If you ask ten developers which programming language you should use, you'll get eleven opinions and at least two arguments. It's one of the most tribal topics in technology, which is a shame, because for most real projects the honest answer is calm, practical, and a little boring: it depends on what you're building, who's building it, and what it has to do for the next five years.
A programming language isn't a religion or a personality. It's a tool. And like any tool, the right one is the one that fits the job, the people holding it, and the conditions you'll work in.
Here's how we think it through with clients who are about to commission a build, without getting dragged into the holy wars.
Start with the job, not the language
Before any language gets named, we get clear on what the software actually has to be. The same questions, every time:
- What kind of thing is it? A website, a phone app, an internal business tool, a data pipeline, an automation script, an integration between two systems?
- Where does it run? In a browser, on a server, on a phone, on a piece of hardware?
- How long does it need to live? A quick internal helper, or a system you'll depend on and extend for a decade?
- Who will maintain it? Your in-house team, a partner, or whoever you can find to hire later?
- What does it talk to? Existing systems, databases, and tools often pull the decision in a particular direction.
Notice that none of those is "which language is fastest" or "which is trending." Those come last, if at all.
A field guide to the usual suspects
You don't need to know fifty languages. A handful covers the overwhelming majority of business software, and each has a lane it's genuinely good in.
JavaScript / TypeScript
The language of the web, full stop. If it runs in a browser, JavaScript is involved. With Node.js it runs on the server too, so one team can build front and back end in one language. TypeScript adds a safety net that catches whole classes of mistakes before they ship, for anything beyond a toy, prefer it. Reach for it when you're building interactive websites and web apps. (It's what powers this very site.)
Python
The friendly generalist. Easy to read, fast to write, and the undisputed home of data, analytics, automation and AI/machine learning. If your project involves crunching data, scripting repetitive work, or anything AI-flavoured, Python is usually the path of least resistance. Reach for it for data work, automation, AI, and back-end services where developer speed matters more than raw performance.
C# and .NET
Microsoft's workhorse, robust, well-tooled, and a natural fit if your world is Windows, SQL Server and modern BI tooling. Excellent for serious business applications, internal line-of-business systems, and APIs that need to be dependable for years. Reach for it when you're invested in the Microsoft ecosystem and want enterprise-grade stability.
Java
The veteran that runs an enormous amount of the corporate world. Verbose but extraordinarily stable, scalable and hire-able, with a vast ecosystem. Reach for it for large, long-lived enterprise systems and Android apps where a deep talent pool matters.
Go (and friends like Rust)
The specialists for performance and scale. Go is simple and brilliant at fast, concurrent network services and infrastructure tooling. Rust trades some ease for memory safety and raw speed where every millisecond counts. Reach for these when high-throughput performance is the actual problem you're solving, not before.
Mobile: Swift, Kotlin, and cross-platform
Native iOS leans on Swift, native Android on Kotlin. If you need both from one codebase, cross-platform frameworks like Flutter (Dart) or React Native (JavaScript) trade a little native polish for a lot of shared effort. The choice hinges on whether one platform must feel flawless or both must ship affordably.
There is no "best" programming language. There's only the best fit for a specific job, a specific team, and a specific horizon. Anyone who tells you otherwise is selling their comfort zone, not your solution.
The factors that matter more than syntax
Once a language is technically capable of the job, and for most business software, several are, the decision turns on things that have nothing to do with the code itself:
- Who you can hire and keep. An exotic language nobody locally knows means a tiny, expensive talent pool and a maintenance headache the day your one specialist leaves. Boring and widely-known is often the wiser bet.
- What you already run. A new system usually has to live alongside existing ones. Matching the ecosystem you're already in saves enormous integration pain.
- The ecosystem and libraries. Half of modern development is gluing together existing, battle-tested pieces. A language with mature libraries for your problem can cut months off a build.
- Developer speed vs runtime speed. For most business software, the cost is people's time, not server time. A language that lets a team build and change quickly usually beats one that shaves milliseconds nobody will notice.
- Longevity. Will this language still be well-supported and hire-able in ten years? The proven, popular options are a safer foundation for something you'll depend on.
The trap to avoid
Choosing a language because it's new and exciting, or because one developer wants it on their CV. We've inherited plenty of systems written in something trendy that the original author then left, and the business was stranded with code nobody else could touch. Build for the team that will maintain it, not the résumé of the person starting it.
So how do you actually decide?
Match the shape of the job to the language's natural lane, then let the practical factors break any tie:
- Web app? TypeScript/JavaScript, often with a Python or C# back end.
- Data, automation or AI? Python.
- Microsoft-centric business system? C#/.NET.
- Large enterprise platform with a big team? Java or C#.
- Mobile app? Swift/Kotlin native, or Flutter/React Native for both at once.
- High-performance service at scale? Go or Rust, once you've confirmed performance is genuinely the constraint.
The real skill isn't memorising that list, it's reading your own situation honestly and resisting the pull of fashion. Like the database underneath it, your language choice is a long-term commitment dressed up as a quick technical call. Make it with your maintenance, your hiring, and your five-year roadmap in view, and you'll rarely regret it.
That's exactly the kind of unglamorous, consequential decision a good technology partner is there to help you get right the first time, before it's set in concrete.
