When it comes to choosing between Python and Golang for your business, I’ve found that it really depends on the type of projects you’re working on and your long-term goals. Over the years, both languages shine in different areas, but the key to making the right choice often comes down to understanding how they fit with what you’re trying to build.

Both Python and Golang are powerful, but they have different strengths. Deciding which language to prioritize is less about picking the "best" language and more about aligning the right technology—and the right hires—with your business needs.

When I think of Python, I think flexibility and speed:

Python is a language that’s incredibly versatile, and it’s used in so many different fields—from fintech to AI to web development. What stands out is its ease of use and how quickly you can get things up and running with it.

• AI and Machine Learning: In AI and machine learning projects, Python is the clear frontrunner. I’ve worked with companies that chose Python specifically because of its strong libraries like TensorFlow, PyTorch, and Scikit-learn. The language’s flexibility allows developers to experiment with models quickly, which is crucial when you’re building something as complex as an AI system. In places like Cambridge, where biotech and AI start-ups are leading the charge, Python is the go-to for data science and algorithm-heavy projects.

• Rapid Prototyping: If you need to iterate quickly—whether it’s for a prototype or early-stage product—Python is ideal. Developers get concepts off the ground in days instead of weeks because of how intuitive the language is. The syntax is easy to pick up, which means teams can collaborate without too much friction, and new hires can get up to speed fast.

• Data Science and Fintech: In fintech, Python is a popular choice for building data analysis tools, trading algorithms, and even automation scripts. Companies in London’s fintech scene rely on Python because of its ability to handle large data sets and complex financial models. It’s also highly readable, making it easier for teams to audit code—important in industries like finance, where accuracy and transparency are key.

For businesses that need a flexible language capable of handling data-heavy tasks, Python is almost always my first recommendation. But I’ll admit, it’s not perfect for everything.

Golang, on the other hand, feels built for performance:

Golang (Go) is where I turn when performance and scalability are front and centre. Over time, I’ve seen it become the language of choice for companies building high-performance backend systems or cloud infrastructure. Its simplicity and speed are its biggest selling points in my view.

• Concurrency and Real-Time Systems: One of the biggest advantages with Golang is how well it handles concurrency. If your business is working on systems that need to process a lot of tasks at once—think real-time trading platforms, IoT, or large-scale cloud applications—Golang shines. I’ve seen fintech companies in London use Golang to power their backend systems because of how efficient it is at handling multiple processes simultaneously. The language was designed with modern workloads in mind, and it shows in how well it performs under pressure.

• Scalable Microservices: Golang is also perfect for businesses building microservices architectures. Its statically typed nature and fast execution make it ideal for creating small, lightweight services that can scale independently. This is something well noted companies adopting, particularly those moving to cloud-native solutions.

• Low-Latency Applications: If your project needs to minimise latency, Golang is an obvious choice. I’ve seen it used in high-frequency trading platforms, real-time bidding systems, and even performance-intensive SaaS platforms. Its low memory footprint and efficient garbage collection allow applications to run smoothly without consuming too many resources.

How to Choose: It’s about your Business Needs:

The question of whether to prioritise Python or Golang comes down to your business goals and the type of project you’re building. From my perspective, here’s how I usually break it down:

• For AI, Machine Learning, and Data-Driven Projects: If you’re working on projects that involve data science, AI, or machine learning—especially in fields like biotech or fintech—Python is usually the right choice. The wealth of libraries and its ease of use make it the best option for businesses that need flexibility and quick iteration.

• For Cloud Infrastructure, Microservices, and Performance-Driven Applications: On the flip side, if your business is focused on building scalable, high-performance systems, especially in fintech or cloud services, Golang is likely the better choice. In my experience, it’s the language that performs best when efficiency and concurrency are non-negotiable.

Hiring the Right Talent Is Key:

Regardless of the language, hiring the right developers for your specific project is what really makes the difference. Here’s how I see it:

• Python Developers: Python developers often need to be strong problem-solvers who can think creatively about how to tackle complex tasks, like building AI models or data analysis systems. The key to hiring Python talent, in my opinion, is finding developers who not only know the language but also understand the frameworks and libraries that are central to your project. For businesses in Cambridge, where AI is a major focus, I’ve seen the right Python hires move projects forward dramatically faster.

• Golang Developers: Golang developers, on the other hand, tend to excel in performance-focused environments. The best Golang hires are those who have experience working on large, scalable systems and know how to write efficient, clean code. Hiring Golang developers with experience in microservices, cloud infrastructure, or real-time applications can make a huge difference, especially when you’re building systems that need to handle a lot of concurrent operations.

In my view, the language you choose should match your business goals, but hiring the right developers for that language is what will ultimately determine your success.

Conclusion: My thoughts on Python vs Golang

The choice between Python and Golang really depends on what your business is trying to achieve. If you’re working on AI, data science, or any project where flexibility and speed to market are key, Python should be your priority. But if you’re building systems that need to scale, handle high concurrency, or minimize latency, Golang is the way to go.

At the end of the day, it’s not just about the language—it’s about finding the right talent that can use the language to push your project forward. I’ve seen how the right Python or Golang developers can transform a project, helping companies scale and innovate faster. Whatever language you choose, make sure your hires align with your goals, and you’ll be set up for success.