the origin repo is here.

this note records my questions and solutions of this project.

First two questions are:

• what is the code const todoInput = document.querySelector(".todo-input") try to do?
• what “event listeners” are (like the addEventListener parts)? or who listening the event?

The first one is to use dot selector to pass the todo-input-related to todoInput, and the code could use it for event listening logic writing. The second one is the browser that listening the event, the event listeners maybe a process of a browser, and when the code which contain addEventListener, browser then create a process for event listen. but actually I'm not sure the explain is right or not.

The whole things are: user write the content, and click the so called Send button, browser listening this button event, cuz the JS code we write is running in the browser, and the browser know, then execute the specific function, for example, addTodo.

Then another question is: if don't create div tag, what will happen?

If we change the code in addTodo from this:

todoDiv.appendChild(newTodo);
todoDiv.appendChild(completedButton);
todoDiv.appendChild(trashButton);
todoList.appendChild(todoDiv);

to this:

todoList.appendChild(newTodo);
todoList.appendChild(completedButton);
todoList.appendChild(trashButton);

which mean directly put the Send button, Delete button, and div on todoList. we could see: after changing the code, those three are divided, much ugly. Although I don't know why I refresh the page and everything become normal(maybe the browser is correcting my code).

Refactor

After read the function of getTodos, I know why after refresh. The page become normal because after refresh, the getTodos function is called, and there also a create todo logic in it, since there the logic is right, the page will still perform right.

But this also come up an issue that, there are repetitive codes in addTodo and getTodos, we can DRY that code.

I DRY that code myself, but seems some bugs occur, so I think I should read twice before coding.

Before, the functions addTodo and getTodos are looked like this:

function addTodo(e) {
  e.preventDefault();
  
  // Create todo div
  const todoDiv = document.createElement("div");
  todoDiv.classList.add("todo");
  
  // Create list
  const newTodo = document.createElement("li");
  newTodo.innerText = todoInput.value;
  
  // Save to local
  saveLocalTodos(todoInput.value);
  newTodo.classList.add("todo-item");
  todoDiv.appendChild(newTodo);
  todoInput.value = "";
  
  // Create Completed Button
  const completedButton = document.createElement("button");
  completedButton.innerHTML = `✓`;
  completedButton.classList.add("complete-btn");
  todoDiv.appendChild(completedButton);
  
  // Create trash button
  const trashButton = document.createElement("button");
  trashButton.innerHTML = `✗`;
  trashButton.classList.add("trash-btn");
  todoDiv.appendChild(trashButton);
  
  // Final Todo
  todoList.appendChild(todoDiv);
}

function getTodos() {
  let todos;
  
  if (localStorage.getItem("todos") === null) {
    todos = [];
  } else {
    todos = JSON.parse(localStorage.getItem("todos"));
  }
  
  todos.forEach(function (todo) {
    // Create todo div
    const todoDiv = document.createElement("div");
    todoDiv.classList.add("todo");
    
    // Create list
    const newTodo = document.createElement("li");
    newTodo.innerText = todo;
    newTodo.classList.add("todo-item");
    todoDiv.appendChild(newTodo);
    todoInput.value = "";
    
    // Create Completed Button
    const completedButton = document.createElement("button");
    completedButton.innerHTML = `✓`;
    completedButton.classList.add("complete-btn");
    todoDiv.appendChild(completedButton);
    
    // Create trash button
    const trashButton = document.createElement("button");
    trashButton.innerHTML = `✗`;
    trashButton.classList.add("trash-btn");
    todoDiv.appendChild(trashButton);
    
    // Final Todo
    todoList.appendChild(todoDiv);
  });

I think it's hard to refactor now, at least at this form.

About these code, here are some questions:

• what is 'e' and what is preventDefault do?
• why we need todoInput.value = "";

As we all know, when a button is submit type, its default action is submit the form to the remote server. But since here we only use local memory to keep the todo list, so don't need to do that. And the 'e' here is just a parameter to pass the related variable of clicking event define by browser.

Delete Myth

After commenting out the style.css link in index.html, I find a strange problem of this code: when I input, submit, and delete the note, it didn't delete at once, but after a refresh. Code is here:

function deleteTodo(e) {
  const item = e.target;

  if (item.classList[0] === "trash-btn") {
    const todo = item.parentElement;
    
    todo.classList.add("fall");
    todo.classList.add("completed");
    removeLocalTodos(todo);
    
    todo.addEventListener("transitionend", (e) => {
      todo.remove();
    });
  }
  
  if (item.classList[0] === "complete-btn") {
    const todo = item.parentElement;
    
    todo.classList.toggle("completed");
  }
}

Here I use console.log to test what is item, and found it is button. But something beyond my surprise:

const todo = item.parentElement;
console.log(todo)
todo.classList.add("fall");
todo.classList.add("completed");
console.log(todo)
removeLocalTodos(todo);

The first and the second log show the same content! which is a div have 3 class.

Last Word

Well, this project is poorly written, I give up reading it. Never, ever, read a rubbish project.

A long time after ChatGPT release, we heavily depending on all kinds of AI products.

• At the end of my college year, 80% of my paper was written by AI.
• After having a job(which is writting script), I use it to coding and give up coding myself.
• During AdventureX 2025, most of the products(including ours) here were created by AI.
• Even some Art Gallery start to put some so-called “AI-generated art” to show.
• Lots of “vibe coders” emege, develop software seems a thing that everyone could do.

We are so damn rely it that we almost lost our own thinking.

Of course I know someone will argue: “then why don't you criticise Google, Facebook, or Tiktok?” My answer is, they only change the way we see the infomation. Or worst, they just push what we wanna hear or see, we could still read the other media. But using AI, most of people will lost their thinking ability.

Don't use, you lose. When AI start its deep thinking, who the hell will think by themself? Once people are not thinking by themself, they are just a AI-prompt speaker, say what AI say, do what AI suggest.

Here is a talk from TED, it hold the same point with me.

On Feb 24th, I finish my first time hackthon on Devpost, with other three friends.

On June 24th, I receive an invitation email from AdventureX 2025. On July 28th, I finished the five days hackathon in Hangzhou.

Later, I joined a hackathon launched by Hackathon Weekly, a organization in Shenzhen.

I was excited, passionate, fall in love with these hackathons. I once hope that, in China, there will be more well-organized hackathons there waiting for people to join in. But now, what I wanna say is: Don't join any hackathon in China, and here are why.

Root weak here

Open Source community is weak in China, and due to the network policy, even in code&design, some people still don't know how to use oversea services.

Most of the hackathons in China don't have the enough revenue to run. They seldom have support from Big Tech like Tencent, Alibaba, Baidu or ByteDance, except for those launched by Big Tech. So there is far less hackathons here in China, and is reasonable why the hackathons in China is poor and low-quality: it just hard to launch new one.

Hasty is evil

Maybe this is not a special one in China, the hackathon oversea is also. But I still wanna say: lots of people are hasty here.

When I join in AdventureX 2025, you could hear at least five people here are drop out, or just don't care school work, just for join hackahton or embrace innovation. Everyone seems want to be next Elon, Jobs, Gates, want to build something great, but hardly sit for a single thing to do.

This won't just be a home for old writings. Just putting a few things here while I shutter some internet presences. Writings anonymised and in one place. Lovely.

#notes #december2025

Yesterday I watched a game of chess. This was the third game between two people: one homeless, the other suspended 20 to 30 feet above the Earth in a small perspex box near Tower Bridge. The score was one all.

The man in the box was renowned magician and levitator David Blaine. His latest trick, Above the Below, is to go 44 days without food in said box, thereby besting Jesus’ world record by four days.

I see Blaine’s opponent, Francois Greeff, at about 10 in the morning. A large chessboard plastic pieces is laid out. On it it says U R NOT ALONE.

Greeff strides into the field of play, an apparently ordinary gent in a suit. He carries a sign. “Hidden Disability is the Prime Cause of Homelessness”. Blaine acknowledges with a friendly wave.

Like many — maybe all — people affected by homelessness, Greeff is not the stereotype.. Most passers-by will see a man in a suit looking intently at a chess board. If they speak to him they’ll hear a well-spoken South African accent. Upon closer inspection, though: the tattered suitcase, fraying suit, laceless shoes.

