intelligent tiering?

Honestly whatever I do, I burn out of them. 

So either the “gurus” spend crazy amounts of money. 

Or they do less than what they promote. 

Or there is some trick I haven’t figured out yet. 

What are the other ai agent experimenters out there saying?

Before you introduce AI systems into your company, do this first:

(If you don’t, you might break your company in the long run)

1) catalogue all internal tools and systems

- have prod/dev/test in place
- document architecture and build
- secure access and data
- check all backups

2) map out internal processes

- use bpmn to visualise 
- capture as is, not ideal
- identify bottlenecks
- identify decisions and approvals 
- identify multiple data entry

3) clean up
- remove redundant infrastructure 
- simplify tooling
- organize storage

In short, so some spring cleaning first. 

If you automate with things held together by duct tape, you’re going to increase the problems.

This is just too funny… and only the tip of the iceberg. 

Don’t run any of this stuff through an LLM expecting results. 

There is no reasoning or intelligence here. You want this stuff to work?

1) data rigour
2) observability
3) continuous validation

Don’t just dump stuff into an “agent” and be surprised when it makes shit up.

Data Director @ Huel | Community Builder @ CRAP Talks | Keeping it Human | Ceteris Paribus

You'll forgive me if I dont believe you, when you say the analytics function will be completely replaced by AI. My post earlier this week about model evaluations doesn't seem so cuckoo now does it! You all laughed when I talked about schema drifts and semantic ambiguity. You're not laughing anymore. 

All jokes aside. AI still needs a human-in-the-loop element to validate it, but more than anything it needs to be built on top of strong data foundations with context. AI-first schemas with clear semantic layers to minimise hallucinations and provide more reliable outputs. As AI adoption scales, data rigour needs to become a top priority. 

I feel bad for these guys. I'm hoping it's a lesson learned situation and nothing more serious. 

(post not written by AI).

If you're on Google Workspace, stick to Gemini and the tools within that ecosystem. It's integrated deeply and there is more you may not know of:

Since these only show up in google labs and in deepmind, most users don't see them and try alternative tools. But that just leads to a fragmented infrastructure.

Stay within the Google ecosystem and try these instead. Some are only available in the US region, but you can get around this with a virtual credit card and a VPN. Not ideal, but cest la vie.

Coding - Project Jules

This is slightly different to claude code because Jules runs continuously in the Google Cloud and keeps learning your codebase, and improving it automatically, eg for bug fixes. 

It introduces changes aside from the main repo, so there's no danger of it screwing up (or deleting) your entire codebase. It's still experimental though.

Agent Use - Mariner

I really hope this is named after the Star Trek character... but I digress.

This is essentially browser use. You can do a workflow like grabbing assets from a site, putting them into a slide, etc and the agent will remember that flow. It can observe what you do, then try to repeat it.

This is different from workflows and automations you build in other tools. Here, you just do the tasks yourself and it learns what it is supposed to do. You can then tweak the agent.

Music - Lyria

This is different from Suno and similar tools because you can actually decompose music and work on different parts of it. like the melody, rhythm, vocals etc. 

Don't use the chat interface though (go to the labs). The cool thing is that you can also create and change music in realtime with musicFX dj. This is like a mixer with AI built in. (We'll probably see this on device in 1-2 years, so this will be fun!)

There's a bunch more, but in short...

Google built & owns Gemini. So once the AI bubble bursts, I think they'll be the ones left standing in a pretty stable position, continuing their efforts. 

If you're making a midterm bet, this is the ecosystem to go for.

This is why I am looking at Lark, Chinese Open Source Models and Linux. 

You might want to start looking into alternatives too.

Director of Public Affairs Dutch Cloud Community

It's not just the CLOUD Act. 

Microsoft, Amazon Web Services (AWS), Google are giving us reassuring messages about using their services. "The risks aren't all that high", "Donald Trump isn't reading your email", and all of them have created European legal entities that allege to be "sovereign".

But over the years America has given itself a variety of tools that allow the administration to control US companies trading overseas, to seize data or metadata, to influence or stop financial transactions or make it impossible for those companies to serve certain customers, wherever they are located on the planet.

As America gradually moves away from international agreements and indeed from being a law and rules based society we cannot, should not close our eyes for the risks we incur.

Senior Advisor, Stuyvesant High School Alumni Association Lead Creative Producer, Tenney Diamond Productions LLC

TEST FOR YESTERDAY!

This is the one test that I got a 100 on! All 20 out of 20 for me.  All of these were once common things that I employed to communicate, write, learn, pay bills, and for entertainment. I am no longer doing any of these things which were once important parts of my life. 

In a converse manner, the lower the score, the more likely you are to embrace new technologies and the possibilities that it offers. 

What is your score?  

If your score was high, do you miss doing some of the things on the list? 

If you got a very low score and need an explanation of any of these items, please let me know. I would be happy to share happy memories.

The future is owned, decentralised systems from office tools to AI. 

Cloud services in GCC lagging due to attacks? No problem, we’ll just reroute to use compute from Kenya. 

The cloud providers will always put their interests above yours. 

So what’s the solution? 

Chinese companies and open source provide an alternative - you host your own models and own tools. 

That is intentional. It’s part of a global strategy. 

If US providers build for the 12% of the world, the remaining 88% will go to India and China. 

That may not be apparent yet because the rest of the world is also looking at GCP, AWS etc and the top US models. 

But once energy is scarce and the AI and Cloud providers prioritise their main market above the global south?

That’s when people will be pressured into alternatives. 

Qwen, Lark, Alibaba Cloud etc will have their day. Self hosted models and open source tooling will spread. 

I predict this to happen within the next 3-6 months.

turns out, all that agents.md files do is to increase the cost for you. 

might that be why AI companies are advising you to use them, so that they increase your consumption?

in any case, it seems that forcing the LLM to "think harder" isn't helping

full article and research paper here
https://lnkd.in/d7PyBHPq

ps: I'm not forcing you into "link in comments" or comment "paper" type of bs that is common these days. 

so you'll have to save or repost this for others to see.

Open article: New Research Reassesses the Value of AGENTS.md Files for AI Coding by infoq.com

New Research Reassesses the Value of AGENTS.md Files for AI Coding

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Stefan Boskovic

ahmet acar

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The Battle

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ahmet acar

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Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}ahmet acar's LinkedIn Performance

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