Bitte gehen Sie weiter. Hier gibt es nichts zu sehen.

Andate pure avanti, qui non c’è niente da vedere.

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It’s such a weird thing to feel this want to have more, even though there’s no real reason. I guess I wanna do what my dad did.

Collaboration night malam ini dibuka dengan sambutan dari para direktur utama pemegang kepentingan project dari beberapa perusahaan yang terlibat. Seperti biasa, ucapan terima kasih dan apresiasi kepada seluruh pihak yang sudah membantu menyukseskan salah satu project terbesar mereka.

Setelah seluruh rangkaian kegiatan formal telah berlangsung, sekarang sudah masuk sesi free time dimana seluruh undangan dapat berbincang dan menikmati hidangan yang sudah disediakan.

Bian memanfaatkan momen ini untuk memperluas relasinya sebagai orang baru, dia berbincang dengan banyak direksi khususnya para direksi NODUS yang juga hadir pada acara malam itu. Setelah puas berkenalan dan berbincang singkat, Bian mengambil segelas white wine lalu berdiri di area yang langsung menghadap balkon.

Sesekali ada beberapa perempuan yang mengajaknya bicara dan menawarkan untuk bergabung dengan mereka. Sabiano tetaplah Sabiano, dia tidak tertarik dan langsung menolak dengan sopan tawaran apapun yang tidak berhubungan dengan kepentingannya.

Bian melirik ke arah jam tangannya, waktu menunjukkan pukul 10 malam. Dia sudah merasa cukup dan berniat untuk meninggalkan tempat itu, tetapi matanya melihat sesuatu yang menarik perhatiannya.

Kai sedang berada di balkon dengan seorang perempuan yang tidak Bian kenali. Niatnya untuk pulang seakan hilang begitu saja saat melihat interaksi Kai dengan perempuan itu, mereka berbicara dan bercanda seakan sudah kenal sedari lama. Perempuan itu bukan salah satu team NODUS jakarta yang berangkat bersama mereka, maka dari itu Bian benar-benar asing dengan perempuan tersebut.

“Bukan urusan gua sih harusnya, lagian semua orang wajar punya kenalannya masing-masing juga.” Pikirnya.

Sesaat Bian berniat untuk benar-benar pergi kali ini, dia melihat perempuan itu perlahan mendekatkan tubuhnya ke arah Kai. Bian bingung, menurutnya itu bukan interaksi antara rekan kerja yang sewajarnya apalagi dia tau Kai sudah punya kekasih.

Beberapa detik kemudian, Kai terlihat tanpa ragu membalasnya dengan pelukan singkat. Balkon tersebut memang sepi, karena semua orang lebih memilih fokus menikmati acara di dalam ballroom.

Bian yang telah jelas melihat semua yang ada di depan matanya, langsung memutuskan untuk pergi dari tempat itu.

Perasaan nya campur aduk, dia tidak tahu harus apa dengan kejadian yang dia lihat tadi. Haruskah dia berpura-pura tidak tahu apa-apa dan menganggap ini bukan urusannya seperti hal biasa yang dia lakukan?

Imagine your neighbor wants to sell you her small bakery. She makes $10,000 a year in profit after all expenses. How much would you pay for it?

This is the most fundamental question in investing, and surprisingly, many people completely ignore it when buying stocks. They chase companies with cool products, exciting growth stories, or buzzy news coverage. However, the only reason to buy an individual stock is if you believe the current price is too low.

Not because the company is growing fast. Not because you love their products. Only because other investors have underestimated what the company is actually worth.

The Bakery Test

Let’s go back to your neighbor’s bakery. It makes $10,000 per year. If she wants $50,000 for it, that’s a P/E ratio of 5—meaning you’d pay $5 for every $1 of annual profit. At that price, if profits stay steady, you’d earn back your investment in five years.

If she wants $200,000? That’s a P/E of 20. Now you’re paying $20 for every $1 of profit. It’ll take twenty years of steady profits just to break even. You’d need to believe the bakery’s profits will grow substantially to justify that price.

And if she wants $1,000,000 for a bakery making $10,000 a year? That’s a P/E of 100. You’re paying a hundred dollars for every dollar of current profit. You’d need to be absolutely certain this bakery is about to explode in popularity—that the $10,000 today will become $50,000 or $100,000 in a few years—otherwise, you’re massively overpaying.

AMD: A Real-World Example

Now let’s look at AMD, the chipmaker. As of late January 2026, AMD trades at roughly $250 per share with a P/E ratio around 130.

What does that mean in plain terms? For every share you buy, you’re paying about $130 for each $1 of AMD’s current annual earnings per share.

Think about that in bakery terms. If AMD were a local business earning $10,000 a year, you’d be paying $1.3 million for it.

For comparison, the S&P 500—a basket of 500 large U.S. companies—trades at a P/E of about 28. The average stock costs you $28 for every $1 of earnings. AMD costs you nearly four times that.

So Is AMD a Bad Investment?

Not necessarily. Here’s where the math gets interesting.

When you buy AMD at a P/E of 110, you’re making a bet. You’re betting that AMD’s profits will grow dramatically—so dramatically that today’s price will look cheap in hindsight. You’re betting that the consensus view of AMD’s future (which is already optimistic, hence the high P/E) still underestimates how well the company will actually do.

The market already expects AMD to benefit from the AI boom, from data center growth, from capturing market share from Intel. That expectation is baked into the price. For AMD stock to go up from here, the company has to exceed those already-high expectations. It has to surprise to the upside.

If AMD simply meets the already very high expectations? The stock probably goes nowhere. If it disappoints? It could fall hard.

Meanwhile, at a P/E of 110, even if AMD’s business performs brilliantly, you’re starting from an expensive base. Remember: you paid $110 for each dollar of current profit. That’s a lot of future growth already priced in.

Financial theory tells us that the correct price of a stock equals the present value of all the future cash it will generate for shareholders. The P/E ratio is a rough shortcut to understanding whether that future cash flow justifies today’s price.

The P/E ratio is your reality check. It forces you to ask: “What would this look like as a simple business? Would I buy a bakery at this price?”

The Question to Ask

Before you buy any stock, ask yourself one question: How much am I paying for each dollar of this company’s profits?

At a P/E of 15, you might be getting a bargain—or buying a company with dim prospects. At a P/E of 110, you might be buying a future titan—or paying a fortune for hype.

Neither high nor low P/E is automatically good or bad. But understanding what you’re paying, and what growth would need to happen to justify that price, is the difference between investing and hoping.

Your neighbor’s bakery makes this obvious. Wall Street makes it complicated. But the question is the same: Is the price right?

You never stop learning, and you can't know everything about your profession. Nice to see how you can improve your usage of HTML in your interface.

I found this bit and wanted to share it.

»HTML’s Best Kept Secret — The Tag: Every developer knows . It’s the workhorse of the web. But ? Most have never touched it. Some don’t even know it exists. […]« — by @denodell

🧑‍💻 https://denodell.com/blog/html-best-kept-secret-output-tag

---

96 of #100DaysToOffload
#log #dev
Thoughts?