After weighing down the mat — autumn is putting in an appearance, it seems — the game begins. Greeff hides two large pawns behind his back. Pointing, Blaine chooses. He’ll play white.

The ranks and files of the board are labelled in duct tape, 1 to 8 and A to H. Greeff and Blaine have developed a simple but effective sign language. Blaine raises a hand to indicate he’s ready to move. This gesture differs only slightly from the friendly but lethargic wave to visitors. Greeff acknowledges with a wave of his own.

Blaine holds up some fingers, corresponding to the rank where the piece he wants to move sits. If there’s more than one, Greeff points to a piece with a broomstick. Blaine wags a finger, and then points left or right. Before long it’s thumbs-up.

Next, Blaine holds up some fingers to show how many squares he wants to move. This time Greeff picks up Blaine’s piece puts it down in the various possibilities. Blaine responds either thumbs up or thumbs down. It’s all great fun to watch.

Blaine plans his moves with pen and paper. His attention only moves to the giant board as Greeff makes his grandiose moves. Blaine communicates alertly, keenly and seems generally normal. (This was at the time that some of his TV appearances were borderline catatonic.)

It’s played out in public, but this is a personal battle for Greeff. He doesn’t want help. He insists that you don’t point at the board when you speak to him, in case Blaine interprets this as taking advice. Otherwise, he’s happy to talk.

“There’s no doubt about it, there’s a real man up there”, he says to passers by who question whether Blaine’s stunt is somehow a trick. “You know when you arm-wrestle, you can feel the resistance and strength of your opponent? This game is the same. I can feel the strength and resistance of David’s mind.” Greeff’s mind isn’t too shabby either. Later I’d find out he’s written a guide to cryptic crosswords.

The game lasts six or seven hours. Sometimes there are errors. Blaine gives away a bishop cheaply in the opening phase. But these are players in unusual circumstances. David Blaine hasn’t eaten for 15 days. Greeff’s story is different. “My cause is more important than my name, so please refer to me as The Hidden Disability Guy, his website says.

Blaine takes longer to move than Greeff. Maybe he just wants to the entertainment to last. Most days there’ll be no game of chess. There’ll just be people waving, or make guerilla documentaries. On a bad day, people throw things.

Mid-afternoon the storm comes. Greeff, equipped with umbrella, continues undeterred. Later he tells me he’s pleased that it rained. As visitors hurry for cover, Greeff is resolved.

Greeff wins between 4 and 5pm. He’s nibbled away at Blaine’s material the whole game. Under-prepared, I watch the end game from the cover of City Hall.

Greeff eventually gives up the umbrella — too windy. He packs up his things with the help of a wobbly associate, dancing to the tune of Special Brew.

Later, I bumped into Greeff at London Bridge station. I congratulated him on his victory, two games to one. He’d arrange to get some pictures from the hipster media types, but he was skeptical that the media proper would be interested. I suggested the internet may be different. Encouraged, Greeff gave me a sticker with his contact details.

“Email me, but make sure you tell me who you are and where I spoke to you”, he said. “I have a disability that affects my memory.” Shaking hands, we parted ways. I went north, The Hidden Disability Guy went south.

#notes #september2003

Hace tiempo, cuando acumulé la suficiente fuerza para ello, me vi un video sobre las tradwives que me interesaba. La autora no es santo de mi devoción, ni la sigo ni nada, pero quería escuchar el discurso. Centra su video en recordarle a la gente que las tradwives son una performance, y no debería usarse como manual de ama de casa. Aún así me siento violenta y molesta porque se reitera con frecuencia que “muy bien por ellas, que hacen mucho dinero con su actuación, una forma más de trabajo y performance”. No, muy bien por ellas no, el hecho de que su performance mueva dinero no la hace más legítima (quizás lo empeore aún más, si cabe). La responsabilidad sobre lo que proyectan sigue estando ahí, no sobrecae solamente en las mujeres cansadas y enganchadas al scroll infinito de sus respectivas aplicaciones (por lo general) privativas. Destaco esto último porque es fácil que el algoritmo de estas apps enganchen una búsqueda de un perfil de mujer que consista en “tips para cocinar” o “tips para calmar a tu bebé” en una ola de tradwives.

Hay cosas de toda esta retórica de mujer ama de casa (más allá del movimiento tradwife) que me resulta muy complejo. Hay una asociación automática del cuidado del hogar con su contraposición, girl-boss creo que se llama popularmente, basada en la idea de excelencia y esfuerzo en el entorno laboral.

Escoge tu veneno.

Al rebuscar esos espacios que están entre ambos conceptos, me he visto en un aprieto. Cuando he leído a Adrienne Rich hablar de la casa y la maternidad en Nacemos de mujer, me he sentido tan violenta que he tenido que frenar. La maternidad se presenta como un yugo en el que se mezcla el amor por una criatura y el odio a todo lo demás que representa cuidarla. No puedo leerlo ahora mismo.

Cuando he leído a Vivian Gornick en Apegos feroces, empiezo a ver varios “registros” de mujer en la casa y veo reflejos de eso que busco, pero de nuevo el patriarcado deslumbra siempre en ese papel. Por ejemplo narrando como su madre se quedaba en la casa pese a haber empezado un trabajo porque su marido (pese a ser activo en círculos de izquierda de mediados de siglo XX en EEUU) sentía agresividad en la idea de que su hija se criase sin una madre constantemente en la casa.

Saltamos entonces, entre otros, a Ir más allá de la piel, escritos de Federici, donde por fin encuentro textos que sitúan el cuerpo, la mujer, la maternidad y el hogar desde otra mirada. Voy a destacar un parrafito que me llegó como una bocanada de aire:

(…) Y la maternidad podría no ser un acto performativo de género, sino entenderse como una decisión política e instauradora de valores. En una sociedad autónoma y autogobernada, este tipo de decisiones se tomaría teniendo en cuenta el bienestar colectivo, los recursos disponibles y la preservación de la riqueza natural. (…) la decisión de tener un hijo también debe contemplarse como una negativa a permitir que los planificadores capitalistas decidan quién puede vivir y quién tiene que morir o ni siquiera llegar a nacer.

Subrayo con el lápiz “podría no ser un acto performativo de género”, satisfecha. Ahí empiezo a encontrarme. Desde los feminismos hemos hablado tanto de cuidar y criar como una sentencia, que cuidar y criar parece el camino malo. Si bien es cierto que por lo general, la independencia económica ayuda a las mujeres a sortear algunos caminos de opresión (por ejemplo la diferencia de poder y su respectiva exposición a la violencia que supone depender de un hombre, pareja o familia), ensalzar la figura del trabajo solo sustituye una prisión por otra.

Volviendo al tema de las tradwives, leí en algún lado la frase “si es lo que quieren, no hay nada de malo”, acompañado de algún comentario sobre las feministas queriendo imponer elecciones vitales sobre las mujeres. Aquí hay varios puntos a destacar. Para empezar, casi todos estos videos (me he tenido que ver algunos o parte de ellos, poco a poco porque si no era una tortura emocional y mental) comentan algo en la línea de “mi marido me ha pedido X, y yo hago su deseo realidad porque él paga las facturas”, y por cierto, no he encontrado tampoco ningún tipo de reciprocidad de “él hace X por mí porque me quiere mucho” o similar. Hay una posición muy clara promovida en esos videos: el hombre (siempre hombre) que se supone que es mi pareja sentimental, es mi jefe. Mi vida doméstica y emocional son un anexo de su vida, él es el protagonista. Dentro de esto, algunas actúan mostrando algún tipo de cuidado (por lo general absurdamente sacrificado) a sus criaturas. Sea como fuere, este tipo de discurso sólo tiene sentido en un contexto que se asume patriarcal y poniendo el centro en quién pone el dinero (que se asume sin rechistar que es un hombre). Por lo tanto, ya de primeras eso de “libertad de decisión” necesita muchas comillas.

