DEV Community: Aneesh Lade

Week 2

Aneesh Lade — Thu, 04 Jun 2026 21:03:13 +0000

Hello everyone! It has been a busy week, but I've made some exciting progress on my machine learning journey. Here is what I've been up to:

Kaggle Orbit Wars & AWS

I completed the baseline implementation for the Kaggle Orbit Wars competition and initially hit a score of around 1030. My score has dipped slightly over the past few days, so I am currently brainstorming ways to improve it.

This week also marked my very first time using AWS! I used it to extract data for reinforcement learning. Transparency check: I spent exactly $7.58 USD on AWS resources during the process.

Paper Reading & RL Insights

I spent a lot of time reading research papers this week.

AlphaZero: I was initially excited about using the self-play mechanism from AlphaZero. However, because this specific game has rock-paper-scissors dynamics, standard self-play might not work effectively.
AlphaStar: This led me to the AlphaStar paper, which uses self-play combined with League Training.

The engineering behind AlphaStar is incredible. Two specific concepts really stood out to me: Pointer Networks and V-trace off-policy correction. I was also impressed by their use of an LSTM core to handle long-term memory.

Next Steps

Moving forward, I plan to leverage Kaggle, AWS, and GCP credits to train different components of my model. I am giving myself total freedom to experiment, imagine, and test unconventional solutions.

Random life update to close out the week: I used to have long hair because I was insecure about my forehead, but I finally decided to shave it all off at home by myself. It honestly feels really weird right now, but it's a fresh start!

Week 1

Aneesh Lade — Wed, 27 May 2026 17:20:41 +0000

Hi everyone! It’s been a week since my first post.

In this past week, I’ve read through research papers on AlphaZero, AlphaGo and many interesting research papers. I have also started implementing my strategy for the Kaggle Orbit Wars competition.

On top of that, I landed an internship at a startup! My work will focus on MCP (Model Context Protocol), learning and understanding how it works, and implementing it so it can interface with LLMs and a custom simulator they’ve built.

Looking ahead to next week, I have two main goals:

Kaggle Orbit Wars: Complete a baseline for the strategy I've decided on.
Internship: Dive seriously into my new role. The team mentioned that this is a relatively new topic, so if we do good work, there’s a chance we might publish a paper. That’s one of the main reasons I'm so excited!

Hello World

Aneesh Lade — Wed, 20 May 2026 16:28:34 +0000

Hey everyone, I'm Aneesh.

Today, I’m launching this developer log as a personal accountability challenge. From this week onward, I am committing to publishing at least one technical post every single week (and more than that if I run into breakthroughs or major roadblocks worth sharing).

My goal is to document the raw, unfiltered engineering journey, the bugs, the design choices, the math derivations, and the late-night simulation wins.

What I'm Building: Kaggle Orbit Wars

Right now, my primary focus is the Kaggle Orbit Wars simulation challenge. It's a brutal 2D real-time strategy environment where you have to conquer rotating planets, navigate gravitational paths around a central sun, and optimize fleet trajectories. With about a month left until the final submission deadline in June, I am aggressively iterating on my agent's state estimation and decision-making logic.

What I'm Learning: UC Berkeley's CS 285

To back up my practical work with deep theoretical foundations, I am currently working through UC Berkeley's CS 285 (Deep Reinforcement Learning) course. Shifting from hard-coded heuristics to understanding advanced policy gradients, Q-learning value functions, and model-based RL is completely reshaping how I think about designing autonomous agents.

Why I'm Doing This

I'm skipping the corporate noise of traditional social media. This space is going to be my open-source lab notebook. If you are also grinding through Orbit Wars, studying RL, or building autonomous systems, follow along or drop a comment—let's build together.

See you next week for the first deep-dive update!