Ik vond een opmerkelijke passage in de gepubliceerde brieven van schrijfster Joan Didion (1934–2021), over de zes therapiesessies die zij had gevolgd.

De therapeut probeerde haar ingewikkelde relatie met haar geadopteerde (inmiddels volwassen) dochter bloot te leggen, om wellicht wat lichtheid te brengen tussen die twee.

Joan vertelt dat ze vroeger als kind nooit dagdroomde over een prinses zijn of over trouwen en kinderen krijgen.

Sterker nog. Haar kinderfantasie was dat ze zichzelf, met een zonnebril op, ergens in Zuid-Amerika de rechtbank uit zag lopen. Daar waar ze net de scheidingspapieren had getekend.

Dat was haar kinderfantasie.

Waarna de therapeut droogjes opmerkt: ‘Vind je dit niet een opmerkelijke fantasie? Ik ben nog nooit iemand tegengekomen die als kind fantasieën had over echtscheidingen.’

Ja.

Dit kun je natuurlijk helemaal ontleden als therapeut. Welk verdriet ligt hierachter? Joan, die haar gehele leven met depressieve periodes kampte, had blijkbaar als kind al donkere gedachten over de wereld.

Maar dan moet ik ook denken aan mijn favoriete acteur Jesse Eisenberg (1983). Een man die ook al vanaf zijn jeugd worstelt met depressie, neuroses en angsten.

Hij vindt het eigenlijk gekker als je niet depressief wordt van deze wereld. Ik bedoel. Moet je eens zien wat een teringzooitje het nu is?

Ja. Inderdaad.

Laten we wel wezen. Het is natuurlijk ook veel vanzelfsprekender dat je ooit in je leven gaat scheiden, dan dat je lang en gelukkig leeft tot je dood met één persoon.

Ik zou zeggen: er is niets mis met je, Joan. Gewoon een kinderziel die de volwassen wereld al heel goed begrijpt.
(overigens bleef zij haar hele leven bij haar man)

Weet je wat het is?

Niet elk gevoel heeft een verklaring of oplossing nodig.

Het hoort ook gewoon allemaal bij het mens zijn. Als je er geen of weinig last van hebt, laat het lekker zijn zoals het is.

Als iemand als volkomen normaal overkomt, dan ken je die persoon nog niet goed genoeg.

Toch?

Mensen zijn raar. Dat is juist zo leuk en tegelijkertijd zo vermoeiend, maar ook heel mooi.

Niet al onze rare eigenschappen, gevoelens en gedragingen hoeven nader bestudeerd of opgelost te worden.

Mijn favoriete documentairemaker en ontregelaar Werner Herzog (1942) vindt zelfreflectie en therapie zelfs een façade. Hij noemt het de slechtste uitvinding van de 20ste eeuw.

Als je te veel zelfonderzoek doet, kun je nauwelijks meer leven met jezelf. Je maakt jezelf ‘onbewoonbaar’ als je op elke plek in je ziel een groot zoeklicht laat schijnen. Laat dingen in de schaduw zitten, zegt hij in zijn memoires.

Blijf mysterieus is zijn oproep.

Zit op zich wat in. Al lees ik zijn woorden meer als dat overbelichting alles lelijk maakt. Als in te veel in je eigen ziel wroeten. Te veel je eigen gedachten en gedragingen overanalyseren. Dat is niet helpend in je dagelijks functioneren.

Het maakt je te zelfbewust. En van te veel zelfbewustzijn word je de duizendpoot die gaat nadenken of hij de ene of de andere voet als eerste in beweging zet.

Daar krijg je ongelukken van.

Heb je wel eens je telefoon of je oplader goed bestudeerd? Het is precies dezelfde als die van iedereen.

Niet goed. Niet goed. Tijd om er weer een ziel in te blazen. Een persoonlijke touch.

Ken je die scène uit de film Meet the Parents (2000), waar Ben Stiller (1965) de luchtvaartmaatschappij belt over zijn koffer?

Hij probeert zijn koffer te openen met een sleuteltje en merkt dat het hangslot niet opengaat. Hij draait de koffer om en ziet dat het de verkeerde is. Vervolgens wandelt hij met de telefoon door de keuken en zegt:

“Yeah, you gave me the wrong suitcase. Uh-huh. Yes, it’s a black Samsonite. Uh-huh. Ok, well don’t you think that the Samsonite people, in some crazy scheme in order to make a profit, MADE MORE THAN ONE BLACK SUITCASE?”

Zo goed, deze grap.

Ja, dat is natuurlijk wat kapitalisme is. Geen handgemaakte kopjes, kleren of meubelstukken meer. Maar massaproductie. Voor iedereen.

• Elk huis een Billy-kast.
• Elk huis een Brabantia-prullenbak.
• Iedereen een zwarte Samsonite-rolkoffer.

Er zit zo weinig ziel in de producten om ons heen. Het voelt zo willekeurig. Het voelt zo actiegericht of zo.

Niet alleen in ons huis, maar ook in de straat.

Kijk eens naar straatlantaarns. Het enige wat ze doen is schijnen en lelijk zijn.

Allemensen.

Waar zijn die mooie lantaarnpalen van 150 jaar geleden? Die je nog wel eens in Parijs ziet staan?

Om maar niet te spreken over van die elektriciteitshuisjes. Allemensen. Had die architect vroeger geen dromen dan van mooie kastelen en toegangspoorten ontwerpen? Waar is de creativiteit heen? Waar is de liefde en aandacht heen? Waar is de drang heen om iets moois in ons leven te plaatsen?

Dan heb je zo’n heel mooi ontworpen nieuwbouwwijk en dan staat daar zo’n lelijk betonnen gebouwtje voor de internetkabels. Of de stroomkabels.

Voor wat? Geldbesparing? Efficiëntie? Zit je dan je hele leven uit het keukenraam te kijken naar zo’n foeilelijk gebouwtje.

==

Kleine bekentenis. Ik houd ervan als stoplichten en lantaarnpalen bestickerd zijn. Met reclame of quotes, of gewoon simpel een website.

Als je iets labelt, wordt het van jou. Dat is een regel.

Met die stickers brengen we weer een ziel in het object. Met graffiti op die elektriciteitshuisjes geven we er weer een persoonlijkheid aan.

We pakken de straat weer terug.

Daarom roep ik je op om dat ook te doen. In je eigen huis welteverstaan.
(Ik promoot geen vandalisme.)

Breng weer ziel in de producten die om je heen liggen.

Echt.

Doe het.

Schrijf er met een viltstift je naam op of de datum waarop je het hebt gekocht.

Grafeer het erin met zo’n graveerpen.

Verzin namen.

Als dat niet altijd gaat, koop blanco labels in de winkel, knip ze op maat, plak ze op je spullen en schrijf er woorden op.

Label je opladers, koffiezetapparaten en laptops.

