AI

I still get excited when I see a boring task and think, “I think I can do something about it, I can build something to automate this.” That is partly the GTM engineering mindset I’ve been in for a while now. And so much of the work is spread across things that do not really belong together. CRM fields, spreadsheets, call notes, dashboards, Slack messages, enrichment tools, random CSV exports, and someone asking for an update five minutes before a meeting. ...

I have spent the last year working around AI security and governance, so I already understood the high level idea behind guardrails. Agents should have boundaries. Tools should have scopes. Read access and write access should mean different things. A system that can touch files, APIs, CRMs, Slack, browsers, or internal docs should probably have a stronger plan than “hope it behaves nicely.” Okay, that last sentence already sounds like I am about to sell you a whitepaper. ...

I have become the annoying person who asks, “Can I run this locally?” This is mainly because after working around AI security and governance for a year, I have started noticing how easily data leaves the systems we understand and enters systems we barely think about. I admit that this is a slightly irritating change in my personality. A year ago, if I found a tool that helped me automate something, summarize something, enrich some data, or speed up a GTM workflow, my first question was usually: does this work? ...

So I was watching a video from this creator I follow and something felt off about it. His lips weren’t syncing right. Not a huge thing, but enough that I noticed. So I went and checked his profile. Turns out he hadn’t actually shown up in any of his own videos for like six or seven months. The whole feed was Heygen. Or something like it, I’m not totally sure which tool. ...

AI Browsers Are Here. But Should You Trust Them? Everyone’s racing to launch their own browser. It’s like last month we had 3 or 4 main browsers in the market and today there are 10,000 and to be honest 9,995 of those are AI browsers. ChatGPT Atlas. Perplexity Comet. Gemini(powered) Chrome almost out I guess. They’re trying to become assistants, agents and interfaces you talk to and not just a browser. ...

Why I’m Picking Up the Math Now I come from product & growth marketing and I’m doing my masters in Data Science and Machine Learning. Most of my work has been about making technical products understandable. Shaping go-to-market plans, writing positioning for AI features, and working across teams to make sure what we build actually makes sense to the people we’re building it for. I’m also on a path to becoming a full-stack machine learning engineer. That means going beyond talking about models. I want to build them. Understand them. Debug them. Know when they’re lying. ...

When Copy‑Paste Stops Working In marketing, we live and die by templates. Landing page templates. Ad copy frameworks. Campaign recipes. Machine learning wouldn’t be that different, right? Just plug in your dataset, borrow someone’s notebook from Kaggle, tweak a few parameters, and be done with it. That’s how a lot of people approach it. And to be fair, it kind of works, until it doesn’t. You get a model that runs, a prediction that looks reasonable, a chart that impresses in a meeting. But under the surface, there’s often a gap. You don’t really know what’s going on. ...

So, the idea for this came from a chat I had with Dhruv, the CEO of Middleware. He pointed out that I should think of myself as a ‘builder-marketer,’ not just a marketer, and that I should build stuff that proves it. I thought about it, and he had a point. A few years later, I would put the same feeling more directly: marketers need enough engineering instinct to build and debug their own workflows. ...