Por otro lado la proyección activa de ese rol a través de las redes está promocionando que la mujer (en general y sin avisos de ningún tipo sobre que están haciendo una performance) acepte ese papel. Lo romantiza, y lo eleva a una imagen que puede distar mucho de lo que realmente era tradicionalmente una mujer, su hogar y su familia. Quiero aclarar con esto último, no me refiero a que esta realidad fuera más atractiva ni mucho menos, si no destacar que no hay una búsqueda real sobre tradiciones o una investigación sobre la mujer de hace generaciones. Es sólo una selección muy concreta de fantasías: cocina, maternidad sacrificada (incluso en situaciones que no requerirían de sacrificio) y sumisión a la figura masculina. Generalmente acompañado también de una estética concreta de ropa y estilo.

En este espacio tan violento, ¿cómo encuentra una referencias para criar desde los feminismos? Pareciera que el simple hecho de criar y cuidar ya viene asociado a “rendirse” al patriarcado, si una escucha los ecos de las redes.

He estado luchando contra esta marea desde el momento en el que me quedé embarazada. Si buscaba referencias, videos, artículos, etc sobre crianza, era un auténtico campo de minas. Ese video cuqui que te enseña una receta interesante y esa madre que te explica como ha hecho un juego sensorial para su bebé, puede saltarte de pronto con una postura fantasiosa tradwife y te hace sospechar o, peor aún, dudar sobre ti misma. “Yo sólo quería cuidar y enseñarle el mundo a otra personita”, es lo que me he repetido muchas veces desde hace un año y algo. De pronto me he visto empujada a una situación en la que el trabajo se ve con otros ojos, y los roles de género que ya resonaban de antes a lo lejos ahora son campanazos diarios. No quería asumir ese papel de girl-boss pero tampoco actuar como madre sacrificada que se queda en la casa.

Para mi la respuesta ha sido una mezcla de varias cosas, como no tener cuenta en redes tipo Instagram , TikTok, Twitter, etc. Pero principalmente juntarme con otras madres. La soledad, el cansancio y la falta de tiempo facilitan que cualquier mensaje simple y fantasioso envenene la proyección de la realidad. Sin embargo juntarme y hablar con otras mujeres (que, irónicamente, es algo que sí ha hecho en otras generaciones), me ha ayudado a encontrar esa crianza de la que habla Federici. También, en mi caso, tener una pareja sensibilizada que ha hecho su búsqueda, estudio y trabajo personal en paralelo al mío para compensar esas cosas que el patriarcado asume de nuestra relación, como el hecho de que él sea una suerte de jefe.

Tener una red de apoyo fuera y dentro de la familia afecta también a ese concepto de sacrificio, y me hace pensar que si no llego y otras llegan, mi hija se beneficia de mi salud emocional y mental, así como de contar indirectamente de más amor a parte del mio. Mi hija sigue siendo mi hija, pero por ella se preocupan (y diferentes medidas) toda una comunidad, seleccionada con cuidado por su padre y por mí. En este descubrimiento de la crianza también caben muchas más posibilidades (quedarse o no en casa, en que medida, de qué manera, por ejemplo, sin que esto sea agresivo ni me haga dudar de mi apoyo a los feminismos. Los configura de una forma más abierta y realista.

Los cuidados como parte de esa proyección de sociedad amable, no como una soga patriarcal. Son una acción que rota. Un día mi pareja me cuida, otro le cuido yo, y así entre les dos, cuidamos a nuestra hija. A veces me siento perdida, pero otras madres tienen la experiencia que buscaba para encontrarme. La respuesta -para mí- estaba en la comunidad, y en salir de esa red de soledad, de individualismo envenenado que promocionan esas redes.

Las tradwife solo son actrices que se aprovechan de ese veneno tan lucrativo.

La crianza y los cuidados no son exclusivos de sus fantasías.

Y eso será lo que le muestre a mi hija.

JOURNAL 4 deécembre 2025

Les psy aujourd'hui m'ont dit que j'étais tout au bord de la falaise mais faut pas que j’aie peur de sauter. Je connais déjà la réponse et je ne veux pas l'accepter parce que ça va inévitablement me questionner après sur moi-même, et je ne veux pas. Et c’est vrai, je sais ce soir qu’ils ont raison. J’y ai bien réfléchi depuis. Oui ça y est, je sais, et je n’ai pas envie d’aller plus loin. Et je sais qu’il va bien falloir le faire, et A sera à mon côté. Mais je ne veux pas le faire tout de suite. Je veux d'abord un gros câlin, gros gros gros, je veux pas descendre au fond.

Washington University of Health and Sciences Belize News: Why Caribbean Medical Schools Are Becoming the Top Choice for Aspiring Doctors

According to the latest Washington University of Health and Sciences Belize News, more aspiring doctors are exploring the advantages of pursuing their medical education in the Caribbean. With flexible entry pathways, globally aligned programs, and strong clinical training opportunities, Caribbean medical schools have quickly become a preferred option for students aiming to build a successful career in medicine. 1. Flexible and Student-Friendly Admission Processes Recent updates highlighted in Washington University of Health and Sciences Belize News show that one of the biggest attractions of Caribbean medical schools is their accessible and student-friendly admission system. Many passionate students face intense competition and limited seats in traditional medical schools, especially in the U.S. and Canada. Caribbean institutions provide an alternative route that maintains high academic standards while giving deserving students a fair opportunity to pursue their dreams of becoming physicians. 2. Globally Aligned and Modern Curriculum Another key point emphasized in Washington University of Health and Sciences Belize News is the strong academic foundation offered by Caribbean schools. Their curriculum aligns with global medical education standards and integrates clinical concepts early in the learning process. This design helps prepare students for international licensing exams, including the USMLE, ensuring compatibility with medical systems in the U.S. and Canada. 3. Early Clinical Exposure and Expanded Training Opportunities Caribbean medical schools are especially recognized for their early clinical exposure. Reports from Washington University of Health and Sciences Belize News highlight how students gain hands-on experience in real medical environments sooner than they might through other pathways. Many institutions also maintain partnerships with hospitals in the United States, giving students exposure to diverse patient populations and helping them build confidence in clinical practice. 4. Advanced Learning Facilities and Technological Support Modern infrastructure is another reason more students choose Caribbean schools. As mentioned in Washington University of Health and Sciences Belize News, many institutions continuously upgrade their simulation labs, anatomy centers, and digital learning tools. These facilities enhance learning by helping students better understand complex medical concepts and develop essential clinical skills. 5. Supportive, Diverse, and Student-Centered Community Caribbean medical schools are known for maintaining small class sizes and fostering a supportive academic environment. This personalized approach allows students to receive one-on-one guidance from experienced faculty. The diverse student community also enriches communication skills and global awareness—qualities vital for future doctors. Conclusion As reflected in the latest Washington University of Health and Sciences Belize News, Caribbean medical schools offer aspiring doctors a strong combination of opportunity, academic excellence, and global readiness. With flexible admissions, a modern curriculum, innovative facilities, and robust clinical pathways, these institutions are becoming the go-to choice for students committed to building a rewarding medical career.

el frío se pega a la ventana y aunque no es nada nuevo este tiempo es así de anticuado un invierno que atrapa la casa estira las horas mientras el silencio / según se mire es soledad o abrigo

STAGES OF MUSIC & AUDIO PRODUCTION

The concept of audio projects, from the earliest ideation to the final release, is an intricate science of creative and technical stages. In this article, I share my personalized approach to music production, which guided me through the production of my EP “Arete.” By distinguishing specific stages, I was able to track my progress, make strategic decisions about project continuance, and effectively manage the overall production process.

I. CONCEPTION

The conception stage sparks the musical journey into existence. It's the birth of an idea, inspired by spontaneous creativity, and born from experimenting with diverse instruments or styles. This stage is characterized by its fluidity and speed; it often concludes as soon as an idea holds enough merit to warrant investing more time and resources.

II. DEMO

Next comes the demo stage, often the longest part of the process. Here, the structure and sound of the track are explored and experimented with, using various amps, synths, and sounds. It's during this stage that many projects are shelved, making it a critical make-or-break point. However, those that persevere are rewarded with a solid foundation track, marking the successful conclusion of this stage.

III. SESSION PREPARATION

Session preparation is a meticulous process involving several sub-checklists. At this stage, the foundation track is exported from the demo project and imported into a new one, complete with key signatures, tempo settings, and beat mapping. Recording settings are adjusted to ensure optimal quality, with stereo recordings set at a 48kHz sample rate and 24bit. Busses are created and assigned, and instruments to be used are prepared.