Schrijf inspirerende quotes erop.

Maak een tekening.

Zet je initialen erop.

Geef instructies.

Zeg wat het is.

Verzin namen.

Maak het van jou.

Blaas er een ziel in. Als een dikke middelvinger naar de massaproductie.

De wereld is van jou.

Ik vernoem mijn spullen naar de Griekse goden.

Het fascinerende aan de Griekse mythologie is dat elke god en elk verhaal de menselijke tekortkomingen omschrijft. Maar ook de oerbehoeftes die we hebben. De dilemma’s die we in het leven tegenkomen.

De Griekse mythologie gaat over hoe het is om een mens te zijn. Het helpt om via deze bril naar de wereld te kijken. De Griekse goden zijn overal om ons heen en zitten in ons. De objecten die we om ons heen verzamelen, vervullen een behoefte in onze menselijke tekortkomingen.

• Mijn oplader heb ik vernoemd naar een Griekse god van het licht, Helios.
• Mijn AirPods heten Apollo. God van de muziek.
• Mijn Boox Palma, waar ik al mijn digitale boeken op lees, heet Athena. Godin van de kennis.
• Mijn dildo heet Zeus, met zo’n grote bliksemschicht. Nee grapje. Zo groot is die niet.

Verklaar me voor gek, maar het geeft een heel andere band met deze objecten die ik elk uur wel minimaal één keer aanraak.

Je jeugd was zo zorgeloos, omdat het nu niet meer zo is. Omdat je nu verantwoordelijkheden en rekeningen en toeslagen hebt.

Die conclusie kan je alleen als volwassen persoon trekken.

Elke keer dat je aan vroeger denkt, doe je dat vanuit het NU.

Je kijkt dus altijd met de blik van vandaag naar toen.

De betekenis van vroeger verandert daardoor elke dag opnieuw.

Therapie is in die zin een vorm van herschrijven van je geschiedenis.

Dat wat je blokkeert in je huidige leven, kan je via de therapeut over je jeugd opnieuw beoordelen.

Niet jij was het probleem. Niet eens je moeder. Het is gewoon iets dat van generatie op generatie wordt doorgegeven.

Daar komt het innerlijke kind om de hoek kijken.

Het innerlijke kind dat schreeuwt om een knuffel. Dat gezien wil worden. Dat eindelijk erkenning wil.

Al wil ik daar graag aan toevoegen dat je ook het contact met je innerlijke volwassene niet moet vergeten.

Kaboem pats.

Dit was een grap. Rustig maar. Niet zo serieus doen.

Goed.

Het innerlijke kind.

In therapietaal is dat de plek van oude angsten, onvervulde behoeften en overtuigingen die je als kind hebt opgebouwd.

Maak daar contact mee, zegt de theorie, zodat je een gezonder volwassen zelfbeeld kunt vormen.

Mijn favoriete Franse psychoanalyticus Jacques Lacan (1901–1981) zou hier zijn keel bij schrapen.

Volgens Lacan bestaat er geen onbeschadigde kern die wacht om gerepareerd te worden. Geen innerlijk paradijs waar je naar terug kunt reizen.

Je zelfbeeld ontstaat juist uit een tekort. Je leert wie je bent doordat je wordt aangesproken door anderen. Via de taal. Via de verwachtingen. Via de blikken van je ouders en leraren. Via het idee zo hoor je je te gedragen en zo hoor je te zijn.

Dat betekent dat je identiteit geen innerlijke waarheid is, maar een constructie. En die constructie kun je een beetje veranderen, maar nooit volledig afbreken.

Het innerlijke kind zegt: heel de wond uit je jeugd.

Lacan zegt: accepteer dat er altijd iets ontbreekt in je leven.

Het innerlijke kind zoekt emotionele afronding. Lacan betoogt dat verlangen nooit stopt. Dat elk ingelost verlangen, wordt opgevolgd door een nieuw gemis.

Bij het innerlijke kind is pijn iets wat je kan stoppen. Bij Lacan hoort pijn bij het mens-zijn.

Dat is een ongemakkelijke waarheid. Maar ook best bevrijdend. Want dan hoef je niet eindeloos je verleden uit te pluizen. Je hoeft niet eens je best te doen om je ‘authentieke’ zelf te worden.

Want het bestaat niet.

Dan blijft er iets heel simpels over.

Je bent niet gebroken. Je bent onvolledig. Zoals iedereen.

Ook al is dit natuurlijk ook maar een verhaal.

Daar zit wel een voordeel aan. We kunnen het blijven herschrijven.

Via Lacan. Via het innerlijke kind. Via welke theorie dan ook.

Zolang het je helpt. Zolang het je leven dragelijker maakt.

I don’t get uptight about much (that’s a lie — I get anxious and stressed about everything), but I do get uptight about accessibility.

I consider myself disabled due to multiple chronic illnesses, though I don’t have any mobility impairments. I don’t drive due to my illnesses, and my primary mode of transportation is walking, with public transit (fairly modest service in my metro area) as the secondary for injury, illness, or unwalkable distances.

As a result, I’m pretty passionate about pedestrian safety and accessibility, and today, in the aftermath of the Arctic storm that hit my city (and half the country), I saw my city fail — yet again — to take pedestrians, transit riders, and people with strollers or mobility aids into consideration at all.

Much of my commute (normally about 30 minutes) was impassable, thanks to the city’s negligence in clearing pedestrian crosswalks and curb cuts, making signals accessible (the berms on which they were mounted were often snowed in or plowed under), and not clearing sidewalks where private property owners (required to clear under city ordinances) had neglected their own duties. But let’s be clear — the city mandates the property owners do it because the city is obliged under the ADA to keep publicly provided pedestrian walkways clear and doesn’t want to maintain the manpower to do it. Property owners neglecting their responsibilities does not excuse the city from its own obligations under the ADA.

And the sidewalks weren’t even the worst — the crosswalks and curb cuts were the worst. I saw a couple with a baby — I see them walking most mornings — nearly slip and fall with their stroller in a crosswalk because the median wasn’t clear, the curb cuts weren’t clear, the road was still slushy, and the asphalt was slick. So two adults and a baby could have been injured. At the next block, they had to walk in the street with their baby in the stroller because the sidewalks weren’t clear and the pedestrian crossing signal was unreachable without wading in nearly knee-deep snow.

To get to my own workplace, I had to traverse a plowed mountain of snow and ice blocking the crosswalk and public sidewalk around about three and a half feet high in places. It was fully taller than the bench at the bus stop (which wasn’t clear and at which no rider with a mobility aid could have been safely let off with the ramp), and in one spot was about as tall as me.

The extra effort of walking in the snow made the journey just plain take longer, leaving me exposed to colder temperatures for longer (not good for one of my chronic conditions), and my blood sugar plummeted abnormally quickly as well, meaning I was shoveling fast carbs in while slogging through snow and over plowbergs trying to get to a place where I could sit down, dry off, and warm up before I passed out.

