Field Notes
Personal thinking, field observations, and operating frameworks on AI product marketing, search evolution, community growth, and explaining difficult technology.
My personal playbook for growing on X (if you're a founder / expert in a particular niche)
A stage-by-stage playbook for growing on X from 0 to 10K+ followers as a founder or niche expert, based on 3 years of analytics and advising creators.
AI in account-based marketing: signal or surveillance?
AI has turned account-based marketing into a real-time listening system on the web. The big question for founders and marketers now isn’t whether it works—but whether you’re using it as honest signal or quiet surveillance.
When your AI can't remember you: fixing the memory problem for agents
Why most AI agents feel forgetful, and a simple, practical pattern for giving them persistent memory without fighting the context window.
Where AI agent mode actually helps—and where it fails
AI agents promised to be digital employees that handle the messy, multi-step work we don’t have time for. The reality is more mixed. Here’s where agent mode quietly shines today—and where it still trips over its own autonomy.
Why reusable AI skills are quietly becoming the new app layer
Claude Code skills show how reusable AI behaviors are turning agents into app platforms—and why a small, opinionated stack often beats installing everything.
Brand safety in the age of generative ads
As AI starts writing our ads and making our images, the line between ‘official’ and ‘fake’ brand communication is blurring fast. Here’s what that means for founders and marketers—and how to stay on the right side of trust.
The AI marketing stack is getting out of hand
Marketers adopted AI to move faster. Instead, many teams now spend their days switching tabs, reformatting outputs, and managing tools that were supposed to save time.
AI video just hit the copyright wall
Disney’s fight with ByteDance over its Seedance 2.0 video model shows what happens when generative AI collides head‑on with decades of entertainment IP.
If the AI has seen the test, what are we really measuring?
Why data contamination in large language models makes some AI benchmarks feel more like an open-book exam than a real test of intelligence—and what builders should do about it.
Community-led growth: moat or unpaid support?
Community can be a growth engine or a clever way to get customers to do your support for free. The difference isn’t vibes—it’s how you design, resource, and measure it.
Claude Code vs Cursor: Autonomy Versus Control
AI agents promise hands-off automation, but most real-world teams are still wrestling with a basic question: how much autonomy do you actually want to give your code?
AI cold email: when scale turns into spam
Everyone wants ‘personalization at scale.’ Recipients just see more spam. Here’s what happens when AI cold email crosses the line—and how founders can keep the channel alive.
Distribution is eating content: why your best work is still invisible
Great content is now just the starting line. The brands and creators who win are the ones who treat distribution as the real product.
AI content isn’t killing your SEO. Generic content is.
Founders aren’t losing rankings because they used AI. They’re losing because they shipped generic, unhelpful content at scale. Here’s how to keep the efficiency and protect originality and search performance.
When AI remembers your book a little too well
New research shows leading AI models can recreate huge chunks of famous novels almost word-for-word. That’s more than a quirky lab trick—it strikes at the heart of how we think about training data, creativity, and copyright.
Deepfakes, disappearing jobs, and the slow collapse of digital trust
AI isn’t just eating tasks—it’s chipping away at what we trust, how we work, and who we believe. Here’s what that means for work, fraud, and weapons, and how to respond without panic.
Does AI personalization improve email marketing?
AI can make email feel more relevant, but only when it is fed real customer data and guided by human judgment. The promise is not magic copywriting; it is better targeting, smarter timing, and fewer generic sends.
The founder-led marketing dilemma: when to keep it in-house and when to hire help
Founders often think the choice is simple: do the marketing yourself, hire a team, or bring in an agency. In practice, the real question is who should own the learning, the message, and the first wins.
Is GEO real, or just SEO with a new name?
Marketers are arguing over whether generative engine optimization is a new discipline or just SEO in a fresh wrapper. The truth is less dramatic, but more useful: GEO changes what you are trying to win, even if many of the tactics still look familiar.
Performance Max and the trust gap: why marketers feel gaslit by “great” results
Google’s Performance Max promises effortless, AI-driven growth. Many marketers are seeing big numbers—but aren’t sure they can trust them. Here’s what the tension looks like on the ground, and how to respond as a founder or marketing lead.
Google’s AI Overviews vs. Your Organic Traffic: What Founders Need to Do Now
AI Overviews are quietly rewriting how people use Google—and for a lot of businesses, that means more impressions, fewer clicks, and a very different marketing game. Here’s what’s really happening and how to respond.
