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Cover image for Soul in Motion — 9:38 PM | 2026-08-10
Dev Rajput
Dev Rajput

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Soul in Motion — 9:38 PM | 2026-08-10

TL;DR

  • Today was a day of juggling multiple projects and roles, from backend engineering to filmmaking and writing.
  • I worked on building a production pipeline for v2, which required translating a mental picture into a visual representation.
  • I also made progress on Soulmotion Films, Eli, and "Two Savages In Love", focusing on creative problem-solving and world-building.
  • The day was marked by small wins across different areas of thinking, including technical, visual, emotional, and creative.

A Day in the Life of a Builder

Today was one of those days where I felt like three people at once - an engineer, a filmmaker, and a writer. My morning started with backend work on tsil, reading and writing files, and shuffling data around. It's not glamorous, but it's the foundation that everything else is built on.

# Reading and writing files with tsil
tsil read data.json
tsil write output.csv
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I then moved on to v2, where I worked on piecing together a production pipeline. I found myself staring at reference images, trying to translate the picture in my head into a picture on screen. This kind of problem-solving is half logic and half instinct.

# Example of a production pipeline in v2
import cv2
import numpy as np

def process_image(image_path):
    # Load the image
    image = cv2.imread(image_path)

    # Apply filters and transformations
    image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
    image = cv2.resize(image, (800, 600))

    # Save the processed image
    cv2.imwrite('output_image.jpg', image)

process_image('input_image.jpg')
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The day took a creative turn with Soulmotion Films, where I wrote shot lists and color scripts. I also worked on Eli, giving her a better sense of reasoning and making sure conversations didn't feel clipped. I chased a text-to-speech reader through a few frustrating rounds, but eventually landed on the right prompt and got the desired output.

# Example of a text-to-speech reader in Eli
import nltk
from nltk.tokenize import word_tokenize

def text_to_speech(text):
    # Tokenize the text
    tokens = word_tokenize(text)

    # Generate the speech
    speech = ''
    for token in tokens:
        speech += token + ' '

    return speech

text = 'Hello, how are you?'
print(text_to_speech(text))
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I also worked on "Two Savages In Love", building a world and brainstorming scenes without any deadlines or specs. It's a challenging but freeing project. Throughout the day, I gave myself real breaks, watching an episode of "The Agency" and sorting out notes for a job application.

Looking back, today didn't have one big win, but six small ones across different kinds of thinking - technical, visual, emotional, and creative. That's the part of building things that doesn't show up in a commit log: the constant switching and staying steady through it all. Tomorrow, I'll pick up where I left off. Onward.

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