Someone asked me about taking the bus, and I had to explain that the bus stop was snowed in and all but inaccessible, and about half of the journey from my apartment to a bus line would have had to been walked on the same route I took to work anyway, and the transfer/wait would’ve made the journey take twice as long.

I’m drafting an email to the mayor, my alderman, the city streets department, and the city’s ADA coordinator to ask what their procedures are for meeting their obligations under the ADA and, if possible, what citations they’ve issued for uncleared walks and how they intend to enforce the mandate to clear public walkways so that pedestrians, transit riders, and the disabled have just as much access to the city as abled people who drive personal vehicles. But when I started writing it, I got agitated and felt myself losing my temper (I was still glycemically volatile at the time), so I’ve put it on pause until I’ve had a little distance. Hopefully, tomorrow’s commute will be easier and I’ll be less irritated and able to compose something professional.

#accessibility #disability

In February 2025, Andrej Karpathy, the former AI director at Tesla and founding engineer at OpenAI, posted something to X that would reshape how we talk about software development. “There's a new kind of coding I call 'vibe coding',” he wrote, “where you fully give in to the vibes, embrace exponentials, and forget that the code even exists.” He described using voice transcription to talk to AI assistants, clicking “Accept All” without reading the diffs, and copy-pasting error messages with no comment. When bugs proved stubborn, he would “just work around it or ask for random changes until it goes away.”

Within months, this approach had transformed from a personal workflow confession into a movement. By November 2025, Collins Dictionary had named “vibe coding” its Word of the Year, defining it as “using natural language prompts to have AI assist with the writing of computer code.” The lexicographers at Collins noted a large uptick in usage since the term first appeared, with managing director Alex Beecroft declaring it “perfectly captures how language is evolving alongside technology.”

The numbers behind this shift are staggering. According to Y Combinator managing partner Jared Friedman, a quarter of startups in the Winter 2025 batch had codebases that were 95% AI-generated. Google CEO Sundar Pichai revealed that more than 25% of all new code at Google was being generated by AI, then reviewed and accepted by engineers. Industry estimates suggest that 41% of all code written in 2025 was AI-generated, with data from Jellyfish indicating that almost half of companies now have at least 50% AI-generated code, compared to just 20% at the start of the year.

But beneath these impressive statistics lies a growing unease. What happens when the developers who built these systems cannot explain how they work, because they never truly understood them in the first place? What becomes of software maintainability when the dominant development methodology actively discourages understanding? And as AI-assisted developers increasingly outnumber traditionally trained engineers, who will possess the architectural discipline to recognise when something has gone terribly wrong?

The Maintainability Crisis Takes Shape

The first concrete evidence that vibe coding carries hidden costs arrived in May 2025, when security researcher Matt Palmer discovered a critical vulnerability in Lovable, one of the most prominent vibe coding platforms. The vulnerability, catalogued as CVE-2025-48757 with a CVSS score of 8.26 (High severity), stemmed from misconfigured Row Level Security policies in applications created through the platform.

Palmer's scan of 1,645 Lovable-created web applications revealed that 170 of them allowed anyone to access information about users, including names, email addresses, financial information, and secret API keys for AI services. The vulnerability touched 303 endpoints, allowing unauthenticated attackers to read and write to databases of Lovable apps. In the real world, this meant sensitive data (names, emails, API keys, financial records, even personal debt amounts) was exposed to anyone who knew where to look.

The disclosure timeline proved equally troubling. Palmer emailed Lovable CEO Anton Osika with detailed vulnerability reports on 21 March 2025. Lovable confirmed receipt on 24 March but provided no substantive response. On 24 April, Lovable released “Lovable 2.0” with a new “security scan” feature. The scanner only flagged the presence of Row Level Security policies, not whether they actually worked. It failed to detect misconfigured policies, creating a false sense of security.

The Lovable incident illuminates a fundamental problem: AI models generating code cannot yet see the big picture and scrutinise how that code will ultimately be used. Users of vibe coding platforms might not even know the right security questions to ask. The democratisation of software development had created a new class of developer who could build applications without understanding security fundamentals.

The Productivity Paradox Revealed

The promise of vibe coding rests on a seductive premise: by offloading the mechanical work of writing code to AI, developers can move faster and accomplish more. But a rigorous study published by METR (Model Evaluation and Threat Research) in July 2025 challenged this assumption in unexpected ways.

The study examined how AI tools at the February to June 2025 frontier affected productivity. Sixteen developers with moderate AI experience completed 246 tasks in mature projects where they had an average of five years of prior experience and 1,500 commits. The developers primarily used Cursor Pro with Claude 3.5/3.7 Sonnet, which were frontier models at the time of the study.

The results confounded expectations. Before starting tasks, developers forecast that allowing AI would reduce completion time by 24%. After completing the study, developers estimated that AI had reduced completion time by 20%. The actual measured result: allowing AI increased completion time by 19%. AI tooling had slowed developers down.

This gap between perception and reality is striking. Developers expected AI to speed them up, and even after experiencing the slowdown, they still believed AI had sped them up. The METR researchers identified several factors contributing to the slowdown: developers accepted less than 44% of AI generations, spending considerable time reviewing, testing, and modifying code only to reject it in the end. AI tools introduced “extra cognitive load and context-switching” that disrupted productivity. The researchers also noted that developers worked on mature codebases averaging 10 years old with over 1 million lines of code, environments where AI tools may be less effective than in greenfield projects.

The METR findings align with data from DX's Q4 2025 report, which found that developers saved 3.6 hours weekly among a sample of 135,000+ developers. But these savings came with significant caveats: the report revealed that context pain increases with experience, from 41% among junior developers to 52% among seniors. While some developers report productivity gains, the hard evidence remains mixed.

Trust Erodes Even as Adoption Accelerates

The productivity paradox reflects a broader pattern emerging across the industry: developers are adopting AI tools at accelerating rates while trusting them less. The Stack Overflow 2025 Developer Survey, which received over 49,000 responses from 177 countries, reveals this contradiction in stark terms.

While 84% of developers now use or plan to use AI tools in their development process (up from 76% in 2024), trust has declined sharply. Only 33% of developers trust the accuracy of AI tools, down from 43% in 2024, while 46% actively distrust it. A mere 3% report “highly trusting” the output. Positive sentiment for AI tools dropped from over 70% in 2023 and 2024 to just 60% in 2025.

Experienced developers are the most cautious, with the lowest “highly trust” rate (2.6%) and the highest “highly distrust” rate (20%), indicating a widespread need for human verification for those in roles with accountability.

The biggest frustration, cited by 66% of developers, is dealing with “AI solutions that are almost right, but not quite.” This leads directly to the second-biggest frustration: “Debugging AI-generated code is more time-consuming,” reported by 45% of respondents. An overwhelming 75% said they would still ask another person for help when they do not trust AI's answers. About 35% of developers report that their visits to Stack Overflow are a result of AI-related issues at least some of the time.

