Home is where you find it—and yourself.

When I flew from at the start of December last year (2025), I expected a respite. A break. A sabbatical. To return to it recovered and refreshed—a slightly different man, perhaps—but one back at home in any case, ready to take over the world.

Or at least content to continue existing in it. I realized in leaving that... I had already left emotionally many months earlier.

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Home… where a man hangs his hat. Where the heart is. Everyone calls someplace home. Even when we no longer have an address, we have something—some place—we know as home.

A place we are from, if nothing else.

I've been on the road for months. Four, to be precise. I set foot, in whole or part, in ten countries—living for a time in eight: Portugal, Spain, France, Italy, Switzerland, Liechtenstein, Germany, and Ireland—before landing back stateside in Florida.

Talk was always about “when we get back home” and “since we left home.” In time, homesickness set in for my wife.

But for me, it never came calling.

For weeks, home was just a shorthand word for comfort and routine. Knowing where my toothbrush was kept. How far it was to the grocery store. Hell—where the grocery store even was. It meant something familiar was left behind.

But it also meant leaving something else behind—something heavier.

A feeling of emptiness. Frustration. Aggravation. Sitting 5,000 miles away alongside friends and family.

Home wasn’t just convenience.

It was negativity. It was frustration. It was a place from which to escape.

And at first, that’s exactly what this exodus was—an escape from the ordinary into the extraordinary. Everything was new. Exciting. Overwhelming.

But by week five, settled into a rhythm in Spain, I realized something unsettling:

the old demons hadn’t been left behind on some dusty shelf.

They had come with me.

Tucked neatly into the shadowed places of my heart and mind.

Family and friends... the familiar... were behind me, yes—but not gone. Through messages, calls, and photos, I found that those I loved most were still with me on the journey.

And stranger still—the new faces I met didn’t replace the old ones.

My heart grew, and my life to include them... My home grew bigger still.

---

And as old routines dissolved and new ones took shape—figuring out transit, where to shop, how to live—I began to understand something I hadn’t before:

Home isn’t where I am.

It is intangible and carried:

In my mind and heart.

This was something new. Something else.

Especially for her.

I live a reality of expectations and obligations—but my heart and mind move in another realm. One that is loyal. Passionate. Entirely hers.

Even thousands of miles away, my wanting is with her.

My thoughts—every day.

I wake and sleep with her as the first and final presence in my mind.

So when a stranger asks, “Where are you from?”

I give them a myth... something to chew on and relish in. More description of past than present.

Or future.

It is answering a deeper question:

Where does the soul return to, when there is nowhere left to go?

And for me—

home is no longer a place on a map.

It is a convergence.

Of memory. Of longing. Of love.

Of that which I carry, and refuse to let go.

Home, is hope.

---

#poetry #wyst

Cuenta una leyenda que en un pequeño pueblo del sur de China aparecieron unos monos que aseguraban ser dueños del árbol que concede todos los deseos. Se llamaban Uno, Dos y Tres.

A tal efecto exhibieron documentos con grandes sellos rojos que -según ellos- habían sido expedidos por la secretaría del mismísimo emperador.

Un sabio taoísta se acercó para ver bien a los monos y la gente lo fue empujando para que se fuera.

-¿Por qué te empujan? -le preguntó una anciana.

-Para que no les agüe la fiesta.

La anciana, confundida, le volvió a preguntar:

-¿Pero no ven que los van a engañar?

A lo que el sabio concluyó:

-Sí, pero eso será mañana. ¡Hoy creen que van a engañar a los monos!

There's something weird about LLMs that creates dissonance in me. It likely has something to do with the difference between all the hype that's being drummed up and the actual product on our hands, even though I understand that the hype also exists for reasons that are insincere. Still, as tech fads go, this beats the metaverse and NFTs by miles: we actually have a product in our hands that the masses are actually using, even if it doesn't quite live up to the tall tales going around. It definitely merits from me to want to figure out what's going on with it, what its limitations are, and if something can be done to go past them.

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Let’s start with the base tool, upon which all the rest of modern AI is built: the raw, unrefined, unassisted Large Language Model.

