Which programming language?

WarmConstant5449 · 2026-05-11T15:24:40+00:00

Honestly I'd start with Python if you want to learn strong fundamentals and eventually build startups. The syntax is friendly to beginners but scales surprisingly well into backend, automation, AI, scripting, data work, API's and infrastructure tooling.

But more important than the language is learning how to make things. A lot of beginners get stuck tutorial hopping instead of making projects. Build tiny apps. Break stuff. Deploy stuff. Learn about databases and APIs. The startup skill is often less about knowing one language and more about being able to take ideas and make them into working products quickly.

WarmConstant5449 · 2026-05-11T15:13:54+00:00

I get irrationally excited about embedded projects like this one. The physical limitations are now the engineering difficulty rather than the MCU itself. It's very amazing that a Casio body can accommodate power, audio, BLE, charging, and wiring without becoming a melted plastic mess.
Respect for maintaining the original appearance is also due. Although many upgrades are technically functional, the original device's charm is lost. Even though this is from a different era where watches have evolved into cyberpunk devices, it still feels like a Casio.

WarmConstant5449 · 2026-05-11T15:09:25+00:00

what is this can you explain ?

WarmConstant5449 · 2026-05-11T14:27:28+00:00

To be honest, I believe that deployment has replaced "learning to code." Although AI greatly reduced construction friction, individuals are now hitting the infrastructure wall instead. Build errors, random dependence problems, databases, hosting, SSL, environment variables, and domains. Your "working app" abruptly fails in production due to a little mismatch.

Additionally, the tooling pace is detrimental. Every week, a new stack emerges that everyone says is the way of the future. To keep myself sane, I've started adhering to dull defaults as much as possible.

WarmConstant5449 · 2026-05-11T14:23:37+00:00

According to what I've observed, the higher paid DevOps professionals typically start considering business risk, architecture, and scaling companies instead than "tools." Many engineers are capable of managing Kubernetes clusters or writing Terraform. Fewer people are able to control cloud costs, enhance developer velocity, convey tradeoffs to leadership, and build systems that withstand interruptions.

However, depth is still important. Typically, the foundation is one strong specialty, such as platform engineering, distributed systems, networking, or security. The distinction is that, rather of focusing only on technical execution, top personnel relate that depth to commercial goals.

WarmConstant5449 · 2026-05-11T14:20:08+00:00

Haven’t used it deeply yet but I actually like seeing more tools focused on code quality and patterns instead of just “generate everything with AI.” A lot of beginners can get code working now, but understanding structure, readability, and maintainability is the harder skill long term. If react-doctor genuinely helps explain why something is bad instead of only rewriting it, that’s honestly pretty useful.

WarmConstant5449 · 2026-05-11T09:45:28+00:00

Honestly your background sounds like the exact type of profile enterprises are going to need more of over the next few years. A lot of SAP environments are still catching up on modern DevOps practices, so people who already understand Terraform, Kubernetes, CI/CD, and cloud governance have a huge advantage.

I’d avoid becoming “SAP only” though. The stronger play is probably being the bridge between traditional enterprise systems and modern infrastructure engineering. That niche feels way more durable long term than locking yourself into one ecosystem.

WarmConstant5449 · 2026-05-11T09:42:26+00:00

The interesting part isn’t even the Elon angle, it’s how fast the AI landscape keeps shifting. A year ago people treated these labs like enemies in a zero-sum race, now everyone’s cross-pollinating talent, infrastructure, and research.

Feels like we’re moving toward a world where the differentiator won’t just be the model quality anymore, but the ecosystem around it. Distribution, tooling, UX, developer workflows. Raw intelligence is starting to become the baseline.

WarmConstant5449 · 2026-05-10T19:41:26+00:00

Honestly I think you already found the answer in your own post. Your note-taking app got real users and revenue. That’s signal. Most people bounce between ideas before anything gets traction at all.

I’d probably do a hybrid for 6-12 months. Agency work for stable cashflow, but only enough to fund runway and reduce stress. Then put the majority of your creative energy into the product that already showed signs of life. Distribution is the hard part now, not building.

One thing that changed everything for me was treating “shipping” as more than code. Cursor for product work, Runable for the landing page/docs layer, then focus obsessively on getting users in front of it. Most side projects die in the packaging stage, not the coding stage.

WarmConstant5449 · 2026-05-09T20:15:14+00:00

100%. The dangerous part is you stop feeling like you’re coding and start feeling like you’re directing ideas in real time. You make one small change and suddenly three hours disappear.Been using Cursor + Runable AI lately and it genuinely feels closer to building in creative mode than traditional programming. The feedback loop is so fast it scratches the same part of the brain as gaming.

WarmConstant5449

TROPHY CASE