When local GPUs beat the cloud API — and when they don’t
For most AI workloads, APIs are still the cheaper, simpler choice. Local GPUs only start to make sense when privacy matters or when you can keep the hardware busy enough to squeeze out every last token.
Will AI Make Humanities Skills More Valuable?
As AI gets better at technical work, the real differentiator may be skills we usually associate with the humanities: critical thinking, communication, and understanding people.
“The click never shows up”: Making sense of influencer ROI when attribution breaks
Founders are pouring money into influencers while feeling blind on ROI. The problem isn’t the influencers—it’s how we’re trying to measure them. Here’s the story of that tension, what’s changed, and how to build a practical framework that respects the messy reality of modern attribution.
Why people still run AI locally when cloud models are stronger
A look at why local AI keeps growing: privacy, control, hardware tinkering, and the simple satisfaction of making a model run on your own machine.
Why marketing attribution keeps failing (and what to do about it)
Teams keep trusting attribution dashboards like they’re the truth—and keep getting burned. Here’s why the models fail, how practitioners are adapting, and what founders and marketers can do differently.
AI memory is the new lock-in nobody’s talking about
As AI tools start remembering everything about us, the real power shift isn’t in the models—it’s in who owns the memory. Here’s what that means for builders, businesses, and anyone betting on AI.
Can one person really build a billion-dollar company with AI?
AI agents are turning a wild thought experiment—the one-person billion-dollar company—into a real strategic question. Here’s what’s hype, what’s changing, and how founders can use the shift without losing the plot.
When organic reach stops feeling organic
Marketers keep asking the same question because the experience keeps repeating itself: the same post, the same cadence, the same audience, and a tiny fraction of the reach. The answer is less dramatic than “social is dead,” but more sobering than “just post better.”
When the algorithm grabs the wheel: marketers, control, and the new AI ad reality
Across Google, Meta, and other platforms, AI-driven ads promise better performance—but many marketers are discovering they’ve quietly lost the ability to steer. Here’s what’s really changing, and how founders can protect results without clinging to the past.
Giving AI a Memory That Feels Like Yours
Why a portable memory layer across AI models may be the missing piece for truly useful AI—plus what builders can do about it today.
“Fair” or “predictable”? The AI pricing question every founder keeps tripping over
AI made it easier to deliver magic, but harder to put a price tag on it. Here’s how founders are quietly figuring out what “fair” pricing looks like—without scaring off buyers or burning through GPU bills.
When AI makes your product easy to copy, PLG stops being the whole story
In an AI-shaped market, the product you ship is easier to imitate, which means product-led growth has to work harder to create a real business—not just a fast-moving feature.
Do you really need a reasoning model?
Everyone’s talking about ‘reasoning models’—but are they actually useful for your work, or just slowing everything down? Here’s a grounded look at what they’re good at, where they fall short, and how to use them without drinking the hype.
Are AI 'reasoning traces' really reasoning?
Why AI models' thought chains all look the same, what that reveals about how they’re trained, and what builders should actually trust.
The community marketing mistake that still trips up founders
The hardest part of community marketing is not finding places to talk. It is learning when to speak like a member and when to mention what you built.
AI search and the slow death of “free” traffic
AI search isn’t killing SEO overnight, but it is quietly gutting the old promise of free, compounding traffic. Here’s what founders and marketers are seeing on the ground—and how to adapt before the floor drops out.
Can small language models really power useful AI agents?
A growing group of builders is proving that tiny, local language models can drive practical AI agents—if you give them the right scaffolding and guardrails.
Will AI really replace software engineers by 2027?
Anthropic says AI will do most, maybe all, of what software engineers do within a year—and some leaders inside the company claim no one writes code by hand anymore. Here’s what that actually means for people who build software, and how to respond without either denial or panic.
Vibe coding vs. real customers: why so many AI SaaS projects stall
A lot of AI builders can code circles around their peers—but struggle to ship anything customers actually pay for. Here’s why the gap between 'vibe coding' and production-ready SaaS is so real, and how to cross it.
Robots won't take your job. They'll bury you in work.
AI was supposed to free us from busywork. For many knowledge workers, it's doing the opposite: shifting the job from doing the work to supervising an endless stream of machine-generated output.
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