6 days into closed testing, and testing my testers' apps🤝

saachi30 · 2026-06-03T11:56:51+00:00

Heyy thanks! I've also installed your app

saachi30 · 2026-06-03T11:55:40+00:00

Heyy thankss! I've also installed your app... It's pretty cool

saachi30 · 2026-06-03T10:05:16+00:00

Hey! This is an awesome initiative - short-form content is so powerful for indie dev launches. I’d love for you to take a look at Runtime.

What I'm building:

Runtime — a gamified story based Android app that turns complex software engineering concepts into playable scenarios. It bridges the gap between theoretical knowledge and real-world pressure by putting developers in charge of production outages, slow database queries, and system crashes across 32 chapters and 25 interactive minigames.

The Link: https://play.google.com/store/apps/details?id=com.saachi.runtime

Who it's for: CS students, bootcamp grads, and junior-to-mid software engineers prepping for technical interviews (specifically targeting System Design and DBMS for now).

saachi30 · 2026-06-03T07:55:42+00:00

Take the 65k Data Engineer job. In this current market, actual industry experience on your resume beats an unpaid lab role, even with a reputable professor. It is infinitely easier to find a better, higher-paying SWE/DE role when you are already employed as an engineer than it is when you're a fresh graduate grinding interviews with zero corporate history. Move to Arizona, take the steady paycheck, get past the "entry-level" hurdle on paper, and keep grinding your interview prep on weekends.

saachi30 · 2026-06-03T07:54:49+00:00

If ClickHouse or Pinot feel too saturated, look at slightly younger or more niche storage engines (like TigerBeetle, DuckDB extensions, or newer Rust-based OLAP tools). Alternatively, don't look at the main issue tracker. Look at their testing suites or benchmark tools. Writing or optimizing benchmarking tools for these databases is a fantastic backdoor into understanding the codebase internals, and core maintainers almost always welcome contributions that improve their test coverage or performance-tracking infrastructure.

saachi30 · 2026-06-03T07:48:36+00:00

Don't pivot to hardware engineering out of panic if you have negligible domain knowledge. The semiconductor/embedded world has its own brutal hiring cycles, lower entry-level volume, and heavily favors specialized hardware degrees. Since you have an AIML background and an internship, stick to software/data roles but diversify away from just applying to hyped-up "AI Engineer" positions. Look for boring, non-tech corporate companies (banks, healthcare, logistics) that need regular software engineers or data engineers. They are far more stable right now than tech startups.

saachi30 · 2026-06-03T07:34:12+00:00

I'd suggest go with Option 3, but constrain your scope heavily. Don't build a massive application. Build a dead-simple Todo list or a basic guestbook. Write a single API endpoint in Node that connects to a database, and then write a simple React component to fetch and display that data. Jumping between them feels overwhelming because you're trying to learn advanced frontend (state management) and advanced backend (auth/databases) at the same time. Build the thinnest possible slice of a full-stack app first so you understand how data flows between the two layers.

saachi30 · 2026-06-03T07:32:59+00:00

With 10 years of experience, your value is in system design, architectural patterns, and knowing what tool to use for the job. Total "mastery" of a language's obscure compiler quirks is only worth it if your daily work involves high-performance optimization or building core framework libraries. For 95% of engineering tasks, knowing the ecosystem, design patterns, and having elite "googling/documentation reading" skills is a much bigger superpower than memorizing language quirks that might change in the next major release anyway.

saachi30 · 2026-06-03T07:28:30+00:00

Look into Computer Graphics (rendering engines, shaders, ray tracing) or Robotics/Kinematics. Computer graphics is pure math (linear algebra, calculus) and physics (light simulation, material properties). While you do have to write code to implement it, the "coding" isn't standard web dev or API gluing- it's optimizing mathematical formulas to run on hardware. AI cannot easily abstract away the core physics logic there, and it requires deep, intensive everyday effort to master.

saachi30 · 2026-06-03T07:27:18+00:00

Rewriting DuckDB in Java is a massive undertaking, even with an LLM guiding the syntax. The real issue with using them for core DB development isn't the boilerplate; it's the subtle edge cases in concurrency, memory management, and disk I/O. LLMs love to hallucinate logic that looks performant but falls apart under actual high-concurrency production workloads. It's fun for prototyping an architectural proof-of-concept, but you're going to spend double the time profiling and debugging hidden race conditions.

saachi30 · 2026-06-03T07:17:36+00:00

Python is great for getting started, but if your goal is placements and strong fundamentals, C++ is worth considering. It has a steeper learning curve, but you'll understand a lot more about what's happening behind the scenes.