IV. SESSION

The session stage is where performance and dynamics take center stage. Each performed instrument must have between nine to seventeen takes per alternate take, ensuring a diversity of options for the final mix. This stage is often the most enjoyable, allowing the musicians to immerse themselves in their craft. While individual tracks' durations may vary, a full-length EP typically takes about 2.5 months to perfect.

V. MIXING

The mixing stage focuses on achieving balance and editing the track. After resetting the board and adjusting the faders, a stereo mix is created and then converted into a Dolby Atmos 7.2 surround in a new project alternative.

VI. MASTERING

During the mastering stage, the track's volume is adjusted to prevent distortion and achieve the right loudness. This stage also includes designing the cover concept. The final result is then loaded into a new Logic Audio project file, using a mastering template with Izotope’s Ozone Mastering. The process should not be rushed and requires regular breaks to rest the ears.

VII. DISTRIBUTION

Distribution involves uploading the music to a platform, such as Distrokid, and setting a release date approximately six weeks out. All metadata and accreditation should be completed at this stage, ensuring a smooth release.

VIII. RELEASE

After release, marketing projects commence. By this point, the production process is finalized and complete. #yeggeArticles

In the world of audio production, few tools are as misunderstood—and as essential—as overdrive and distortion. While often associated with screaming guitar solos and aggressive rock music, these effects play a far more nuanced and universal role in modern music production. From the warmth of a vocal track to the punch of a drum mix, subtle harmonic distortion has become one of the secret ingredients that separates amateur recordings from professional productions.

Understanding the Fundamentals

At its core, distortion occurs when an audio signal exceeds the capacity of a system to reproduce it cleanly. When you push an amplifier, preamp, or digital plugin beyond its linear operating range, the peaks of the waveform begin to flatten or “clip.” This clipping creates new harmonic content that wasn't present in the original signal—additional frequencies that add color, character, and perceived loudness.

Overdrive is a gentler, more gradual form of this clipping. It typically introduces predominantly odd-order harmonics (3rd, 5th, 7th) and compresses the signal in a smooth, musical way. Think of it as the sound of analog circuits being pushed just past their comfort zone—warm, saturated, and forgiving.

Distortion is more aggressive, with harder clipping that generates both odd and even harmonics in greater quantities. This creates a more obvious, textured effect that ranges from fuzzy warmth to outright sonic destruction.

The Science of Saturation

When a signal clips, the flat-topped waveform contains additional frequency content beyond the fundamental tone. These harmonics relate mathematically to the original frequency:

• Even harmonics (2nd, 4th, 6th) are octaves and musical intervals that sound consonant and pleasing, adding thickness and warmth
• Odd harmonics (3rd, 5th, 7th) add brightness, edge, and character, but can sound harsh in excess

Different types of distortion—tube, tape, transformer, transistor—each have unique harmonic signatures. Tube distortion, for instance, emphasizes even harmonics and compresses smoothly, which is why it's prized for its “musical” quality. Tape saturation adds warmth and glues elements together through gentle compression and high-frequency softening.

The Power of Subtlety

Here's where things get interesting: you don't need to hear distortion for it to dramatically improve your mix.

When used subtly—often to the point of being nearly imperceptible—overdrive and saturation serve several critical functions:

1. Harmonic Enhancement Adding just 1-2% of harmonic distortion can make a track “pop” without sounding obviously distorted. These additional harmonics help instruments occupy more frequency space, making them fuller and more present. A vocal with gentle saturation cuts through a dense mix more easily because it contains more harmonic information for our ears to latch onto.

2. Perceived Loudness Saturation creates the illusion of increased volume without actually raising peak levels. By adding harmonics and gently compressing transients, material sounds louder and more forward even at the same measured level. This is why analog recordings often feel “bigger” than overly clean digital ones.

3. Glue and Cohesion Passing multiple tracks through the same type of subtle saturation—like a mix bus running through a tape emulation—creates harmonic relationships between elements. This “glues” the mix together, making disparate recordings sound like they were captured in the same space with the same equipment.

4. Taming Harshness Counterintuitively, distortion can make something smoother. By clipping extreme peaks and adding warmth, saturation can tame shrill cymbals, harsh vocals, or brittle digital recordings. The key is using soft clipping that rounds off peaks rather than hard clipping that creates more aggression.

5. Analog Color Digital recordings can sound sterile or “flat” without the subtle nonlinearities present in analog equipment. Adding gentle saturation at multiple stages mimics the cumulative effect of signal passing through consoles, preamps, tape machines, and more—the “mojo” that characterizes classic recordings.

Practical Applications

Vocals: A touch of tube saturation can add body and presence, helping vocals sit perfectly in the mix without excessive EQ or compression. Many engineers apply 10-20% saturation, barely audible in solo but transformative in context.

Drums: Gentle tape saturation on a drum bus adds punch and cohesion, making individual hits feel like parts of a unified kit rather than separate samples.

Bass: Slight overdrive in the upper harmonics helps bass translate to small speakers by adding audible overtones while keeping the fundamental intact.

Mix Bus: Perhaps the most important application—light saturation on the stereo bus (1-3dB of gain reduction) adds dimension and commercial polish. This mimics the cumulative effect of mixing through an analog console.

Parallel Processing: Heavily distorting a copy of a signal and blending it under the clean version allows you to add aggression and harmonics while maintaining clarity—common with drums and bass.

The Philosophy of “Just Enough”

The mastery of distortion in production lies in restraint. The goal isn't to hear the effect but to feel its absence when it's removed.

Professional engineers often use saturation on nearly every channel in microscopic amounts—3-5% here, a barely-driven plugin there. Individually, these might be inaudible, but collectively they transform a mix from flat and digital to warm and three-dimensional.

This is audio production as sculpture: knowing what to add, what to subtract, and when to leave well enough alone. Subtle distortion isn't about making things dirty—it's about making them alive.

Overdrive and distortion represent one of the most powerful tools in the modern producer's arsenal, not despite their ability to degrade a signal, but because of it. In an era where digital recordings can achieve technical perfection, the strategic introduction of controlled imperfection has become essential for creating music that feels organic, powerful, and emotionally resonant.

The next time you hear a record that sounds inexplicably “good”—warm, punchy, and present—there's a strong chance you're hearing the cumulative effect of subtle saturation at work throughout the production chain. It's not magic, but it might as well be.

It’s so strange how I never write anything anymore. I feel like I’ve really cheapened this entire “project”, but to be honest, I have had an outlet in E since meeting her. I have my social needs met, and I have someone I can talk more than enough to. I’m not really sure how I’m supposed to have the urge to journal when I have that person there who wants to listen.

It’s very clear to me that I can’t have anything to do with my salvation. The chasm between me and God is far too wide, and I will never become perfect. This is something that I’ve realized before, but not to the extent I have realized it now. I’ve given up on myself before, but not to this extent, not yet. I was holding a couple things very tightly in my hand and it was getting painful to hold onto them, so painful that I had to let go.

Today, I went to a group Bible study, which really just turned into a private Q&A session for me because I had too many questions. I should feel bad for the other people that had to sit through that, but I don’t. Fuck them. Maybe not really in a fuck them way, but before I got there today, I was spiraling hard, thinking about ways to ruin my life.

During the Bible study, I was able to get a lot of clarity on some questions on how I was to live my life. First off, here’s the roadmap of my current spiritual journey in chronological order. Steps 1-2 are what I’ve experienced thus far, and everything after it is what I see to be my next steps.

1. In a state of existential despair, looking for a clear cut path to salvation because I believed in God and hell, and would do anything to escape it. Fear dominated here, and I would guilt trip myself over the smallest things, because I was trying to achieve my way to salvation through perfection. I’m always going insane in my head.

2. I give up on myself entirely, realizing that I cannot do anything to achieve my salvation, and if God wants me in hell, I cannot do anything about it. So be it. Fear passes away here into a serenity bordering on lifelessness. I’m still spiraling, not in a way driven by fear, but characterized with a fatalistic carelessness.

3. My next stage is approaching this Christian thing entirely differently. No more chasing after perfection. God is the only one that can give me any kind of understanding of truth, change my heart or life in any meaningful way. It can ONLY come from Him. With that presupposition in mind, I’m going to approach this Christianity from a relationship with God angle instead.