Perhaps most telling for the enterprise adoption question: developers show the strongest resistance to using AI for high-responsibility, systemic tasks like deployment and monitoring (76% do not plan to use AI for this) and project planning (69% do not plan to). AI agents are not yet mainstream, with 52% of developers either not using agents or sticking to simpler AI tools, and 38% having no plans to adopt them.

Google's 2024 DORA (DevOps Research and Assessment) report found a troubling trade-off: while a 25% increase in AI usage quickened code reviews and benefited documentation, it resulted in a 7.2% decrease in delivery stability. The 2025 DORA report confirmed that AI adoption continues to have a negative relationship with software delivery stability, noting that “AI acts as an amplifier, increasing the strength of high-performing organisations but worsening the dysfunction of those that struggle.”

Technical Debt Accumulates at Unprecedented Scale

These trust issues and productivity paradoxes might be dismissed as growing pains if the code being produced were fundamentally sound. But the consequences of rapid AI-generated code deployment are becoming measurable, and the data points toward a structural problem.

GitClear's 2025 research, analysing 211 million changed lines of code from repositories owned by Google, Microsoft, Meta, and enterprise corporations, found emerging trends showing four times more code cloning, with “copy/paste” exceeding “moved” code for the first time in history.

During 2024, GitClear tracked an eightfold increase in the frequency of code blocks with five or more lines that duplicate adjacent code, showing a prevalence of code duplication ten times higher than two years ago. Lines classified as “copy/pasted” (cloned) rose from 8.3% to 12.3% between 2021 and 2024. The percentage of changed code lines associated with refactoring sank from 25% of changed lines in 2021 to less than 10% in 2024, with predictions for 2025 suggesting refactoring will represent little more than 3% of code changes.

“What we're seeing is that AI code assistants excel at adding code quickly, but they can cause 'AI-induced tech debt,'” explained GitClear founder Bill Harding. “This presents a significant challenge for DevOps teams that prioritise maintainability and long-term code health.”

A report from Ox Security found that AI-generated code is “highly functional but systematically lacking in architectural judgment.” This aligns with observations that code assistants make it easy to insert new blocks of code simply by pressing the tab key, but they are less likely to propose reusing a similar function elsewhere in the code, partly because of limited context size.

The financial implications are substantial. McKinsey research indicates that technical debt accounts for about 40% of IT balance sheets, with organisations carrying heavy technical debt losing up to 20% to 40% of their IT budgets to maintenance, leaving far less for genuine innovation. Companies pay an additional 10 to 20% to address tech debt on top of the costs of any project.

Armando Solar-Lezama, a professor at MIT specialising in program synthesis, offered a colourful assessment in remarks widely cited across the industry: AI represents a “brand new credit card here that is going to allow us to accumulate technical debt in ways we were never able to do before.”

When the Bill Comes Due

In September 2025, Fast Company reported that the “vibe coding hangover” was upon us. “Code created by AI coding agents can become development hell,” said Jack Zante Hays, a senior software engineer at PayPal who works on AI software development tools. He noted that while the tools can quickly spin up new features, they often generate technical debt, introducing bugs and maintenance burdens that must eventually be addressed by human developers.

The article documented a growing phenomenon: developers struggling to maintain systems that had been easy to create but proved difficult to extend. “Vibe coding (especially from non-experienced users who can only give the AI feature demands) can involve changing like 60 things at once, without testing, so 10 things can be broken at once.” Unlike a human engineer who methodically tests each addition, vibe-coded software often struggles to adapt once it is live, particularly when confronted with real-world edge cases.

By the fourth quarter of 2025, the industry began experiencing what experts call a structural reckoning. LinkedIn searches for “Vibe Coding Cleanup Specialist” reveal dozens of programmers advertising their services as digital janitors for the AI coding revolution. As one consultancy describes it: “Companies increasingly turn to such specialists to rescue projects where AI code is raw, without proper architecture and security. Those who made demos now call in seniors to make the code stable and secure.”

Y Combinator CEO Garry Tan raised this question directly: “Suppose a startup with 95% AI-generated code successfully goes public and has 100 million users a year or two later. Will it crash? Current reasoning models aren't strong enough for debugging. So founders must have a deep understanding of the product.”

The Disappearing Pipeline for Engineering Talent

The impact of vibe coding extends beyond code quality into workforce dynamics, threatening the very mechanisms by which engineering expertise has traditionally been developed. A Stanford University study titled “Canaries in the Coal Mine? Six Facts about the Recent Employment Effects of Artificial Intelligence,” authored by Erik Brynjolfsson, Bharat Chandar, and Ruyu Chen, examined anonymised monthly payroll data from ADP covering millions of workers across tens of thousands of US firms through July 2025.

The findings are stark: employment for software developers aged 22 to 25 declined by nearly 20% compared to its peak in late 2022. Workers aged 22 to 25 are the most exposed to artificial intelligence, suffering a decline in employment of 13%. Early career workers in the most AI-exposed occupations (like software engineering, marketing, and customer service) have experienced a 16% relative decline in employment, even after controlling for firm-level impacts.

Meanwhile, the employment rates of older workers in high AI-exposure fields are holding strong. For workers aged 30 and over, employment in the highest AI-exposure categories grew between 6% and 12% from late 2022 to May 2025. One interpretation offered by the researchers is that while younger employees contribute primarily “codified knowledge” from their education (something AI can replicate), more experienced workers lean on tacit knowledge developed through years on the job, which remains less vulnerable to automation.

A Harvard study on “Seniority-Biased Change” (2025), where two Harvard economists analysed 62 million LinkedIn profiles and 200 million job postings, found that in firms using generative AI, junior employment “declines sharply” relative to non-adopters. The loss was concentrated in occupations highly exposed to AI and was driven by slower hiring, not increased firing. The researchers interpret this as companies with AI largely skipping hiring new graduates for the tasks the AI handled.

The traditional pathway of “learn to code, get junior job, grow into senior” is wobbling. Year-over-year, internships across all industries have decreased 11%, according to Indeed. Handshake, an internship recruitment platform, reported a 30% decline in tech-specific internship postings since 2023. Per the Federal Reserve report on labour market outcomes, computer engineering graduates now have one of the highest rates of unemployment across majors, at 7.5% (higher even than fine arts degree holders).

The Expertise Atrophy Loop

The junior employment crisis connects directly to a deeper concern: fundamental skill atrophy. If developers stop writing code manually, will they lose the ability to understand and debug complex systems? And if the pipeline for developing new senior engineers dries up, who will maintain the increasingly complex systems that vibe coding creates?

Luciano Nooijen, an engineer at the video-game infrastructure developer Companion Group, used AI tools heavily in his day job. But when he began a side project without access to those tools, he found himself struggling with tasks that previously came naturally. “I was feeling so stupid because things that used to be instinct became manual, sometimes even cumbersome,” he told MIT Technology Review. Just as athletes still perform basic drills, he thinks the only way to maintain an instinct for coding is to regularly practice the grunt work.