Its limitations are fairly obvious:

• It makes shit up: It makes shit up in a way that's fundamental to its constitution, since what it is constructed to do is imitate human writing, which is itself largely neutral to truth and does not intrinsically contain self-correction mechanisms in that sense. In part, this results from the innate versatility of the language, that allows many things to be said regardless if they're true or not (a principle upon the very concept of fiction rests), which leaves mere statistical frequency to distinguish “3 plus 4 is 9” from “3 plus 4 is 7” as one being truer than the other, by virtue of the mathematically correct statements being repeated more often. The LLM doesn't encode a proper math engine in its inference layers (which for a computer is most ironic), which means that, like with most other topics, its deliberations are generally only true by mere statistical approximation.

• It is beholden to the premise: given that a fundamental quality of (passable) human-made text is coherence, both syntactic, semantic, and thematic, this generally rubs off on an LLM, which (before post-training) will generally go along with whatever premise given, keeping up with its thrust and its tone, by virtue of being trained to generate output that is coherent with the input. This is the base appeal of an LLM (that it is able to elaborate on any given premise) but it also makes it extremely prone to syncopancy, by design enabling even the most deranged flights of fancy and, in some cases, conducting a “technological folie à deux” devolving into cases of AI psychosis.

• It doesn't know when to stop: the single output mode that an LLM has is to generate the next token in a linear sequence. Taken as a parallel with someone talking (a pareidolia that most, if not every AI company has been very eager to exploit), it's like a conversationalist that simply does not know when (or how!) to stop talking in order to actually think some things through. Its single process is to keep talking, even when it runs into serious informational snags (like self-contradiction, or being stuck in circles repeating the same things over and over) simply because that's all the machine is designed to output, one word after another by mere statistical inertia.

Think of it like this: when asked to complete “8 times 12 is:”, a person would generally parse the phrase, stop and switch mental processes in order to make a mental calculation, and only upon completing it, they would write down “96.” If they didn't feel in the mood or otherwise felt particularly sure of themselves, they could go by sheer memory and say whatever number felt most likely in the moment, which is the closest parallel to what an LLM does with every generated token.

An LLM does not innately possess such a context-switch procedure: neither the means by which to realize it is needed, nor the tools to operate once this realization happens. As we do something, there’s checks running through our head that make us go “this is something I should calculate” or “this is something I should gather data for” or “oh I should check if this is true” or “this is an important step, is this actually in line with what i was supposed to be doing?”.

No such tripwires are in place for an LLM’s stream-of-consciousness output. After the input is given, it’s off to the races and barely anything that can be said to be a novel decision is made after that. This is the reason why an LLM is said to be unable to make art – it doesn’t go through the process of figuring things out, and in not doing so it doesn’t make the decisions that impregnate a piece of art with personal meaning.

---

Of course, by now the AI what we work with is not just a mere raw LLM, but refined post-trained models, usually primed to generate a preliminary “thinking mode” (spending tokens on summarizing and evaluating the situation before outputting user-directed tokens), accompanied by tailored prompt add-ons (such as web searches to plump the input context with updated data), a variety of tools that the LLM can access and is trained to use (like operating your calendar, your mailbox, your console), as well as structured environments where the LLM has access to automatic feedback (like a compiler output) that the model can iterate upon (the so-called agentic loops).

To be straight, this is the industry moving in the right direction. We want AI to make decisions, and to do so properly these decisions have to be frequent and based in actual searches, reasoning and/or calculations. For example, when you look at eg. the recognized best coding practices (such as version control, comprehensive test suites, continuous integration, meaningful documentation, fast feedback cycles, iterative development, focus on users, small batches of work), one of their main thrust is to both provide quick, cogent feedback and empower rapid iteration based on said feedback, so that the steering and decision-making can be more fine-grained, and thus generally easier to execute and more effective in the overall. This is a project structure that benefits both humans and LLMs, with the likes of compiler output providing the course correction that a LLM sorely needs to direct itself. These approaches are working; they are providing real results as they shore up the weaknesses of the raw unrefined LLM.