Our pastor said, the reason the Good News is called “Good News” is because when you’ve tried to save yourself and failed at it, and realized that you have no potential — zero potential at all to reach across the chasm between you and God, the fact that Jesus came and died on the cross for us is Good News. He claimed that he’d been a Christian for 44 years, decided he was going to become a pastor early on in his life, but he thinks he just understood the Gospel/Good News a week ago, despite the fact that he’d been preached it hundreds of times. I think what he meant there is that there are different levels to understanding this. I believe I am only at the beginning of coming to understand this, and nobody will ever reach completion in their journey. So there will be many more aha moments incoming.

Duty can very quickly become a bad thing in your relationship with God. I’ve had some problems with this, so I’m really not going to try that hard anymore. Our pastor said that a sign of legalism creeping into your life is if you start feeling guilty when you don’t do the “Christian thing”. If I don’t feel very moved by God to do something, I’m not going to do it anymore. I can’t live my life like this anymore. I need to move on, or I’m going to get cardiac arrest.

Our pastor also said something about fighting the law, and fighting against your sin. If you draw a line in the sand for yourself, you’re sure to cross it. However, if you love God, and have abounding joy in Him, you won’t be too tempted by stuff anymore, because you’re already fulfilled. So that’s why I’m going to stop trying to torture myself to perfection in all areas of my life, whether it be being a better programmer, better Christian, etc.. I’m going to approach it via my relationship with God, and let Him work.

I need to keep my hands off the steering wheel, and hand it to God. But even for that, that’s what God is going to do. I need to stop expecting “basic competency” or good things from myself. That’s simply not a possibility. There’s no point expecting a 3-year old to write mathematical proofs. But that’s a very freeing sensation.

tldr; stop focusing on perfection, focus on the relationship. Do it all in community, because God uses community to teach and show us how it’s done.

The future of shopping isn't happening on a screen. It's happening in the spaces between your words and a machine's understanding of what you want. When you ask an AI agent to find you the best noise-cancelling headphones under £300, you're not just outsourcing a Google search. You're delegating an entire decision-making process to an algorithmic intermediary that will reshape how billions of pounds flow through the digital economy.

This is agentic commerce: AI systems that browse, compare, negotiate, and purchase on behalf of humans. And it's already here. OpenAI's ChatGPT now offers instant checkout for purchases from over one million Shopify merchants. Perplexity launched its Comet browser with AI agents that can autonomously complete purchases from any retailer. Opera introduced Browser Operator, the first major browser with AI-based agentic capabilities built directly into its architecture. Google is expanding its AI Mode shopping interface across the United States, adding capabilities that let customers track prices and confirm purchases without ever visiting a retailer's website.

The numbers tell a story of exponential transformation. Traffic to US retail sites from generative AI browsers and chat services increased 4,700 per cent year-over-year in July 2025, according to industry tracking data. McKinsey projects that by 2030, the US business-to-consumer retail market alone could see up to one trillion dollars in orchestrated revenue from agentic commerce, with global projections reaching three trillion to five trillion dollars.

But these astronomical figures obscure a more fundamental question: When AI agents become the primary interface between consumers and commerce, who actually benefits? The answer is forcing a reckoning across the entire e-commerce ecosystem, from multinational retailers to affiliate marketers, from advertising platforms to regulatory bodies. Because agentic commerce doesn't just change how people shop. It fundamentally rewrites the rules about who gets paid, who gets seen, and who gets trusted in the digital marketplace.

The Funnel Collapses

The traditional e-commerce funnel has been the foundational model of online retail for two decades. Awareness leads to interest, interest leads to consideration, consideration leads to conversion. Each stage represented an opportunity for merchants to influence behaviour through advertising, product placement, personalised recommendations, and carefully optimised user experience. The funnel existed because friction existed: the cognitive load of comparing options, the time cost of browsing multiple sites, the effort required to complete a transaction.

AI agents eliminate that friction by compressing the entire funnel into a single conversational exchange. When a customer arriving via an AI agent reaches a retailer's site, they're already further down the sales funnel with stronger intent to purchase. Research shows these customers are ten per cent more engaged than traditional visitors. The agent has already filtered options, evaluated trade-offs, and narrowed the field. The customer isn't browsing. They're buying.

This compression creates a paradox for retailers. Higher conversion rates and more qualified traffic represent the holy grail of e-commerce optimisation. Yet if the AI agent can compress browsing, selection, and checkout into the same dialogue, retailers that sit outside the conversation risk ceding both visibility and sales entirely.

Boston Consulting Group's modelling suggests potential earnings before interest and taxes erosion of up to 500 basis points for retailers, stemming from price transparency, smaller order sizes, and agent platform fees. That five per cent margin compression might not sound catastrophic until you consider that many retailers operate on margins of ten to fifteen per cent. Agentic commerce could eliminate a third of their profitability.

The risks extend beyond margins. Retailers face diminished direct access to customers, weaker brand loyalty, and growing dependence on intermediary platforms. When customers interact primarily with an AI agent rather than a retailer's website or app, the retailer loses the ability to shape the shopping experience, collect first-party data, or build lasting relationships. The brand becomes commoditised: a product specification in an agent's database rather than a destination in its own right.

This isn't speculation. Walmart announced a partnership with OpenAI enabling seamless “chat to checkout” experiences. Shopify integrated with ChatGPT to allow instant purchases from its merchant base. Etsy followed suit. These aren't defensive moves. They're admissions that the platform layer is shifting, and retailers must establish presence where the conversations are happening, even if it means surrendering control over the customer relationship.

The Revenue Model Revolution

If agentic commerce destroys the traditional funnel, it also demolishes the advertising models built upon that funnel. Consider Google Shopping, which has operated for years on a cost-per-click model with effective commission rates around twelve per cent. Or Amazon, whose marketplace charges sellers approximately fifteen per cent in fees and generates billions more through advertising within search results and product pages. These models depend on human eyeballs viewing sponsored listings, clicking through to product pages, and making purchase decisions influenced by paid placement.

AI agents have no eyeballs. They don't see banner ads or sponsored listings. They process structured data, evaluate parameters, and optimise for the objectives their users specify. The entire edifice of digital retail advertising, which represents a 136 billion dollar industry in 2025, suddenly faces an existential question: How do you advertise to an algorithm?

The early answer appears to be: You don't advertise. You pay for performance. OpenAI has reportedly discussed a two per cent affiliate commission model for purchases made through its shopping features. That's six times lower than Google Shopping's traditional rates and seven times lower than Amazon's marketplace fees. The economics are straightforward. In a world where AI agents handle product discovery and comparison, platforms can charge lower fees because they're not operating expensive advertising infrastructure or maintaining complex seller marketplaces. They're simply connecting buyers and sellers, then taking a cut of completed transactions.

This shift from advertising-based revenue to performance-based commissions has profound implications. Advertisers will spend 12.42 billion dollars on affiliate programmes in 2025, up 10.2 per cent year-over-year, driving thirteen per cent of US e-commerce sales. The affiliate marketing ecosystem has adapted quickly to the rise of AI shopping agents, with seventy per cent of citations for some retailers in large language models stemming from affiliate content.

But the transition hasn't been smooth. Retail affiliate marketing revenues took a hit of over fifteen per cent year-over-year in the second quarter of 2024, when Google's search algorithm updates deprioritised many affiliate sites. If ChatGPT or Perplexity become the primary shopping interfaces, and those platforms negotiate direct relationships with merchants rather than relying on affiliate intermediaries, the affiliate model could face an existential threat.

Yet the performance-based structure of affiliate marketing may also be its salvation. Cost-per-acquisition and revenue-share pricing align perfectly with agentic commerce, where marketing dollars are spent only when a purchase is made. Industry analysts predict retail media networks will reshape into affiliate-like ecosystems, complete with new metrics such as “cost per agent conversion.”

The retail media network model faces even more severe disruption. Retail media networks, which allow brands to advertise within retailer websites and apps, are projected to reach 136 billion dollars in value during 2025. But these networks depend on high human traffic volumes consuming brand messages, sponsored product listings, and targeted advertisements. When agentic AI threatens those traffic volumes by handling shopping outside retailer environments, the entire business model begins to crumble.