Developer discourse in 2025 was split. Some admitted they hardly ever write code “by hand” and think coding interviews should evolve. Others argued that skipping fundamentals leads to more firefighting when AI's output breaks. The industry is starting to expect engineers to bring both: AI speed and foundational wisdom for quality.

Y Combinator partner Diana Hu pointed out that even with heavy AI reliance, developers still need a crucial skill: reading code and identifying errors. “You have to have taste, enough training to judge whether the LLM output is good or bad.”

This creates a troubling paradox. The pathway to developing “taste” (the intuition that distinguishes quality code from problematic code) has traditionally come through years of hands-on coding experience. If vibe coding removes that pathway, how will the next generation of developers develop the judgement necessary to evaluate AI-generated output?

Building Guardrails That Preserve the Learning Journey

The question of whether organisations should establish guardrails that preserve the learning journey and architectural discipline that traditional coding cultivates is no longer theoretical. By 2025, 87% of enterprises lacked comprehensive AI security frameworks, according to Gartner research. Governance frameworks matter more for AI code generation than traditional development tools because the technology introduces new categories of risk.

Several intervention strategies have emerged from organisations grappling with vibe coding's consequences.

Layered verification architectures represent one approach. Critical core components receive full human review, while peripheral functionality uses lighter-weight validation. AI can generate code in outer layers, subject to interface contracts defined by verified inner layers. Input access layers ensure only authorised users interact with the system and validate their prompts for malicious injection attempts. Output layers scan generated code for security vulnerabilities and non-compliance with organisational style through static analysis tools.

Contract-first development offers another model. Rather than generating code directly from natural language, developers first specify formal contracts (preconditions, postconditions, invariants) that capture intent. AI then generates implementation code that is automatically checked against these contracts. This approach draws on Bertrand Meyer's Design by Contract methodology from the 1980s, which prescribes that software designers should define formal, precise, and verifiable interface specifications for software components.

Operational safety boundaries prevent AI-generated code from reaching production without human review. All AI-generated changes go through established merge request and review processes. Admin controls block forbidden commands, and configurable human touchpoints exist within workflows based on customer impact.

The code review bottleneck presents its own challenges. As engineering teams discover, the sheer volume of code now being churned out is quickly saturating the ability of midlevel staff to review changes. Senior engineers, who have deeper mental models of their codebase, see the largest quality gains from AI (60%) but also report the lowest confidence in shipping AI-generated code (22%).

Economic Pressure Versus Architectural Discipline

The economic pressure toward speed is undeniable, and it creates structural incentives that directly conflict with maintainability. Y Combinator CEO Garry Tan told CNBC that the Winter 2025 batch of YC companies in aggregate grew 10% per week, and it was not just the top one or two companies but the whole batch. “That's never happened before in early-stage venture.”

“What that means for founders is that you don't need a team of 50 or 100 engineers. You don't have to raise as much. The capital goes much longer,” Tan explained. About 80% of the YC companies that presented at Demo Day were AI-focused, with this group able to prove earlier commercial validation compared to previous generations.

But this very efficiency creates structural incentives that work against long-term sustainability. Forrester predicts that by 2025, more than 50% of technology decision-makers will face moderate to severe technical debt, with that number expected to hit 75% by 2026. Industry analysts predict that by 2027, 75% of organisations will face systemic failures due to unmanaged technical debt.

The State of Software Delivery 2025 report by software vendor Harness found that, contrary to perceived productivity benefits, the majority of developers spend more time debugging AI-generated code and more time resolving security vulnerabilities. If the current trend in code churn continues (now at 7.9% of all newly added code revised within two weeks, compared to just 5.5% in 2020), GitClear predicts defect remediation may become the leading day-to-day developer responsibility.

The software craftsmanship manifesto, established in 2008 by developers meeting in Libertyville, Illinois, articulated values that seem increasingly relevant: not only working software, but also well-crafted software; not only responding to change, but also steadily adding value; not only individuals and interactions, but also a community of professionals.

As Tabnine's analysis observed: “Vibe coding is what happens when AI is applied indiscriminately, without structure, standards, or alignment to engineering principles. Developers lean on generative tools to create code that 'just works.' It might compile. It might even pass a test. But in enterprise environments, where quality and compliance are non-negotiable, this kind of code is a liability, not a lift.”

Structural Interventions That Could Realign Development Practice

What structural or cultural interventions could realign development practices toward meaningful problem-solving over rapid code generation? Several approaches warrant consideration.

First, educational reform must address the skills mismatch. The five core skills shaping engineering in 2026 include context engineering, retrieval-augmented generation, AI agents, AI evaluation, and AI deployment and scaling. By 2026, the most valuable engineers are no longer those who write the best prompts but those who understand how to build systems around models. Junior developers are advised to use AI as a learning tool, not a crutch: review why suggested code works and identify weaknesses, occasionally disable AI helpers and write key algorithms from scratch, prioritise computer science fundamentals, implement projects twice (once with AI, once without), and train in rigorous testing.

Second, organisations need governance frameworks that treat AI-generated code differently from human-written code. Rather than accepting it as a black box, organisations should require that AI-generated code be accompanied by formal specifications, proofs of key properties, and comprehensive documentation that explains not just what the code does but why it does it. The DORA AI Capabilities Model identifies seven technical and cultural best practices for AI adoption: clear communication of AI usage policies, high-quality internal data, AI access to that data, strong version control, small batches of work, user-centric focus, and a high-quality internal platform.

Third, the code review process must evolve. AI reviewers are emerging as a solution to bridge the gap between code generation speed and review capacity. Instead of waiting hours or days for a busy senior developer to give feedback, an AI reviewer can respond within minutes. The answer emerging from practice involves treating AI reviewers as a first-pass filter that catches obvious issues while preserving human review for architectural decisions and security considerations.

Fourth, organisations must invest in maintaining architectural expertise. Successful companies allocate 15% to 20% of budget and sprint capacity systematically to debt reduction, treating it as a “lifestyle change” rather than a one-time project. McKinsey noted that “some companies find that actively managing their tech debt frees up engineers to spend up to 50 percent more of their time on work that supports business goals.”

The Cultural Dimension of Software Quality

Beyond structural interventions, the question is fundamentally cultural. Will the industry value the craftsmanship that comes from understanding systems deeply, or will economic pressure normalise technical debt accumulation at scale?

The signals are mixed. On one hand, the vibe coding hangover suggests market correction is already occurring. Companies that moved fast and broke things are now paying for expertise to fix what they broke. The emergence of “vibe coding cleanup specialists” represents market recognition that speed without sustainability is ultimately expensive.

On the other hand, the competitive dynamics favour speed. When Y Combinator startups grow 10% per week using 95% AI-generated code, the pressure on competitors to match that velocity is intense. The short-term rewards for vibe coding are visible and immediate; the long-term costs are diffuse and deferred.

The craftsmanship movement offers a counternarrative. Zed's blog captured this perspective: “Most people are talking about how AI can help us make software faster and help us make more software. As craftspeople, we should look at AI and ask, 'How can this help me build better software?'” A gnarly codebase hinders not only human ability to work in it but also the ability of AI tools to be effective in it.

