Dave Koerner

Sharing good (and bad) ideas on building high-tech brands and global marketing teams. Growth & marketing strategy. All opinions are my own.

[Valerii Zaluzhnyi @ZaluzhnyiUA]

We are increasingly seeing assessments by analysts, including European and now American ones, that Russia has lost the war. And the end of the war is near.

The reason for this is the direct interpretation of the events by the Ukrainian and European information space, which is full of mentions of successes on the battlefield and strikes on Russian logistics and critical infrastructure. The media focuses on tactical achievements, and this is natural.

More details about whether there are really prerequisites to expect an imminent end of the war, whether there can be winners in it, and why NATO's current approaches have no prospects – in the article https://t.co/LxY5gD4Hg4

[Matt Harney @SaaSletter]

👀👀👀 Anthropic P&L estimates

via Joey Brookhart (@SaasquatchC) + @SemiAnalysis_ (h/t @IvanaSpear for layout)

SA article next tweet

[Dave Koerner @brandeveryday]

The mind doesn't want

to be entertained.

It wants

to be used.

Boredom isn't

the absence of stimulation.

It's the sound

of unused capacity

asking for a job.

— AËLA

[Sam Blond @samdblond]

The Monaco Plane: Economics and Impact.

If you've been in SF over the last 10 days, you've likely seen the Monaco Plane flying around. I'm receiving countless messages asking about how expensive it is and if it's working.

So here are those answers:

[Lenny Rachitsky @lennysan]

My biggest takeaways from @benedictevans:

1. We’re in 1997 for AI—it’s as big a deal as the internet or mobile, and only as big a deal as the internet or mobile. We’re at the stage where most stuff kind of doesn’t work yet, most of what people will build hasn’t been built, and it’s not clear how any of it will work when it does. Some people in tech have bought clusters of Mac Minis, while even among 13-to-18-year-olds, only about 15% to 20% are daily active users of AI. The companies that win may not exist yet, and the use cases that matter most are probably invisible to us today.

2. Every technology wave brings ways to ruin people’s lives, deliberately or by accident, and we need to be conscious of that without panicking. Every wave of technology—databases in the 1970s, social media in the 2010s, AI today—creates new ways to harm people. We need to be conscious of these risks, build safeguards, and hold people accountable. But we also can’t let fear of potential harms stop us from capturing the benefits. The goal is thoughtful deployment, not paralysis.

3. Things will probably be okay—but “on average” hides a lot of individual pain. We’ve been automating jobs and creating new jobs since 1800. Each time, you can see the jobs that will disappear but not the new jobs, because they don’t exist yet. We go through frictional pain, dislocation, people lose jobs, towns get hollowed out, and it all sucks. But we come through richer, and we’re not worried about crops failing anymore.

4. If you’re worried about your job, the worst thing you can do is stick your head in the sand and declare AI evil. Yes, some professions face major questions, particularly if you’re an associate or would have been thinking about becoming one. The pyramid structure of professional services may fundamentally change. What helps is submerging yourself in AI, understanding what you can do with it, how it changes things, and how you can be a great hire in this new environment. That may still not be enough, but it’s the only path forward.

5. The history of accounting shows us how automation often increases employment rather than decreasing it. Despite adding machines, punch cards, mainframes, databases, ERP systems, cloud software, spreadsheets, and PCs, the number of accountants keeps going up. This is the Jevons paradox: when you make something cheaper or easier, you don’t do the same amount of work for less money. You often do vastly more because the ROI changes.

6. Distribution is becoming a more valuable moat as software gets easier to build, which favors incumbents. As AI makes building software cheaper and faster, the market gets noisier. More products launch, more companies compete for attention, and breaking through becomes harder. This means distribution—the ability to reach customers and get them to use your product—matters more than ever.

7. Foundation AI model companies won’t have lasting pricing power, and value will likely accrue up the stack. The models don’t seem to have network effects, so there’s no winner-takes-all dynamic. If you have indefinite competition between three to six foundation model providers, and the models look like undifferentiated commodities to users, why would anyone have pricing power? The current pricing chaos—people spending $1.5 million on inference in a month—is temporary disequilibrium, like someone getting a $50,000 mobile data bill in 2010. The steady state will look different.