The industry response has been to pivot from business-to-consumer advertising to what executives are calling business-to-AI: competing for algorithmic attention rather than human attention. Traditional brand building, with its emphasis on emotional connections, lifestyle aspirations, and community, suddenly becomes the most valuable marketing strategy. Because whilst AI agents can evaluate specifications and compare prices, they still rely on the corpus of available information to make recommendations. A brand that has invested in thought leadership, earned media coverage, and authentic community engagement will appear more frequently in that corpus than a brand that exists only as a product listing in a database.

The new battleground isn't the moment of purchase. It's the moment of instruction, when a human tells an AI agent what they're looking for. Influence that initial framing and you influence the entire transaction.

The Merchant's Dilemma

For retailers, agentic commerce presents an agonising choice. Participate in these new platforms and surrender margin, control, and customer data. Refuse to participate and risk becoming invisible to a growing segment of high-intent shoppers.

The mathematics of merchant incentives in this environment grow complex quickly. If Target and Walmart stock the same product at the same price, how does an AI agent decide which retailer to recommend? In traditional e-commerce, the answer involves search engine optimisation, paid advertising, customer reviews, shipping speed, and loyalty programme benefits. In agentic commerce, the answer increasingly depends on which merchant is willing to pay the AI platform a performance incentive.

Industry analysts worry this creates a “pay to play” dynamic reminiscent of Google's shift from organic search results to advertising-dominated listings. Anyone who has used Google knows how much the first page of search results is stuffed with sponsored listings. Could agentic commerce go the same way? Currently, executives at AI companies insist their algorithms pick the best possible choices without pay-to-play arrangements. But when significant money is involved, the concern is whether those principles can hold.

Perplexity has directly criticised Amazon for being “more interested in serving you ads, sponsored results, and influencing your purchasing decisions with upsells and confusing offers.” The criticism isn't just rhetorical posturing. It's a competitive claim: that AI agents provide a cleaner, more consumer-focused shopping experience precisely because they're not corrupted by advertising revenue. Whether that purity can survive as agentic commerce scales to trillions of pounds in transaction volume remains an open question.

Some merchants are exploring alternative incentive structures. Sales performance incentive funds, where retailers pay commissions to AI platforms only when purchases are completed, align merchant interests with platform performance. Dynamic pricing strategies, where retailers offer AI platforms exclusive pricing in exchange for preferential recommendations, create a more transparent marketplace for algorithmic attention. Subscription models, where merchants pay fixed fees for inclusion in AI agent recommendation databases, avoid the pay-per-click inflation that has plagued search advertising.

But each of these approaches raises questions about transparency, fairness, and consumer welfare. If an AI agent recommends Target over Walmart because Target pays a higher commission, is that a betrayal of the user's trust? Or is it simply the same economic reality that has always governed retail, now made more efficient through automation? The answer depends largely on disclosure: whether users understand the incentives shaping the recommendations they receive.

The Transparency Crisis

Trust is the currency of AI shopping agents. If users don't trust that an agent is acting in their best interests, they won't delegate purchasing decisions. And trust requires transparency: understanding how recommendations are generated, what incentives influence those recommendations, and whether the agent is optimising for the user's preferences or the platform's profit.

The current state of transparency in AI shopping is, charitably, opaque. Most AI platforms provide little visibility into their recommendation algorithms. Users don't know which merchants have paid for preferential placement, how commissions affect product rankings, or what data is being used to personalise suggestions. The Federal Trade Commission has made clear there is no AI exemption from existing consumer protection laws, and firms deploying AI systems have an obligation to ensure those systems are transparent, explainable, fair, and empirically sound.

But transparency in AI systems is technically challenging. The models underlying ChatGPT, Claude, or Perplexity are “black boxes” even to their creators: neural networks with billions of parameters that produce outputs through processes that defy simple explanation. Algorithmic accountability requires examination of how results are reached, including transparency and justification of the AI model design, setup, and operation. That level of scrutiny is difficult when the systems themselves are proprietary and commercially sensitive.

The FTC has responded by launching Operation AI Comply, taking action against companies that rely on artificial intelligence to supercharge deceptive or unfair conduct. Actions have targeted companies promoting AI tools that enable fake reviews, businesses making unsupported claims about AI capabilities, and platforms that mislead consumers about how AI systems operate. The message is clear: automation doesn't absolve responsibility. If an AI agent makes false claims, deceptive recommendations, or unfair comparisons, the platform operating that agent is liable.

Bias represents another dimension of the transparency challenge. Research on early AI shopping agents revealed troubling patterns. Agents failed to conduct exhaustive comparisons, instead settling for the first “good enough” option they encountered. This creates what researchers call a “first-proposal bias” that gives response speed a ten to thirty times advantage over actual quality. If an agent evaluates the first few results more thoroughly than later results, merchants have an incentive to ensure their products appear early in whatever databases the agent queries.

Data bias, algorithmic bias, and user bias are the main types of bias in AI e-commerce systems. Data bias occurs when training data isn't representative of actual shopping patterns, leading to recommendations that favour certain demographics, price points, or product categories. Algorithmic bias emerges from how models weigh different factors, potentially overvaluing characteristics that correlate with protected categories. User bias happens when AI agents learn from and amplify existing consumer prejudices rather than challenging them.

The automation bias problem compounds these challenges. People may be unduly trusting of answers from machines which seem neutral or impartial. Many chatbots are effectively built to persuade, designed to answer queries in confident language even when those answers are fictional. The tendency to trust AI output creates vulnerability when that output is shaped by undisclosed commercial incentives or reflects biased training data.

Microsoft recently conducted an experiment where they gave AI agents virtual currency and instructed them to make online purchases. The agents spent all the money on scams. This wasn't a failure of the AI's reasoning capability. It was a failure of the AI's ability to assess trust and legitimacy in an environment designed to deceive. If sophisticated AI systems from a leading technology company can be systematically fooled by online fraud, what does that mean for consumer protection when millions of people delegate purchasing decisions to similar agents?

The Regulatory Response

Regulators worldwide are scrambling to develop frameworks for agentic commerce before it becomes too embedded to govern effectively. New AI-specific laws have emerged to mandate proactive transparency, bias prevention, and consumer disclosures not otherwise required under baseline consumer protection statutes.

The FTC's position emphasises that existing consumer protection laws apply to AI systems. Using artificial intelligence and algorithms doesn't provide exemption from legal obligations around truthfulness, fairness, and non-discrimination. The agency has published guidance stating that AI tools should be transparent, explainable, fair, and empirically sound, whilst fostering accountability.

European regulators are taking a more prescriptive approach through the AI Act, which classifies AI systems by risk level and imposes requirements accordingly. Shopping agents that significantly influence purchasing decisions would likely qualify as high-risk systems, triggering obligations around transparency, human oversight, and impact assessment. The regulation mandates clear disclosure of whether an entity is human or artificial, responding to the increasing sophistication of AI interactions. Under the AI Act's framework, providers of high-risk AI systems must maintain detailed documentation of their training data, conduct conformity assessments before deployment, and implement post-market monitoring to detect emerging risks. Violations can result in fines up to seven per cent of global annual turnover.

But enforcement remains challenging. The opacity of black box models means consumers have no transparency into how exactly decisions are being made. Regulators often lack the technical expertise to evaluate these systems, and by the time they develop that expertise, the technology has evolved. The European Union is establishing an AI Office with dedicated technical staff and budget to build regulatory capacity, whilst the UK is pursuing a sector-specific approach that empowers existing regulators like the Competition and Markets Authority to address AI-related harms in their domains.

The cross-border nature of AI platforms creates additional complications. An AI agent operated by a US company, trained on data from multiple countries, making purchases from international merchants, creates a jurisdictional nightmare. Which country's consumer protection laws apply? Whose privacy regulations govern the data collection? Who has enforcement authority when harm occurs? The fragmentation extends beyond Western democracies. China's Personal Information Protection Law and algorithmic recommendation regulations impose requirements on AI systems operating within its borders, creating a third major regulatory regime that global platforms must navigate.

Industry self-regulation has emerged to fill some gaps. OpenAI and Anthropic developed the Agentic Commerce Protocol, a technical standard for how AI agents should interact with merchant systems. The protocol includes provisions for identifying agent traffic, disclosing commercial relationships, and maintaining transaction records. Google and Amazon rely on separate, incompatible systems, making it difficult for merchants to translate product catalogues into multiple formats.