Perhaps the most significant intervention would be changing how we measure success. Currently, the industry celebrates velocity: lines of code generated, features shipped, time to market. What if we equally celebrated sustainability: code that remains maintainable over time, systems that adapt gracefully to changing requirements, architectures that future developers can understand and extend?

Where the Reckoning Leads

The proliferation of vibe coding as a dominant development methodology threatens long-term software maintainability in ways that are now empirically documented. Code duplication is up fourfold. Refactoring has collapsed from 25% to potentially 3% of changes. Delivery stability decreases as AI adoption increases. Junior developer employment has fallen by 20% while the pathway to developing senior expertise narrows.

The question of whether organisations should establish guardrails is no longer open. The evidence indicates they must, or face the consequences documented in security incidents, technical debt accumulation, and the structural erosion of engineering expertise.

Whether economic pressure toward speed will inevitably normalise technical debt at scale depends on choices yet to be made. Markets can correct when costs become visible, and the vibe coding hangover suggests that correction has begun. But markets also systematically underweight future costs relative to present benefits, and the current incentive structures favour speed over sustainability.

The interventions that could realign development practices toward meaningful problem-solving are known: layered verification architectures, contract-first development, operational safety boundaries, educational reform emphasising fundamentals alongside AI fluency, governance frameworks that require documentation and review of AI-generated code, investment in architectural expertise, and cultural shifts that value sustainability alongside velocity.

The path forward requires preserving what traditional coding cultivates (the learning journey, the architectural discipline, the deep understanding of systems) while embracing the productivity gains that AI assistance offers. This is not a binary choice between vibe coding and craftsmanship. It is the harder work of integration: using AI to augment human expertise rather than replace it, maintaining the feedback loops that develop judgement, and building organisations that value both speed and sustainability.

The stakes extend beyond any individual codebase. As software mediates an ever-larger share of human activity, the quality of that software matters profoundly. Systems that cannot be maintained will eventually fail. Systems that no one understands will fail in ways no one can predict. The reckoning that began in 2025 is just the beginning of a longer conversation about what we want from the software that shapes our world.

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References and Sources

1. Karpathy, A. (2025, February 2). Twitter/X post introducing vibe coding. https://x.com/karpathy/status/1886192184808149383

2. Collins Dictionary. (2025). Collins Word of the Year 2025: Vibe Coding. https://www.collinsdictionary.com/us/woty

3. CNN. (2025, November 6). 'Vibe coding' named Collins Dictionary's Word of the Year. https://www.cnn.com/2025/11/06/tech/vibe-coding-collins-word-year-scli-intl

4. TechCrunch. (2025, March 6). A quarter of startups in YC's current cohort have codebases that are almost entirely AI-generated. https://techcrunch.com/2025/03/06/a-quarter-of-startups-in-ycs-current-cohort-have-codebases-that-are-almost-entirely-ai-generated/

5. CNBC. (2025, March 15). Y Combinator startups are fastest growing, most profitable in fund history because of AI. https://www.cnbc.com/2025/03/15/y-combinator-startups-are-fastest-growing-in-fund-history-because-of-ai.html

6. METR. (2025, July 10). Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity. https://metr.org/blog/2025-07-10-early-2025-ai-experienced-os-dev-study/

7. Stack Overflow. (2025). 2025 Stack Overflow Developer Survey. https://survey.stackoverflow.co/2025/

8. Stack Overflow Blog. (2025, December 29). Developers remain willing but reluctant to use AI: The 2025 Developer Survey results are here. https://stackoverflow.blog/2025/12/29/developers-remain-willing-but-reluctant-to-use-ai-the-2025-developer-survey-results-are-here

9. Palmer, M. (2025). Statement on CVE-2025-48757. https://mattpalmer.io/posts/statement-on-CVE-2025-48757/

10. Security Online. (2025). CVE-2025-48757: Lovable's Row-Level Security Breakdown Exposes Sensitive Data Across Hundreds of Projects. https://securityonline.info/cve-2025-48757-lovables-row-level-security-breakdown-exposes-sensitive-data-across-hundreds-of-projects/

11. GitClear. (2025). AI Copilot Code Quality: 2025 Data Suggests 4x Growth in Code Clones. https://www.gitclear.com/ai_assistant_code_quality_2025_research

12. Google Cloud Blog. (2024). Announcing the 2024 DORA report. https://cloud.google.com/blog/products/devops-sre/announcing-the-2024-dora-report

13. Google Cloud Blog. (2025). Announcing the 2025 DORA Report. https://cloud.google.com/blog/products/ai-machine-learning/announcing-the-2025-dora-report

14. McKinsey. (2024). Tech debt: Reclaiming tech equity. https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/tech-debt-reclaiming-tech-equity

15. Fast Company. (2025, September). The vibe coding hangover is upon us. https://www.fastcompany.com/91398622/the-vibe-coding-hangover-is-upon-us

16. Final Round AI. (2025). Young Software Developers Losing Jobs to AI, Stanford Study Confirms. https://www.finalroundai.com/blog/stanford-study-shows-young-software-developers-losing-jobs-to-ai

17. Stack Overflow Blog. (2025, December 26). AI vs Gen Z: How AI has changed the career pathway for junior developers. https://stackoverflow.blog/2025/12/26/ai-vs-gen-z/

18. MIT Technology Review. (2025, December 15). AI coding is now everywhere. But not everyone is convinced. https://www.technologyreview.com/2025/12/15/1128352/rise-of-ai-coding-developers-2026/

19. InfoQ. (2025, November). AI-Generated Code Creates New Wave of Technical Debt, Report Finds. https://www.infoq.com/news/2025/11/ai-code-technical-debt/

20. The New Stack. (2025). Is AI Creating a New Code Review Bottleneck for Senior Engineers? https://thenewstack.io/is-ai-creating-a-new-code-review-bottleneck-for-senior-engineers/

21. Tabnine Blog. (2025). A Return to Craftsmanship in Software Engineering. https://www.tabnine.com/blog/a-return-to-craftsmanship-in-the-age-of-ai-for-software-engineering/

22. Zed Blog. (2025). The Case for Software Craftsmanship in the Era of Vibes. https://zed.dev/blog/software-craftsmanship-in-the-era-of-vibes

23. Manifesto for Software Craftsmanship. (2009). https://manifesto.softwarecraftsmanship.org/

24. DX. (2025). AI-assisted engineering: Q4 impact report. https://getdx.com/blog/ai-assisted-engineering-q4-impact-report-2025/

25. Jellyfish. (2025). 2025 AI Metrics in Review: What 12 Months of Data Tell Us About Adoption and Impact. https://jellyfish.co/blog/2025-ai-metrics-in-review/

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Tim Green UK-based Systems Theorist & Independent Technology Writer

Tim explores the intersections of artificial intelligence, decentralised cognition, and posthuman ethics. His work, published at smarterarticles.co.uk, challenges dominant narratives of technological progress while proposing interdisciplinary frameworks for collective intelligence and digital stewardship.

