I'm Trying to Get Better at Everything (and Accidentally Building another IoT Network at the same time)
I don’t really know where I’m going in tech yet — and for a while, that bothered me.
There are so many different paths: backend engineering, embedded systems, web development, networking… and it feels like everyone else has already picked a lane. I’m trying to see that as a strength rather than a weakness.
Instead of specialising too early, I’ve been focusing on getting better at as many areas as I can. Not in a scattered way, but by building things, testing them and testing myself as I go.
One of the best examples of that mindset has been my recent dive into IoT.
How I've Ended Up Building another IoT System
Someone told me about their business idea and it involves IOT which was a big part of my course at Hallam University so I told him that I'm probably the ideal person to build him a prototype IoT system that he can present to his potential funders. He knows more about that side of things so I can watch and learn things from him as well.
Before I knew it, I was back experimenting with my Raspberry Pi as the centre of my own small network. Not just sending data, but thinking about the full pipeline — how data is collected, transmitted, processed, and stored.
That’s when things started to click for me.
Where All the Different Skills Started Connecting
What surprised me most was how all the different things I’d been learning suddenly became useful at the same time.
Python became the glue that held everything together. I used it to handle incoming data, write scripts, and build backend services. It’s the language I keep coming back to whenever I need to make something actually work.
FastAPI gave me a way to turn that functionality into something structured — an API that could receive data from devices and expose it cleanly. It made the system feel more real, like something that could actually scale beyond a small experiment.
That naturally led into thinking about microservices. Instead of one big application, I started imagining separate components: one for data ingestion, one for processing, one for storage. I’m still early in this, but it’s changing how I think about system design.
On the hardware side, working with low-power communication and constrained devices pushed me toward learning more C++. It’s definitely more challenging, but it’s helping me understand what’s actually happening beneath the surface — especially when performance and efficiency matter. Long term I would love to get into embedded systems and C++ is must for that kind of thing.
Then there’s the data itself. Storing it properly led me into PostgreSQL, where I’ve been learning how to structure and query data in a way that actually makes sense long-term. It’s one thing to collect data — it’s another to make it useful.
And of course, none of this exists in isolation. I’ve also been learning front end development so I can actually visualise the data I’m collecting. Even a simple interface makes a huge difference — it turns raw numbers into something you can understand at a glance.
Side Quests That Turned Out to Be Useful
Even things that felt unrelated at first have ended up being useful. Web scraping, for example, started as a way to experiment with Python and automation. But it’s helped me understand how data is structured on the web, how to extract it, and how messy real-world data can be.
That same mindset applies to everything I’ve been learning — nothing is really wasted. It all connects eventually.
What I’m Starting to Realise
I used to think I needed to pick a direction and commit to it as early as possible. Now I’m starting to think the opposite might be the right move for me at the moment.
By exploring different areas: software, hardware, networking, data , I’m not just learning isolated skills. I’m learning how systems fit together. And that feels a lot more valuable than specialising too early in something I might not even enjoy long-term.
I still don’t know exactly where I’ll end up. But I do know this: I’m getting better at building things, understanding systems, and figuring stuff out as I go.
For now, that’s enough.
What surprised me most was how all the different things I’d been learning suddenly became useful at the same time.
Python became the glue that held everything together. I used it to handle incoming data, write scripts, and build backend services. It’s the language I keep coming back to whenever I need to make something actually work.
FastAPI gave me a way to turn that functionality into something structured — an API that could receive data from devices and expose it cleanly. It made the system feel more real, like something that could actually scale beyond a small experiment.
That naturally led into thinking about microservices. Instead of one big application, I started imagining separate components: one for data ingestion, one for processing, one for storage. I’m still early in this, but it’s changing how I think about system design.
On the hardware side, working with low-power communication and constrained devices pushed me toward learning more C++. It’s definitely more challenging, but it’s helping me understand what’s actually happening beneath the surface — especially when performance and efficiency matter. Long term I would love to get into embedded systems and C++ is must for that kind of thing.
Then there’s the data itself. Storing it properly led me into PostgreSQL, where I’ve been learning how to structure and query data in a way that actually makes sense long-term. It’s one thing to collect data — it’s another to make it useful.
And of course, none of this exists in isolation. I’ve also been learning front end development so I can actually visualise the data I’m collecting. Even a simple interface makes a huge difference — it turns raw numbers into something you can understand at a glance.
Side Quests That Turned Out to Be Useful
Even things that felt unrelated at first have ended up being useful. Web scraping, for example, started as a way to experiment with Python and automation. But it’s helped me understand how data is structured on the web, how to extract it, and how messy real-world data can be.
That same mindset applies to everything I’ve been learning — nothing is really wasted. It all connects eventually.
What I’m Starting to Realise
I used to think I needed to pick a direction and commit to it as early as possible. Now I’m starting to think the opposite might be the right move for me at the moment.
By exploring different areas: software, hardware, networking, data , I’m not just learning isolated skills. I’m learning how systems fit together. And that feels a lot more valuable than specialising too early in something I might not even enjoy long-term.
I still don’t know exactly where I’ll end up. But I do know this: I’m getting better at building things, understanding systems, and figuring stuff out as I go.
For now, that’s enough.
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