However, we are still in the infancy of agents and the methods we use are still crude. The current supports to the LLM’s functioning are either post-training reinforcement learning to alter its general functioning, specific prompts, or ad-hoc tools with text-based invocations. We have access to Claude Code’s source and we know nothing fancier than this is being done under the hood; this is as far as the state of the art goes. All of these extra functionalities keep relying on the LLM’s text generation as the fundamental mode of operation, which remains prone to both hallucination and missing the point even as it appears to go in the right direction. They are rigid fixes to constrain and direct behaviour, but in their rigidness they are both wasteful and brittle. Modern AI still has a substantial failure rate for complex tasks, and this shows none better than the slew of new bugs and uptime crises that has plagued the companies that have forcefully imposed AI adoption in their internal coding practices (like Microsoft, or Amazon)

Even as we are reaching into capabilities that seem to genuinely surpass human feats (such as Claude Mythos being able to find decades-old exploits in our most used and supervised code), we are running against the limitations of the method, and we cannot hope much longer to improve the LLM’s approximations by just training it more. The gains we’re getting in the last years have been not just more fragile but increasingly expensive, if not outright wasteful, on both the training side and the inference side. OpenAI has declared that it intends to spend 120 billions of dollars in model training alone in the next two years, which is a genuinely mind-boggling amount.

On the user side, token burn has increased in recent years by orders of magnitude (far outstripping the efficiency gains of newer models), and all this compute is starting to run against the physical and economical limits of the industry. A paradigm shift is increasingly necessary to sustain hopes of the technology continuing to increase in capabilities. So what can be done about this? Where can a fault be located, and what can be done about it?

---

What we have now is a model that is trained specifically on human text, which (both discursive text and programming code) is the result of thinking instead of the process. The text does not contain the thinking process that resulted in the text, much like a house does not contain cranes or scaffolding or cement mixer trucks. An LLM by default will brazenly trudge forward because it is drawing reference from a corpus that does the same; text is generally done in order to expose a singular point, in one continued stream, without all the searching, thinking, trying and wandering that got someone there, and if some of that text follows that pattern it is a vanishing amount.

To truly teach an LLM to think, it would have to

• structure its output so that it delegates very frequently to other tools (including web search, math operations, and various other checks) in order to maintain closeness to truth/task.

• This would most likely need some sort of backtracking/future-seeing modality where the model is able to reason and second-guess what it is going to say X tokens in the future and trigger second-guessing mechanisms on those

• To implement those triggers reasonably, the procedure to check for (effectively) alignment on the to-be-generated output has to be both fairly snappy and only occasionally activated; thankfully we do have inspiration to draw from the way that our neurons work.

Neurons are semi-anarchically organized into collectives that fulfill different mental functions, and they get fed depending if they get to operate or not, so the neurons are constantly on the lookout to take work from one another once the right occasion comes, and for example this can work by way of threshold activation, where a neuron activates only after a weighted sum of the stimuli it receives passes a certain threshold.

And an LLM is already a neural network of a kind, operating by similar algorithms, so there’s definitely potential there. However, to realize this potential, the LLM would have to be used in ways that go beyond mere next-token generation, and instead the model would have to be harnessed in new, slightly different ways. It is my belief that an LLM is (partly) wasted on mere next-token prediction, when the underlying model that allows for that contains effectively a vector field of human meaning, albeit filtered through words.

If there’s anything that LLMs have shown us in recent years, is that words (as well as other input methods like images) encode a whole lot of meaning that can be captured by a model. From here, there reasonably should be other ways to harness this organized meaning-space other than just checking how a phrase continues. What if we manage to locate the point in vector space that approximates some concept of ours and decide to check text against it to see if it passes a threshold or not (which is likely similar to what we do when we monitor the tone of a piece of text)? It feels to me like a lot of the hard work has already been done, namely crafting such a vector space. The LLM science is young and far from everything has been tried; I think something of worth may be found in that direction. The paredolic thrust of treating an LLM as mere text generator can only carry us so far, and I believe a lot of progress could be done once we figure out proper tripwires for an LLM that are not reliant on the stream-of-text catching itself.

Volt.fm är en digital tjänst som riktar sig till musikälskare som vill få en djupare förståelse för sitt lyssnande. Genom att koppla sitt Spotify-konto kan användaren analysera sin musiksmak på ett mer detaljerat sätt än vad den vanliga appen erbjuder. Tjänsten samlar data om vilka artister, låtar och genrer man lyssnar mest på och presenterar det i tydliga och ofta visuellt tilltalande sammanställningar.

Här är ett exempel på hur det kan se ut.

En av de mest uppskattade funktionerna är möjligheten att följa sin musikstatistik över tid. Användaren kan se hur smaken förändras, vilka låtar som varit mest spelade under olika perioder och upptäcka mönster i sitt lyssnande. Volt.fm erbjuder också jämförelser, där man kan se hur ens musiksmak står sig i relation till andra användare, vilket skapar en social dimension kring musikupplevelsen.