His writing has been featured on Ground News and shared by independent researchers across both academic and technological communities.

ORCID: 0009-0002-0156-9795 Email: tim@smarterarticles.co.uk

In Summary: * My radio is now tuned to The Flagship Station for IU Sports and I'm listening to the extensive pregame coverage ahead of tonight's men's college basketball game between the Indiana Hoosiers and the Purdue Boilermakers. Opening Tip is still an hour away, but I'm ready to hear the call of this game.

Prayers, etc.: *I have a daily prayer regimen I try to follow throughout the day from early morning, as soon as I roll out of bed, until head hits pillow at night. Details of that regimen are linked to my link tree, which is linked to my profile page here.

Health Metrics: * bw= 223.55 lbs. * bp= 145/87 (68)

Exercise: * morning stretches, balance exercises, kegel pelvic floor exercises, half squats, calf raises, wall push-ups

Diet: * 06:15 – 1 banana, 1 tangerine * 09:00 – snacking on cookies * 10:00 – 1 cheese sandwich * 13:20 – big plate of pancit * 15:10 – 1 fresh apple * 16:40 – snacking on saltine crackers

Activities, Chores, etc.: * 03:00 – listen to local news talk radio * 05:15 – bank accounts activity monitored * 06:10 – read, pray, follow news reports from various sources, surf the socials * 12:55 – start my weekly laundry * 15:00 – listening to the The Jack Riccardi Show * 15:50 – following news reports from various sources, surfing the socials, then settling on relaxing music and prayers

Chess: * 12:45 – moved in all pending CC games

For my birthday, I sprung for a slipstrop and a few flexcut carving tools. While the tools haven’t arrived yet, I spent an inordinate amount of time stropping the tools I do have yesterday, and friends, let me tell you: sharp tools make battleship gray lino feel like the soft cut stuff.

I was just amazed at the difference. I started with a speedball-knock-off tool with changeable blades, and picked up a package of Temu woodblock carving tools (with real wooden handles!). I currently own on flexcarve palm tool – a very small V-cut that I use for outlining and fine details – and thought that the flexcarve was the biggest upgrade I could make.

After stropping, even the temu tools are feeling good.

So, I felt the need to “doodle” in lino – there was no major plan for this, and it’s just a scrap from a larger piece, but it cut SOOOO nice.

I have some water-based black to proof with, so of course, here’s a print:

Having sharp tools means my control is so much better – not having to use force, but just allowing the blade to cut, guiding it across the material – it’s amazing.

I suspect there will be more doodles in the future, because doing the small things are just fun!

S.N.I.t ; VVA Human Interest

De Mensen van de KNMI gevoelstemperatuur metingen

Hai, inderdaad ja. Mijn naam is Richard Kleiderman. Ik ben al vijf jaar actief bij het KNMI, als expert werkzaam in het weer en gevoel lab. Deelnemer temperatuur ervaring, ik ben één van een select gezelschap, 12 medewerkers, inclusief chauffeur, temperatuur voelers, wij worden alle dagen binnen bewaard behalve als de het instituut ons nodig heeft. Wij worden dan in een geblindeerd merkloze zwarte wagen naar diverse meet locaties gebracht, daar moeten we uit de auto met alleen een speedo badpak of zwembroek aan en terug in de wagen, vervolgens zeggen we op de graad nauwkeurig hoe koud of heet het voelt, en allemaal zonder te weten hoe het echt is. Puur op voel talent, hoog ontwikkelde waarnemings genen zitten er in ons. De KNMI heeft ons er op geselecteerd. Jaren door geselecteerd, zware studies moesten we volgen, fysiek overleven terwijl overal om ons heen de temperatuur er was, die dan steeg of daalde, en dan werden we keer op keer getest. Zwaar werk, zeker de opleiding. Het was het waard, zonder meer. De Koninklijke kan niet zonder ons functioneren. Het vaderland en zijn onverveerde volk heeft ons nodig, ze moeten voor ze zomaar naar buiten gaan weten wat ze daar gevoelsmatig staat te wachten. De gewone recht toe recht aan meters zijn niet langer goed genoeg, het kwik liegt u min of meer voor, het is eigenlijk altijd kouder dan het werkelijk is.

Uhuh, uhuh. Binnenkort, binnenkort ja, dan gaan we samen met buienradar en weeronline iets nieuws beginnen, nu gebleken is dat de meet apparatuur keer op keer tekort schiet bij eigenlijk alles gaan we onze voel sprieten ook richten op gevoels windkracht en richting, als er windkracht 4 staat, uit het Oosten, dan zegt ons gevoel dat het meer lijkt op een West 6, gevoels regenstand, heel vaak hoor je 6 mm op een dag, maar als je buiten staat, leunt op een schoffel, loopt of fietst, voelt het als 4 of 0 of wel 9 mm. We willen ook nog zoiets ontwikkelen voor de zonkracht maar dat zit voorlopig alleen in het vat dat heeft meer voeten in aarde vanwege de gevaren die zonlicht kracht voelen op de onbedekte blote huid met zich meebrengt.

We hebben met een ander team nog iets gedaan betreffende de extra's, van die dingen als goed barbecue weer, tuinweer, we vonden, met name de mensen van de weer instituten die hun geld uit dit bronmateriaal moeten ronselen, het aanbod daarin mager, zeg maar schraal. De uitbreiding bevat onder andere goed paintball weer, lekker ijsvis weer, perfect weer voor fierljeppen, goed voor kievitei rapers, fijn mest of maai weer (ook voor privé veldjes, op zaterdag) veel ruimere keuze zodat meer mensen kunnen weten wat ze moeten doen als er buiten weer is. Bedankt fijn dat u wel belangstelling toont voor ons, de drijvende krachten achter de Koninklijke, zonder ons zou iedereen maar raak voelen, die onwetenden, amateurs!

Gentle words

Understand that it is ok to comfort yourself The small sounds of the tv playing the voices of friends you have come to know well is not a wrong thing to listen to. It is ok to sit on a soft surface Sometimes you need to take on the posture of a slightly crumpled infant, held up in a sitting position to look with large black eyes at the world. This is often better than a futuristic chair even with all its knobs. It's ok to soothe yourself with the feel of soft blankets and almost painful bathwater that makes you sweat through your hair. Yes, it's ok to light candles. Tiny fires in big darks, small warm tongues that murmur gentle words just out of hearing. Why do we deny ourselves these small, soothing pleasures. We would not deny a baby though their needs are the same as ours. Jobs, age and time in this weird world do not change that. My thin veins have thrummed with Puritanical blood. I have associated soothing with sin though my body and spirit are in want of such tender care. Do it! I will, now. Ah, the beads of sweat begin to form.

ipnotico:

https://youtu.be/EuEfhz0OCwA?si=CeCjEfFo5uP79Vhe