You're killing your brain between prompts.
With agentic coding your brain already does less. You're not writing the code, you're reviewing structure and making architecture calls, and even those you brainstorm with the agent. An MIT EEG study confirmed it: the more the AI does, the less your brain engages.
And what do we fill that downtime with? Reels and tiktok. Scrolling short-form videos in that gap is becoming the normal thing to do. We barely notice it, but it slowly hurts our performance and hides what we could do with that time.
Two things fixed this for me.
1. The weekends-only rule. No insta, no yt shorts on weekdays, apps uninstalled. Any long-form video is fine, entertainment, podcasts, whatever. Preferably content that doesn't ask much of your focus, because that spends your focus too.
Everything comes back on weekends. You can't quit shorts completely (I couldn't), it's a source of info and entertainment as well. So don't quit, schedule.
3rd month on this rule and my focus is the best it's been.
2. Parallel projects. Takes some adjusting at first, but run multiple projects at once. I do 4-5 sometimes. While one agent works you switch to the next project, so there's no dead time to get pulled into a feed. I'll share the tools that made parallel sessions work for me (orca, herdr) in another post. But you can add claude notifications to whatever setup you have today, wrote about that here.
We can take on more work than we think. Instead of scrolling between prompts, say yes to that additional opportunity and fill that time with real work.
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Python allows you to create enumerations that are also regular strings!
Previously, when working with APIs, JSON, and configurations, it was often necessary to manually extract the value from an Enum.
For example:
class Status(Enum):
ACTIVE = "active"
When serializing, you would get an enumeration object:
Status.ACTIVE
rather than a regular string:
"active"
In Python 3.11, StrEnum was introduced to solve this problem.
from enum import StrEnum
class Status(StrEnum):
ACTIVE = "active"
BLOCKED = "blocked"
Now, the value can be used wherever a string is expected:
json.dumps({"status": Status.ACTIVE})
The result:
{"status": "active"}
At the same time, the advantages of enumerations are preserved:
Status.ACTIVE
Status.BLOCKED
You cannot accidentally pass an incorrect value:
Status("unknown")
will result in an error.
🔥 StrEnum allows you to combine the strict typing of enumerations with the convenience of regular strings, without manual conversion when working with APIs, JSON, and configurations
🎨 AU Logo Design Competition 2027
The African Union invites young African creatives aged 18–24 to design the official logo and visual identity for the AU Theme of the Year 2027.
🏆 1st: $5,000 | 2nd: $2,000 | 3rd: $1,000
📅 Deadline: October 23, 2026, 11:59 PM EAT
🌍 Open to citizens of all AU Member States
🎨 No formal design qualification required.
🔗 Guidelines & Submission: https://au.int/en/newsevents/20260829/call-entries-calling-young-african-creatives-logo-competition-au-theme-year
#AfricanYouth #Youth #Agenda2063
@OPPsphere
"How to Train a Neural Network" is a concise summary of the MIT course lectures on deep learning from 2024. It focuses on one of the fundamental questions in neural networks: how a model learns its weights.
The summary examines the training process from a mathematical perspective. It covers topics such as forward propagation, loss functions, gradients, backpropagation, and gradient-based optimization methods.
I believe this is an interesting resource for those who want to go beyond a general, intuitive understanding of neural networks and begin to delve into the mathematics that underlies their training.
https://ocw.mit.edu/courses/6-7960-deep-learning-fall-2024/mit6_7960_f24_lec2.pdfhttps://t.me/CodeProgrammer 🤩