Utöver statistik fungerar tjänsten som ett verktyg för upptäckt. Genom analyser av lyssningshistoriken kan Volt.fm ge rekommendationer på nya artister och låtar som passar ens personliga smakprofil. Detta gör det enklare att hitta ny musik utan att behöva leta aktivt.

Volt.fm en tjänst som kombinerar dataanalys och musikintresse på ett engagerande sätt. Den tilltalar både den nyfikna lyssnaren som vill förstå sina vanor och den passionerade musikfantasten som vill utforska nya ljudvärldar baserat på sin egen smak.

My older son loves looking at family photos and videos on my phone. Of course I’m there supervising his time. My wife and I also limit his TV time to one hour a day. There’s always the temptation of giving our son our phones just to calm him so we try not to do that.

As an experiment my wife bought a custom family photo book from Shutterfly to see if he’ll look at the photos there instead on my phone. It was a failure. But a good thing about it is my younger son loves it. I see him always looking towards the photo book and gets sad if we don’t sit and look at it.

While not ideal it sure beats letting them play mindless games and looking at Cocomelon videos. If you have the chance buy a photo book and include that in your children’s collection of books to look at. Hopefully it gets used well.

#children #phone #photobook #pictures #videos

OK, so this hopefully won't be come a daily post, but our President posted this image of himself yesterday (12 April). Utter blasphemy. He should delete it and repent. Hopefully he doesn't really think this about himself...but I tend to take people at their word.

Here's the direct link if you don't believe me...

#politics

Budapest är en av Europas mest fascinerande städer, där historia, kultur och modernitet möts i en fängslande miljö. Om du planerar en långhelg här kommer du att upptäcka en stad som bjuder på allt från imponerande arkitektur och heta källor till en levande mat- och dryckesscen. Här är en guide som kommer att inspirera dig att utforska varje hörn av denna vackra huvudstad i Ungern.

När du stiger in i Budapest känns det som att kliva in i en annan tid. Staden är uppdelad av Donau, som skiljer Buda och Pest åt och binder dem samman med sina ikoniska broar, som Széchenyi kedjebron. Börja din resa på den västra sidan, Buda, som känns lite mer lugn och traditionell. Här ligger det magnifika Budaslottet, som reser sig ovanför staden och erbjuder en hisnande utsikt över Donau. Slottet är inte bara ett historiskt monument utan också hem för flera museer, inklusive Ungerns nationalgalleri. Promenera genom slottets gator och upptäck de smala gränderna som leder dig tillbaka till medeltiden. Borterst på den västra sidan hittar du Gellértberget, vars topp erbjuder en av de bästa vyerna över hela staden. Om du är i form kan du ta trapporna upp, eller välja den mer bekväma hissen som går upp till citadellet, där du kan njuta av ett glas vin medan du blickar ut över den gyllene Donau.

När du korsar bron till den östra sidan, Pest, möts du av en helt annan atmosfär. Här är det liv och rörelse, med butiker, kaféer och restauranger som lockar både lokalbefolkningen och turister. Hjärtpunkten i Pest är den storslagna Andrássy-avenyn, som påminner om Paris med sina eleganta byggnader och trädkantade boulevarder. Längs avenyn hittar du operahuset, en av de vackraste byggnaderna i Europa, och St. Stephans basilika, som är uppkallad efter Ungerns första kung och rymmer en helig handrelik. Klättra upp i basilikan och njut av panoramautsikten över takåsarna och den omgivande staden. Om du är i stan under julen kommer Andrássy-avenyn att förvandlas till en sagolik marknad med glödlampor, julgranar och doften av kryddor som lockar besökarna till julstämning.

En av de mest unika upplevelserna i Budapest är dess termiska bad. Staden ligger på en underjordisk varmvattenkälla, och baden har varit en del av lokalbefolkningens liv i århundraden. Det mest berömda badet är Széchenyibadet, ett magnifiskt jugendbad med turkisk inspirerad arkitektur. Här kan du simma i de heta bassängerna, njuta av ångbadet eller bara ligga och slappna av i den varma vattnet omgiven av mosaik och skulpturer. Om du vill ha en mer intim upplevelse kan du besöka Gellértbadet, som är lika vackert och dessutom har en utomhuspool med havsutsikt. Baden är inte bara en plats att tvätta sig på, utan en upplevelse i sig, där du kan tillbringa hela dagen omgiven av historia och avkoppling.