The question of liability looms large. When an AI agent makes a purchase that the user later regrets, who is responsible? The user who gave the instruction? The platform that operated the agent? The merchant that fulfilled the order? Traditional consumer protection frameworks assume human decision-makers at each step. Agentic commerce distributes decision-making across human-AI interactions in ways that blur lines of responsibility.

The intellectual property dimensions add further complexity. Amazon has sued Perplexity, accusing the startup of violating its terms of service by using AI agents to access the platform without disclosing their automated nature. Amazon argues that Perplexity's agents degrade the Amazon shopping experience by showing products that don't incorporate personalised recommendations and may not reflect the fastest delivery options available. Perplexity counters that since its agent acts on behalf of a human user's direction, the agent automatically has the same permissions as the human user.

This dispute encapsulates the broader regulatory challenge: existing legal frameworks weren't designed for a world where software agents act autonomously on behalf of humans, making decisions, negotiating terms, and executing transactions.

The Power Redistribution

Step back from the technical and regulatory complexities, and agentic commerce reveals itself as fundamentally about power. Power to control the shopping interface. Power to influence purchasing decisions. Power to capture transaction fees. Power to shape which businesses thrive and which wither.

For decades, that power has been distributed across an ecosystem of search engines, social media platforms, e-commerce marketplaces, payment processors, and retailers themselves. Google controlled discovery through search. Facebook controlled attention through social feeds. Amazon controlled transactions through its marketplace. Each entity extracted value from its position in the funnel, and merchants paid tribute at multiple stages to reach customers.

Agentic commerce threatens to consolidate that distributed power into whoever operates the AI agents that consumers trust. If ChatGPT becomes the primary shopping interface for hundreds of millions of users, OpenAI captures influence that currently belongs to Google, Amazon, and every retailer's individual website. The company that mediates between consumer intent and commercial transaction holds extraordinary leverage over the entire economy.

This consolidation is already visible in partnership announcements. When Walmart, Shopify, and Etsy all integrate with ChatGPT within weeks of each other, they're acknowledging that OpenAI has become a gatekeeper they cannot afford to ignore. The partnerships are defensive, ensuring presence on a platform that could otherwise bypass them entirely.

But consolidation isn't inevitable. The market could fragment across multiple AI platforms, each with different strengths, biases, and commercial relationships. Google's AI Mode might excel at product discovery for certain categories. Perplexity's approach might appeal to users who value transparency over convenience. Smaller, specialised agents could emerge for specific verticals like fashion, electronics, or groceries.

The trajectory will depend partly on technical factors: which platforms build the most capable agents, integrate with the most merchants, and create the smoothest user experiences. But it will also depend on trust and regulation. If early AI shopping agents generate high-profile failures, consumer confidence could stall adoption. If regulators impose strict requirements that only the largest platforms can meet, consolidation accelerates.

For consumers, the implications are ambiguous. Agentic commerce promises convenience, efficiency, and potentially better deals through automated comparison and negotiation. Customers arriving via AI agents already demonstrate higher engagement and purchase intent. More than half of consumers anticipate using AI assistants for shopping by the end of 2025. Companies deploying AI shopping agents are delivering thirty per cent more conversions and forty per cent faster order fulfilment.

But those benefits come with risks. Loss of serendipity and discovery as agents optimise narrowly for stated preferences rather than exposing users to unexpected products. Erosion of privacy as more shopping behaviour flows through platforms that profile and monetise user data. Concentration of market power in the hands of a few AI companies that control access to billions of customers. Vulnerability to manipulation if agents' recommendations are influenced by undisclosed commercial arrangements.

Consider a concrete scenario. A parent asks an AI agent to find educational toys for a six-year-old who loves science. The agent might efficiently identify age-appropriate chemistry sets and astronomy kits based on thousands of product reviews and educational research. But if the agent prioritises products from merchants paying higher commissions over genuinely superior options, or if it lacks awareness of recent safety recalls, convenience becomes a liability. The parent saves time but potentially compromises on quality or safety in ways they would have caught through traditional research.

Marketplace or Manipulation

Agentic commerce is not a future possibility. It is a present reality growing at exponential rates. The question is not whether AI shopping agents will reshape retail, but how that reshaping will unfold and who will benefit from the transformation.

The optimistic scenario involves healthy competition between multiple AI platforms, strong transparency requirements that help users understand recommendation incentives, effective regulation that prevents the worst abuses whilst allowing innovation, and merchants who adapt by focusing on brand building, product quality, and authentic relationships.

In this scenario, consumers enjoy unprecedented convenience and potentially lower prices through automated comparison shopping. Merchants reach highly qualified customers with strong purchase intent. AI platforms create genuine value by reducing friction and improving matching between needs and products. Regulators establish guardrails that prevent manipulation whilst allowing experimentation. Picture a marketplace where an AI agent negotiates bulk discounts on behalf of a neighbourhood buying group, secures better warranty terms through automated comparison of coverage options, and flags counterfeit products by cross-referencing manufacturer databases, all whilst maintaining transparent logs of its decision-making process that users can audit.

The pessimistic scenario involves consolidation around one or two dominant AI platforms that extract monopoly rents, opaque algorithms shaped by undisclosed commercial relationships that systematically favour paying merchants over best products, regulatory capture or inadequacy that allows harmful practices to persist, and a race to the bottom on merchant margins that destroys business viability for all but the largest players.

In this scenario, consumers face an illusion of choice backed by recommendations shaped more by who pays the AI platform than by genuine product quality. Merchants become commodity suppliers in a system they can't influence without paying increasing fees. AI platforms accumulate extraordinary power and profit through their gatekeeper position. Imagine a future where small businesses cannot afford the fees to appear in AI agent recommendations, where platforms subtly steer purchases toward their own private-label products, and where consumers have no practical way to verify whether they're receiving genuinely optimal recommendations or algorithmically optimised profit extraction.

Reality will likely fall somewhere between these extremes. Some markets will consolidate whilst others fragment. Some AI platforms will maintain rigorous standards whilst others cut corners. Some regulators will successfully enforce transparency whilst others lack resources or authority. The outcome will be determined by choices made over the next few years by technology companies, policymakers, merchants, and consumers themselves.

The Stakeholder Reckoning

For technology companies building AI shopping agents, the critical choice is whether to prioritise short-term revenue maximisation through opaque commercial relationships or long-term trust building through transparency and user alignment. The companies that choose trust will likely capture sustainable competitive advantage as consumers grow more sophisticated about evaluating AI recommendations.

For policymakers, the challenge is crafting regulation that protects consumers without stifling the genuine benefits that agentic commerce can provide. Disclosure requirements, bias auditing, interoperability standards, and clear liability frameworks can establish baseline guardrails without prescribing specific technological approaches. The most effective regulatory strategies will focus on outcomes rather than methods: requiring transparency in how recommendations are generated, mandating disclosure of commercial relationships that influence agent behaviour, establishing accountability when AI systems cause consumer harm, and creating mechanisms for independent auditing of algorithmic decision-making. Policymakers must act quickly enough to prevent entrenchment of harmful practices but thoughtfully enough to avoid crushing innovation that could genuinely benefit consumers.

For merchants, adaptation means shifting from optimising for human eyeballs to optimising for algorithmic evaluation and human trust simultaneously. The retailers that will thrive are those that maintain compelling brands, deliver genuine value, and build direct relationships with customers that no AI intermediary can fully replace. This requires investment in product quality, authentic customer service, and brand building that goes beyond algorithmic gaming. Merchants who compete solely on price or visibility in AI agent recommendations will find themselves in a race to the bottom. Those who create products worth recommending and brands worth trusting will discover that AI agents amplify quality rather than obscuring it.

For consumers, the imperative is developing critical literacy about how AI shopping agents work, what incentives shape their recommendations, and when to trust algorithmic suggestions versus conducting independent research. Blind delegation is dangerous. Thoughtful use of AI as a tool for information gathering and comparison, combined with final human judgment, represents the responsible approach. This means asking questions about how agents generate recommendations, understanding what commercial relationships might influence those recommendations, and maintaining the habit of spot-checking AI suggestions against independent sources. Consumer demand for transparency can shape how these systems develop, but only if consumers actively seek that transparency rather than passively accepting algorithmic guidance.

