The executive behind the intelligence
Builder. Marketer. One of the few people writing about AI who was deploying it in production long before the rest of the internet decided to have opinions about it.
The backstory
Most people writing about AI have never built a business with it. Pierre has been running it in production since 2012 — through three generations of machine learning, two IBM Watson engagements, Amazon's early AI tooling, and everything that followed.
The career started the hard way: cracking social media advertising when Fortune 500s were spending serious money and producing near-zero returns. That gap between what technology promised and what it actually delivered in real business conditions became an obsession. It still is. The core work has never changed: take complex technology, strip out the noise, and build something that grows revenue.
Across fintech, real estate, lending, and direct-to-consumer platforms, Pierre helped build RealtyMogul into the platform that put institutional-grade real estate investing within reach of everyday Americans — helping regular investors across the country make hundreds of millions of dollars in returns that had previously been reserved for the ultra-wealthy. He contributed to taking Modiv Industrial public as the first direct-to-retail real estate investment platform to complete an IPO. He was central to the marketing campaigns that flipped the U.S. House of Representatives in 2018. A career totaling more than $1.5 billion in client value. None of it was theoretical.
Machine learning entered the picture around 2012 — long before it was a useful dinner-party topic. Then IBM Watson in 2018. Then Amazon's early AI tooling. By the time ChatGPT arrived and suddenly everyone had opinions, there were years of real deployment, calibrated failure, and hard-won judgment already in the bank.
PromptHacker launched in 2023 with a clear premise: most AI content is written by people who have never built a business with it. Every issue is run through the same standard that has driven $1.5 billion in client value: does this actually work in production, and does it move the needle? If the answer is no, it does not make the brief.
Key milestones
The editorial standard
Every AI development that appears in the brief has passed all four gates. This is what separates intelligence from noise.
Does this change how a business operates, competes, or earns? If the honest answer is no, it does not make the brief — regardless of how impressive the benchmark looks.
Tools and developments are evaluated against real business conditions, not demo environments. If something only works in a controlled showcase, that gets noted or it gets cut.
What is available to deploy right now by a business without a dedicated AI engineering team. Research papers and waitlisted products are interesting — they are not intelligence.
Every claim is traced to official announcements, documentation, or primary reporting. No secondhand summaries, no marketing copy treated as fact.
The lens everything gets viewed through
"It takes human intelligence to understand how to get the most out of artificial intelligence."
A new model release is not a story. A new capability that helps a business close deals faster, eliminate a recurring cost, or serve customers without adding headcount — that is a story. Every development in the brief gets reduced to first principles: what does this actually change, and how does that translate to productivity and profit?
Most AI coverage tells you what happened. PromptHacker answers the only question that matters to an executive: what should I do with this by Friday? Artificial intelligence generates capability. Verified human intelligence decides how to use it. That distinction is everything — and it is exactly what separates a useful briefing from another recap of a press release.
Pierre is a Mensa member. That is not a personality detail — it is the engine behind the analysis. Every new model, every capability release, every workflow claim gets subjected to the same rigorous reduction: what does this actually change for a business that needs to perform on Monday? The answer to that question is what readers get. Not what the technology can do in a demo. What they should specifically do with it, how far they can push it before it breaks, and where the compounding advantage actually lives.
Who reads PromptHacker
Stays current on AI without drowning in noise. Reads to understand what is actually changing, cut through vendor hype, and keep a clear edge on competitors who are still guessing.
Not content just reading about AI. Wants verified, tested workflows running inside their business. Reads to find the next automation that frees up genuine time and multiplies output.
Building AI capability across an organization, not just optimizing their own workflow. Reads to understand where the technology is going and how to position their team ahead of it.
Beyond the brief
Every year, more work moves to systems that run without being asked. That compounding effect is what has allowed Pierre to split time between Miami, Dubai, and the South of France without losing momentum. The locations are not the point. The freedom is. Every workflow and tool covered in the brief is evaluated through that same lens: does it genuinely free up time, multiply output, and return control over how you spend your hours?
Productivity tools get marketed as ways to do more. The better frame is doing less manually so your time goes somewhere worth spending it. Every automation covered in the brief is evaluated first by how much genuine time it returns — not how impressive it looks in a demo.
The AI activities in every Kids section get tested on Pierre's daughter before they make the brief. She is training to become an astronaut, has already piloted aircraft, and builds robots in her spare time. If it does not hold her attention and challenge her, it does not make the issue. The bar is deliberately high.
Most AI coverage is written by people impressed by the technology. The brief is written by someone who has been deploying it in production since 2012 and learned to separate what works from what benchmarks well. When consensus points one direction, that is usually the moment to look harder at the other.
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Verified AI developments distilled into executive-grade action. Every issue written by someone who has deployed AI across $1.5 billion in client engagements.