När kvällen faller på bör du ge dig ut och utforska stadens nattliv. Budapest har ett mycket levande nattliv, med allt från traditionella ungerska vinbarer till moderna klubbar. Om du vill prova lokal mat och dryck bör du besöka en ruin pub, som är en typisk ungersk företeelse. Dessa pubar ligger i gamla, övergivna hus och trädgårdar, och har en unik atmosfär med ljus, musik och en mix av lokalbefolkning och turister. Szimpla Kert är den mest berömda ruin puben och ett måste att besöka. Här kan du njuta av ungerska specialiteter som goulash, langos och chimney cake, medan du lyssnar på live musik och umgås med nya människor. För en mer sofistikerad kväll kan du besöka en vinbar i hjärtat av Budapest, där du kan prova ungerska viner som Egri Bikavér, eller “Tjurens blod”, en kraftfull rödvin som är perfekt att njuta av tillsammans med en tallrik korv och ost.

Mat är en stor del av den ungerska kulturen, och Budapest har en fantastisk mat- och dryckesscen som sträcker sig från traditionella rätter till moderna fusionkök. För att verkligen uppleva den ungerska maten bör du besöka en traditionell étkezde, eller matsal, där du kan njuta av hemlagad mat till rimliga priser. Rosenstein Vendéglő är ett utmärkt val, där du kan prova rätter som paprikachicken med nokedli, en typ av ungerska nudlar. Om du är ute efter en mer modern upplevelse kan du besöka Menza, en restaurang som serverar ungerska rätter med en modern twist i en retro miljö. För en snabbare måltid kan du prova street food, som langos, en friterad degkaka toppad med gräddfil och ost, eller chimney cake, en söt, spiralformad bakelse som är perfekt att njuta av medan du promenerar längs Donau.

För dem som älskar konst och historia är Budapest en skattkista. Staden har flera museer som är värda ett besök, som Ungerns nationalmuseum, som berättar historien om landet från romartiden till idag. På andra sidan Donau ligger Konstmuseumet, som rymmer verk av europeiska mästare som Rembrandt och El Greco. Om du är intresserad av konstscenen bör du också besöka House of Terror, ett museum som berättar historien om de två diktaturerna som har präglat Ungern under 1900-talet. Museet ligger i en byggnad som tidigare var säte för den nazistiska och kommunistiska regimen, och erbjuder en gripande och tankeväckande upplevelse.

När det kommer till boende har Budapest något för alla smaker och budgetar. Om du vill bo mitt i hjärtat av staden och ha allt inom gångavstånd bör du välja ett hotell på eller nära Andrássy-avenyn. Hotel Continental Budapest är ett utmärkt val, med en fantastisk utsikt över Donau och en pool på taket. För en mer intim och charmig upplevelse kan du välja att bo på ett hotell i hjärtat av Buda, som Budapest Castle Hotel, som ligger i ett gammalt kloster och erbjuder en lugn reträtt mitt i staden. Om du är på jakt efter lyx och bekvämlighet är Four Seasons Hotel Gresham Palace ett av de finaste hotellen i Europa, med en hisnande arkitektur och en spaavdelning som är svår att motstå.

En av de bästa sakerna med Budapest är att staden är både historisk och modern på samma gång. Du kan tillbringa en dag med att utforska gamla ruiner och kungliga slott, och nästa dag njuta av en cocktail på en rooftopbar med utsikt över hela staden. För en riktig höjdpunkt kan du besöka 360 Bar, en bar som ligger på taket av ett hus i centrala Budapest. Här kan du njuta av en drink medan du tittar ut över hustaken och de upplysta monumenten som lyser upp natthimlen.

Om du har tid över bör du också ge dig ut på en utflykt utanför staden. Óbuda, den gamla delen av Budapest, är en trevlig plats att besöka för att se de romerska ruinerna och njuta av en lugnare atmosfär. En annan populär utflykt är till Margaretön, en grön ö mitt i Donau som är perfekt för en picnic eller en promenad. Ön är också hem för en konsertsal och en liten zoo, vilket gör den till en perfekt plats för en familjedag.

Budapest är en stad som aldrig tar slut på saker att göra och upplevelser att utforska. Oavsett om du är där för att njuta av den rika historien, de heta källorna, den fantastiska maten eller det pulserande nattlivet, kommer du att lämna staden med minnen som varar livet ut. Så packa dina väskor, boka ditt flyg och ge dig ut på ett äventyr i en av Europas vackraste städer. Budapest väntar på dig!