Who Controls the Algorithm Controls Commerce

The fundamental question agentic commerce poses is who gets to shape the marketplace of the future. Will it be the AI platforms that control the interface? The merchants with the deepest pockets to pay for visibility? The regulators writing the rules? Or the consumers whose aggregate choices ultimately determine what succeeds?

The answer is all of the above, in complex interaction. But that interaction will produce very different outcomes depending on the balance of power. If consumers remain informed and engaged, if regulators act decisively to require transparency, if merchants compete on quality rather than just algorithmic gaming, and if AI platforms choose sustainable trust over exploitative extraction, then agentic commerce could genuinely improve how billions of people meet their needs.

If those conditions don't hold, we're building a shopping future where the invisible hand of the market gets replaced by the invisible hand of the algorithm, and where that algorithm serves the highest bidder rather than the human asking for help. The stakes are not just commercial. They're about what kind of economy we want to inhabit: one where technology amplifies human agency or one where it substitutes algorithmic optimisation for human choice.

The reshape is already underway. The revenue is already flowing through new channels. The questions about trust and transparency are already urgent. What happens next depends on decisions being made right now, in boardrooms and regulatory offices and user interfaces, about how to build the infrastructure of algorithmic commerce. Get those decisions right and we might create something genuinely better than what came before. Get them wrong and we'll spend decades untangling the consequences.

The invisible hand of AI is reaching for your wallet. The question is whether you'll notice before it's already spent your money.

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Sources and References

1. McKinsey & Company (2025). “The agentic commerce opportunity: How AI agents are ushering in a new era for consumers and merchants.” McKinsey QuantumBlack Insights.

2. Boston Consulting Group (2025). “Agentic Commerce is Redefining Retail: How to Respond.” BCG Publications.

3. Opera Software (March 2025). “Opera becomes the first major browser with AI-based agentic browsing.” Opera Newsroom Press Release.

4. Opera Software (May 2025). “Meet Opera Neon, the new AI agentic browser.” Opera News Blog.

5. Digital Commerce 360 (October 2025). “McKinsey forecasts up to $5 trillion in agentic commerce sales by 2030.”

6. TechCrunch (September 2025). “OpenAI takes on Google, Amazon with new agentic shopping system.”

7. TechCrunch (March 2025). “Opera announces a new agentic feature for its browser.”

8. PYMNTS.com (2025). “Agentic AI Is Quietly Reshaping the eCommerce Funnel.”

9. Retail Brew (October 2025). “AI agents are becoming a major e-commerce channel. Will retailers beat them or join them?”

10. eMarketer (2025). “As consumers turn to AI for shopping, affiliate marketing is forging its own path.”

11. Retail TouchPoints (2025). “Agentic Commerce Meets Retail ROI: How the Affiliate Model Powers the Future of AI-Led Shopping.”

12. Federal Trade Commission (2023). “The Luring Test: AI and the engineering of consumer trust.”

13. Federal Trade Commission (2025). “AI and the Risk of Consumer Harm.”

14. Federal Trade Commission (2024). “FTC Announces Crackdown on Deceptive AI Claims and Schemes.”

15. Bloomberg (November 2025). “Amazon Demands Perplexity Stop AI Tool's Purchasing Ability.”

16. CNBC (November 2025). “Perplexity AI accuses Amazon of bullying with legal threat over Comet browser.”

17. Retail Dive (November 2025). “Amazon sues Perplexity over AI shopping agents.”

18. Criteo (2025). “Retail media in the agentic era.”

19. Bizcommunity (2025). “Retail media: Agentic AI commerce arrives, estimated value of $136bn in 2025.”

20. The Drum (June 2025). “How AI is already innovating retail media's next phase.”

21. Brookings Institution (2024). “Algorithmic bias detection and mitigation: Best practices and policies to reduce consumer harms.”

22. Lawfare Media (2024). “Are Existing Consumer Protections Enough for AI?”

23. The Regulatory Review (2025). “A Modern Consumer Bill of Rights in the Age of AI.”

24. Decrypt (November 2025). “Microsoft Gave AI Agents Fake Money to Buy Things Online. They Spent It All on Scams.”

25. Mastercard (April 2025). “Mastercard unveils Agent Pay, pioneering agentic payments technology to power commerce in the age of AI.”

26. Payments Dive (2025). “Visa, Mastercard race to agentic AI commerce.”

27. Fortune (October 2025). “Walmart's deal with ChatGPT should worry every ecommerce small business.”

28. Harvard Business Review (February 2025). “AI Agents Are Changing How People Shop. Here's What That Means for Brands.”

29. Adweek (2025). “AI Shopping Is Here but Brands and Retailers Are Still on the Sidelines.”

30. Klaviyo Blog (2025). “AI Shopping: 6 Ways Brands Can Adapt Their Online Presence.”

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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: * And a very satisfying Wednesday draws close to its end. With Gregorian Chant playing softly in the background I'm finishing my night prayers. After that, some quiet reading will take me to bedtime.

Prayers, etc.: * My daily prayers

Health Metrics: * bw= 222.78 lbs. * bp= 142/81 (66)

Exercise: * kegel pelvic floor exercise, half squats, calf raises, wall push-ups

Diet: * 06:30 – 1 peanut butter sandwich * 07:25 – fried rice with shrimp, chicken, and meat * 10:00 – 1 fresh orange * 11:30 – rice based casserole cooked with different meats and vegetables

Activities, Chores, etc.: * 04:30 – listen to local news talk radio * 05:50 – bank accounts activity monitored * 05:55 – read, pray, listen to news reports from various sources * 13:00 to 15:00 – watch old game shows with Sylvia * 16:30 – listening to the pregame show ahead of tonight's NCAA women's basketball game when the Western Michigan Broncos travel to Bloomington, Indiana to face the Indiana Hoosiers. I'll stay with this station for the radio call of the game. * 18:35 – After a satisfying win (Lady Hoosiers 71 – Western Michigan 53) my plans now are to listen to relaxing music, do my night prayers, and quietly read until bedtime.

Chess: * 15:45 – moved in all pending CC games

By L. Moraitis

A republic lives or dies by the courage of its citizens. Constitutions can formalize powers, balance institutions, and distribute authority, but no constitutional structure can compensate for a population that has forgotten how to deliberate in public without fear. The mixed constitution—Aristotle’s balanced polity, Polybius’s Roman model, Montesquieu’s separation of powers—was never merely a diagram of institutions. It was a training ground for fearless civic character. Its purpose was to produce not simply order, but citizens capable of sustaining liberty through disciplined courage.

Fearless deliberation is the antidote to two perennial dangers: the tyranny of the few and the volatility of the many. Monarchs and oligarchs thrive when public speech is timid, when dissent becomes a private whisper. Pure democracies decay when citizens abandon reason for passion and noise. The mixed constitution counters both dangers by institutionalizing conflict within bounds: executives check assemblies, aristocracies check demagogues, the people check corruption. But these checks function only when citizens are willing to speak boldly, criticize power openly, and confront each other’s arguments without retreating into tribal comfort.

In this sense, the mixed constitution is masculinist in its metaphor: it demands civic toughness, not in the biological or gendered sense, but in the classical sense of virtus, andreia—virtue understood as capacity for public risk. Courage is not merely a military virtue; it is the willingness to stand unarmed in the public square and give reasons. This was the core insight of both the Athenian assembly and the Roman senate. A polity in which citizens fear reputational destruction, legal retaliation, or social ostracism for speaking honestly cannot deliberate; and where deliberation fails, the mixed constitution collapses into either factional war or administrative despotism.

Mixed constitutions restrain power precisely to create space for fearless speech. When no single faction can dominate, citizens can express disagreement without immediate danger. When power is divided, truth-telling becomes possible; when power is monopolized, even truth whispered becomes perilous. Thus, the structure of the constitution serves the virtue of the citizen, and the virtue of the citizen sustains the structure.

The republic of the unafraid is not a society without conflict. It is a society where conflict is public, principled, and bounded—the crucible in which rational self-rule is forged. Fearless deliberation is not the ornament of a free society; it is the price of admission.