The Blog

Four ways to think
about work.

No filler, no recycled listicles. This is where I write down what I've actually learned running budgets, fixing broken pipelines, and sitting in rooms where things needed to get decided — in four formats, depending on how you like to take it in.

01
Read · 3-5 min

Articles

Short, sharp, no-fuss writing on marketing and business — the kind you can read in the time it takes for coffee to cool. No padding, no "10 tips" filler. Every piece earns its place by saying something useful: a framework that actually works, a number that changes how you'd decide, a take that's been tested against a real budget or a real campaign. If it doesn't change how you'd act on Monday morning, it doesn't get published.

Read the Articles →
02
Read · Narrative

Work Stories

Fictionalised, character-driven stories built from real situations — problem-solving, leadership, communication, the moments that actually shape a career. Each one is set inside a different work culture: EU, US, India — because the unwritten rules of how decisions get made, how feedback lands, and how trust gets built change completely depending on where you're sitting. These aren't case studies. They're stories you remember, that happen to teach you something about how the corporate world actually works in different parts of it.

Read the Stories →
03
Listen · AI-Produced

Podcast

Not everyone wants to read. Some ideas land better spoken out loud, walked through, explained. This stream takes the Articles and Work Stories and turns them into AI-produced audio episodes — built to make the thinking more intuitive, not just more accessible. Same ideas, different door in: for the commute, the gym, or whenever reading isn't an option but learning still is.

Listen to Episodes →
04
Read · Fast-Moving

AI Use Cases

The bonus stream — and the one that changes the fastest. AI in marketing and business is an ocean right now, not a topic: new tools, new workflows, new ways to do the job, almost every week. This gets its own space instead of getting buried inside Articles, because it deserves to be tracked on its own timeline — real, specific use cases from actual work, not generic "AI tips" you've already read fifty versions of.

See the Use Cases →
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