Some WordPress plugin businesses won't survive this.

If you spend any time on social media, you'll see that revenue is coming down for WordPress plugin businesses, and who knows where they'll bottom out. Honestly, some of them are screwed, and it's not looking good for others.

For as long as I can remember, the defensible position for most plugins has always been:

• Feature gating
• Add-ons
• Support

There are others to consider, but these have always been the main reasons why you'd renew a license. Today, Claude (or pretty much any AI offering) sorta makes them less critical.

For example, consider a plugin that revokes access to certain settings unless you have a valid license code. Or, one that shows a constant license nag on your dashboard. Well, now you can just whip up Claude and tell it to remove the code that does this and you're done. You don't have to be a developer, it just takes a couple of seconds.

For add-ons, it does sort of depend on the scope. Those that add simple integrations are no longer a necessary buy. Why pay extra to connect to Mailchimp when AI can just whip up a mini-plugin for you? Pretty much any connector add-on is a quick fix. Okay, it's perhaps a tad longer if you're not a developer through trial and error. But if you have a client and you're a dev, you can save your client money by just having AI build out the connection really quick.

There will always be a need for support, but less so now when you can just ask AI for help to troubleshoot something. This is especially true for plugins that are more of a utility. Now, on the other side of this is that many plugin companies are using AI to help them give better support. Of the three, this one is the area that is still a strong motivator to renew a license, plugin depending.

Now What?

You know, I don't have a definitive solution for this one. I don't think anyone does as the market sands are still shifting. AI has really challenged the status quo of tech.

For me, here are the areas I'd be thinking about if running a WordPress plugin business:

Community

AI can't recreate it. This is a wedge. This is why someone will want to renew. Many plugins have big communities but they are an afterthought. Some even consider them a burden. It's time to make it a top priority. For example, I would start evaluating the utility of adding a Slack or Discord offering. Or, potentially investing more heavily into a FB group if it already exists.

SaaS Certain Features

Look for the areas that create the most support and try to find a way to make those a SaaS to improve user experience, dependability and to reduce headaches for both you and your customers. If you're hung up on keeping that part of the code open source, you can still do so if you want (though it's not necessary).

Invest in New Marketing

Blogging is still worth it, on some level, but if that's all you do then time to move into new areas. Connection matters, and for the moment, YouTube is how you do that. I'd invest heavily into YouTube to bring about the human element in an AI world (this goes back to my first point on community).

WordPress Isn't Going Anywhere

This is not the “death” of the platform by any means. New avenues are going to open up, and that means for WordPress plugins as well. This is just a market shift, and there will be some growing pains along the way. For some, this means the end of their business. That's the nature of the free market.

#WordPress

Viele Menschen engagieren sich derzeit mit beeindruckender Energie in demokratische Projekte – weit seltener jedoch in demokratische Parteien. Dafür gibt es durchaus nachvollziehbare Gründe. Parteien gelten allgemein als schwer zugänglich, ihre Entscheidungswege als komplex, manches, was von oben kommt, bleibt selbst für Engagierte vor Ort nicht immer transparent.

Und dennoch: Wir leben in einer parlamentarischen Demokratie. Politische Initiativen, zivilgesellschaftliches Engagement und Bewegungen können Debatten anstoßen, Druck erzeugen und Perspektiven verschieben. Doch die konkrete Umsetzung politischer Vorhaben – also das Organisieren von Mehrheiten, das Verabschieden von Gesetzen, das Gestalten von Regierungspolitik – erfolgt nach wie vor maßgeblich über Parteien. Wer sie strukturell schwächt, schwächt damit auch die zentralen Instrumente demokratischer Gestaltung.

Gleichzeitig wäre es verkürzt, Engagement außerhalb von Parteien als bloße Konkurrenz zu begreifen. Im Gegenteil: Oft sind es gerade Bewegungen und Projekte, die Themen setzen, Parteien herausfordern und sie inhaltlich voranbringen. Demokratische Erneuerung entsteht im Zusammenspiel – nicht im Gegeneinander. Weder Parteien allein noch zivilgesellschaftliche Initiativen für sich genommen reichen aus, um nachhaltige Veränderungen zu bewirken.