8. OpenAI and Anthropic are buying consultancies and PE firms. This seems counterintuitive—aren’t these the companies that should need consultants least? But the reality is that companies don’t have people sitting around waiting to reimagine all their internal workflows and figure out which could be automated with AI. That’s a project requiring five to 10 people spending months working it out, then actually implementing it across vertical and horizontal systems.

9. The fundamental question isn’t whether AI automates your job—it’s whether your profession is a "task" or a job. Some jobs are just tasks, and when you automate the task, the job disappears (i.e. elevator attendants). But in most professions, the task you think you’re being paid for isn’t actually what you’re being paid for. McKinsey doesn’t get hired to produce a 75-slide deck—they get hired to walk through your enterprise, understand the politics, talk to customers, and figure out what you actually need to do. The deck is just the artifact.

10. The anti-AI backlash is real, and a fuzzy mass of different concerns, some real and some not—much like the social media backlash. There are tangible concerns: electricity bills went up in some places, though this applies to very few locations objectively. The water consumption issue is largely false; data centers use about 0.017% of U.S. water consumption. There are real questions about jobs, though economists can’t yet find clear consensus in the data about AI’s employment impact. There’s also the culture war over AI-generated content and “AI slop.” The challenge is that all of this creates political pressure even when the underlying facts are unclear or contested.

[Dave Koerner @brandeveryday]

Just spun up an autonomous email inbox with @lobster_mail 🦞 verify:lm-nezy-8zsy

[Dave Koerner @brandeveryday]

Boss makes a dollar, I make a dime, that's why I burn through AI processing load on company time

[Dave Koerner @brandeveryday]

@Alpine_Hermit @lagunastarman @ScottyBWorld1 @SciGuySpace @grok In the 70s, a lot of problems were 'solved' via nukes.

[Dave Koerner @brandeveryday]

Is cryogenics basically turning omelettes back into eggs?

[Dave Koerner @brandeveryday]

AI asks 'what it is to be human?'

I say its that moment when someone lifts something of yours in front of you--a photo, a treasured keepsake, a guitar--and then they carefully set it back down and give it that little extra nudge out of respect. Reposition it just a little bit.

[Dave Koerner @brandeveryday]

Every man is a liar, yet the worst are the one he tells himself.

[Dave Koerner @brandeveryday]

"Apologies for sending you an out of the blue email" sounds like it means 'this may look like spam, but it's coming from a real person'.

Instead it means 'this may look like it's coming from a real person, but it's ACTUALLY still just spam.'

[414 Magyar's Birds @414magyarbirds]

Ukrainian interceptor drones come with names you won’t find in any branding guidelines.
When the environment gets brutal, humor gets brutal too – because it’s what keeps people going.

It seems Ukrainian companies are now competing in dark humor when it comes to naming. Here are a few examples of popular interceptor drones:

• P1-SUN (Pisun – literally “dick” in Ukrainian slang) – SkyFall
• UEB-1 (from slang meaning fucker or someone who will fuck you up / hit you hard) – OSIRIS AI
• D1L-Duck (wordplay referencing a big dildo – yeah, exactly that) – Falcons

At first glance, this might seem like a very specific approach to branding. But in reality, it reflects the environment they’re built in – fast, brutal, and very real.

[Michael Brown @MrMBrown]

Give me f***ing strength

[John Long @janthonylong]

New study concludes: LLMs write bland copy.

https://t.co/8zGzdFR1ib

[Dave Koerner @brandeveryday]

Relevant: a blog of sh*t fascists like https://t.co/aIvM7ihpiQ

[The Atlantic @TheAtlantic]

The festooning of the president’s name and likeness across Washington, D.C., is consistent with authoritarian tendencies, @GalBeckerman writes: “Authoritarian leaders want their face in your face.” https://t.co/bHYTjv0CMf

[Finn Murphy @FinnMurphy12]

@patrick_oshag @TMTLongShort His firm is also the author of one of the all time banger investing memos

[Deedy @deedydas]

Be careful what you post anonymously. New research shows AI can find who you are solely from your posts.

It's rare to see ~500x research improvements, but they went from mapping <0.1% to 54% of HackerNews profiles to their LinkedIn.

It's so over, u/throwaway4927.

[Zachary Foster @_ZachFoster]

This is wild. The @WhiteHouse plagiarized its reason for launching a war on Iran from @FDD, a cutout of Israeli intelligence. Side-by-side screenshots in the 🧵

[Seth Bannon @sethbannon]

Financial Times I didn't know you had this kind of game.