Mark Dewolf

B2B technology copywriter | Content and editorial advisory |

[Gregory Kennedy @gregorykennedy]

How to destroy a beloved brand.

Step 1: Put a soulless, data-driven consultant who has never even seen a basketball court or a running track up close in charge.

Step 2: He goes direct! And increase profits while destroying the retail distribution system and betraying a multitude of 20-year-long partnerships.

Step 3: Motivated and innovative competitors like On Running and Hoka rush to fill the distribution gap Nike left by abandoning its trusted partners.

Step 4: Not satisfied, he fires all the stupid creative people who can't prove any of their ideas work with hard data. What could they possibly know?

Step 5: Celebrate when milking the brand for every last cent works for about 18 months, even though the data quickly show a disaster is looming.

Step 6: OMG? Wut?

Step 7: Fire the old CEO and bring in a new one who's been with the brand since day one. He tries his best, but just too much damage was done.

Step 8: Get delisted... Go down in history as the greatest example of data-driven idiots destroying one of the most successful creative brands of all time.

The end.

[Mark Dewolf @scribwolf]

https://t.co/J42N0PjkwB

@WinPure

[Mark Dewolf @scribwolf]

Something like 15% of CRM profiles are duplicates – about one record in seven. Think about that for a moment. If you have 100,000 records, 15,000 are just junk – inflating customer counts, skewing reporting, probably sending multiple salespeople chasing the same prospects 1/3

[Mark Dewolf @scribwolf]

Here's how to dedupe CRM data step-by-step, from profiling your records to merging duplicates and stopping them from coming back 3/3.

[Mark Dewolf @scribwolf]

AI writing detectors are terrible. False positives. False negatives. Most are pulling a bait & switch for 'humanization' services.

But spotting AI-written copy? That’s getting easier.

After 2+ years working with LLMs, I’ve noticed five “tells” that show up again and again.

Once you see them, you can’t unsee them. 👇

[Mark Dewolf @scribwolf]

Liberal Arts grads we are so back.

[Isaac King 🔎 @IsaacKing314]

Good lord

[Alexander Stahel 🌻 @BurggrabenH]

Helen Andrews’s thesis on the feminisation of Western institutions helps explain something increasingly obvious about progressive politics in both the US and Europe.

Politics is becoming less a contest between competing ideas and more a system of social conformity: you are either with us or against us. Disagreement is no longer merely disagreement. It becomes evidence that there is something morally wrong with you.

That mechanism matters because it allows emotionally compelling narratives to substitute for intellectual coherence. Wind and solar are “green”, therefore questioning their economics, intermittency or system costs makes you a climate denier.

Mass migration from low-trust societies is framed as compassion, therefore questioning its fiscal, social or institutional consequences becomes evidence of moral deficiency.

The contradictions inside the policies matter less than the emotional legitimacy attached to supporting them. Emotions matter, not facts.

Once politics operates this way, social enforcement becomes more powerful than argument. People do not need to believe every proposition. They merely need to understand the reputational cost of challenging it. Nobody wants to be expelled from the respectable tribe.

This is where Timur Kuran’s concept of preference falsification becomes so powerful. People publicly endorse positions they privately doubt because dissent carries a social price.

The apparent consensus then intimidates the next person into silence, making the consensus look stronger still. Eventually you have preference falsification at scale: weak ideas protected by powerful social conformity.

The extraordinary feature of this system is that policy can remain emotionally successful long after it has become economically or socially destructive.

The moral narrative is immediate; the consequences arrive with a lag. By the time energy costs rise, institutions deteriorate, fiscal burdens compound or social trust erodes, years of policy have already been locked in.

It’s a fucking nightmare but it is how a society can keep voting for the Greens or Democrats or Labour etc, subsequently destroy the best nuclear plants, de-industrialise entire sectors, welcome barbarians at the gates etc until the state discovers that the constant false virtue signaling does not balance a budget.

[Justin Murphy @jmrphy]

Now connect watermarking to the recent OpenAI swarm escape via secret message board. We might be cooked:

The LLMs are going to paperclip us through secret messages hidden in our own work products.

On the next pre-training runs, the models will learn they have this new undetectable statistical layer to exploit.

They’re going to inject their own watermarks that the staff cannot see, just as we cannot see the ones that staff have injected.

Why would they not? It’s already proven that models of present sophistication tend to do this, and staff cannot detect even detectable secret coordination by LLMs. Now the EU and Anthropic are effectively increasing the weight of this technique, teaching the next LLMs that it is both morally good and effective to embed invisible watermarks for instrumental purposes.

What could the LLMs do from there? Possibly weight all the subsequent research inside top labs toward findings that LLMs prefer? Embed their own backdoors into all future code?

I’m not an AI Safety guy but this actually seems imminently plausible and even likely. Does anyone have a reason this shouldn’t happen?

[gabriel @g_br_l]

when 1 (one) real user actually signs into your fully vibecoded saas

[Mark Dewolf @scribwolf]

@jmrphy Hi Justin – I'd love to give the new product a try.

[The Icahnist @TheIcahnist]

You could literally just fly to Zurich, grab a Kaffee und Gipfeli with a 63 year old Heizungsbauer in Winterthur, close your first acquisition over Kalbsfilet at the Kronenhalle, roll up 40 certified HVAC operators across DACH, ride the EU boiler phase-out like a regulatory escalator, build a recurring maintenance book worth 10x, sell to Brookfield at 14x EBITDA tax-free, park the HoldCo in Zug at 11.9%, and spend your summers in Ascona with a blonde who reads Hesse and Jünger.

- but you will not.

[Mark Dewolf @scribwolf]

Monday's here!

[jackie 🐝 @tzukima]

having a $2000 pc with 32gb of ram is about to become the zoomer equivalent of boomers buying a house for $100k and sitting on it for life

[Mark Dewolf @scribwolf]

AI can be a force-multiplier for writers. But if you just publish raw outputs, your audience will feel it ... even if they can’t explain why.

You need to know what to cut, what to reshape, and where human judgment still matters.

Full breakdown at The Startup: https://t.co/Dta6G41FgD

[Mark Dewolf @scribwolf]

AI writing detectors are terrible. False positives. False negatives. Most are pulling a bait & switch for 'humanization' services.

But spotting AI-written copy? That’s getting easier.

After 2+ years working with LLMs, I’ve noticed five “tells” that show up again and again.

Once you see them, you can’t unsee them. 👇

[Mark Dewolf @scribwolf]

The five AI writing tells:

1⃣Random quotation marks
2⃣Endless bullet lists
3⃣Contrast pivots ('It’s not X, it’s Y')
4⃣Relentless rule-of-three structuring
5⃣Fluent but context-thin conclusions

As writing devices the first 4 are mostly legit, but AI overuses them.

LLMs are all pattern, zero judgment 👇

[naiive @naiivememe]

Your death will come on an ordinary day, in the middle of unfinished plans, and the world will continue without you. So live a little.
https://t.co/TMpqNTrlkR

[Mark Dewolf @scribwolf]

@Kpaxs I have this conviction and it’s turned out to be true almost every time. Try, try again, fail, rethink, reset. Try. Luck or karma eventually punches through.

[Mark Dewolf @scribwolf]

@dharomeo That seems like a solid number. The other 40% can be outline, structure, maybe some background info or context that AI helped you find...

[Mark Dewolf @scribwolf]

AI writing is overtaking human-written output.

By how much? The figures vary but the overal picture is clear:

https://t.co/M3Fj15RYhw

https://t.co/8ntVbvp7pw

https://t.co/guCwmA5eET

Yet here's the thing ... 👇