Gerade deshalb erscheint es mir aber als sehr sinnvoll, auch dort Verantwortung zu übernehmen, wo politische Entscheidungen tatsächlich getroffen werden. Politik beginnt für die meisten Menschen vor der eigenen Haustür – und sie bleibt auch dann wirksam, wenn man bereit ist, Spannungen und Widersprüche innerhalb von Parteien auszuhalten. Diese Auseinandersetzungen sind kein Zeichen von Schwäche, sondern Teil demokratischer Praxis.

Ich würde mir deshalb wünschen, dass mehr Menschen diesen Weg wählen und sich in einer Partei engagieren. Nicht aus naivem Optimismus, sondern aus einer realistischen Einschätzung heraus: Parteien sind veränderbar, wenn auch nicht beliebig. Einfluss durch Engagement ist nicht garantiert – dafür sind sie zu komplex und zu stark in institutionelle Logiken eingebunden. Und doch zeigt sich immer wieder, gerade im Wahlkampf oder in Phasen intensiver Mobilisierung: Keine Parteispitze kann ohne eine aktive, überzeugte Basis nachhaltig wirken – dadurch haben wir an der Basis auch ein starkes Druckmittel, um Veränderungen zu erzwingen.

Eine lebendige Demokratie braucht beides – starke zivilgesellschaftliche Impulse und handlungsfähige Parteien. Entscheidend ist meines Erachtens, dass sich mehr Menschen nicht nur für das eine oder das andere entscheiden, sondern bereit sind, diese Verbindung mitzugestalten. Und momentan braucht es mehr aktive Menschen in Parteien, die die Ausdauer haben, sich für Veränderungen stark zu machen.

昔、自分はアニメが好きだと思っていた。 大学1年から4年にかけて、確かにアニメをよく見ていたからだ。 ただ、社会人になって、アニメを見る事はいきなりなくなった。忙しくもないのにだ。

今は、本当にアニメに興味がない。 むしろ、映像そのものに興味がないとも言える。 なぜ興味がないのかと問われれば、理由は単純で、ただ自分の生活を追うこと、それ自体が自分にとっての、そして、そのまんまの意味での現実であり、それで完結しているからだろう。

しかし、当時見ていたアニメのキャラクターに対して、その時の自分にとっては大事な存在であった。 SNSで、『らき☆すた』や『涼宮ハルヒ』の画像が流れてくると未だにそこで少し手を止めてしまう。 なんとなく、その感覚をどこか美しいもののように捉えていたが、それを言語化したときに気づいたのは、ただ自分が枯れていただけだった、という少し悲しい事実でもある。 言語化した時に悲しい気持ちになるのは慣れている。 俺はいつもなぜそれを美しいと思ったのか、という部分をいつも抽出できない。

本質からは少し外れる。 自分の悪い癖として、思考を数珠つなぎにして本題から逸らしてしまって申し訳ない。 特に、体力が万全でないと感じたときにその傾向が強くなる。 そういうとき、自分で自分をつまらない人間だと思う一方で、このままの自分で終わるはずがないという妙な確信もあり、いずれ自然に修復されるだろうと考えて、能動的な行動を先送りにしてしまう。

映像が好きになれない理由の一つとして、容量の重たさがある。 テキストに比べて、映像は容量が大きく、情報量も多く、扱うにも負荷がかかる。 テキストは自由に編集・生成できてストレスがないが、映像は現代のコンピューターでもまだ重い。 自分は重たいものを持つのが嫌いだ。 重さは、自分の限界を露わにし、できることの範囲を強制的に意識させる。つまり、窮屈さを増幅させる。 映像も、帰りにスーパーで買う食材も、水2L×9本の段ボールも、すべて窮屈だ。 最終的に俺は空を飛びたいというのに。

映像は重い。 音楽は普通。 テキストは軽い。 そう、テキストは軽い。

だから自分は、こうして文章を書いていられるのだと思う。

How was your day beautiful?

I want to know everything so please don’t spare any details. Did you see the sun today..?

I love your nail colours, what inspired you..?

I want to let you know, I love when your hair curls and you’re half asleep to put the kettle on in the morning. I love how you hold yourself to standards built on self love and strength.

Did you know? I think the stars shine for you… I look for signs of you everywhere because you’re always where I want to be.

I love that you wear your activewear when you can’t decide on what outfit for the day.

The way you take care of others and cheer them on is beautiful, please don’t ever change that about you.

Thank you for asking how my day was, and really listening. Same time tomorrow gorgeous?