META DESCRIPTION: Discover the latest programming language trends in developer tools and software engineering for September 2025, including Python’s parallel leap, classic language comebacks, and emerging alternatives.

The Week in Developer Tools & Software Engineering: Programming Languages Take Center Stage (September 4–11, 2025)

Introduction: Why This Week in Programming Languages Matters

If you thought programming languages were a solved problem, this week’s headlines would like a word. From Python’s long-awaited leap into true parallelism to the resurgence of “golden oldies” and the rise of new contenders, the world of developer tools and software engineering is anything but static. In fact, the past seven days have delivered a flurry of news that not only signals where the industry is headed, but also challenges our assumptions about what makes a language relevant—or even revolutionary.

Why should you care? Because the tools and languages developers choose today will shape the apps, AI, and digital experiences of tomorrow. Whether you’re a seasoned engineer, a tech leader, or just someone who wants to keep their finger on the pulse of innovation, understanding these shifts is essential. This week, we’ll dive into:

• Python’s game-changing move to free-threaded execution and what it means for performance and productivity.
• The return of classic languages like Perl to the top 10, and what that says about the industry’s appetite for reliability and legacy code.
• The emergence of new languages like Zig and Gleam, offering fresh perspectives and alternatives to the old guard.
• The growing influence of AI on coding practices and the tools developers use every day.

So grab your favorite debugging snack and let’s decode the week’s most important stories—because in the world of software engineering, the only constant is change.

Python’s Parallel Revolution: Free-Threaded Python and the End of the GIL

For years, Python’s infamous Global Interpreter Lock (GIL) has been the programming equivalent of a speed bump on the Autobahn. No matter how many cores your machine boasted, Python would politely decline to use them all at once, limiting true parallelism and frustrating developers working on performance-critical applications. But as of this week, that’s about to change in a big way[1][2].

Python 3.14 is set to introduce free-threaded execution, finally removing the GIL and unlocking the full power of modern multi-core processors. As Michael Kennedy, a prominent voice in the Python community, put it: “The maximum performance I can get out of a single Python process is 10% of what my machine is actually capable of.” With the GIL gone, Python can now run multiple threads in parallel, making it a serious contender for high-performance computing and data-intensive workloads[1][2].

But with great power comes great responsibility. Developers will need to grapple with the complexities of concurrent programming—race conditions, deadlocks, and all the other challenges that come with parallelism. Still, the consensus is clear: this is a transformative moment for Python, and one that could reshape its role in everything from AI to web development[1][2].

The numbers back up the excitement. According to recent developer surveys, Python usage continues to surge, marking one of the largest year-over-year gains for any established language. Even more striking: a significant portion of Python developers have two years or less of professional experience, signaling a new generation of coders eager to push the language’s boundaries[1].

And it’s not just about performance. Python’s ecosystem is evolving rapidly, with frameworks like FastAPI seeing increased adoption among Python developers, underscoring the language’s growing appeal for web development[1]. Meanwhile, work is underway to make iOS and Android officially supported platforms, bringing Python’s “write once, run anywhere” dream closer to reality[1].

Key takeaways:

• Python 3.14’s free-threaded execution removes the GIL, enabling true parallelism[1][2].
• Python’s popularity is at an all-time high, with explosive growth among new developers[1].
• FastAPI and mobile support are expanding Python’s reach into new domains[1].

The Return of the “Golden Oldies”: Perl and the Battle for the Top 10

If you thought the programming language popularity contest was a young developer’s game, think again. The latest TIOBE Index for September 2025 reads like a retro playlist, with Perl making a surprise comeback into the top 10[3]. It’s a reminder that in software engineering, what’s old can be new again—especially when reliability, legacy support, and a vast ecosystem are on the line.

The battle for the top 10 is fierce, with classic languages like Visual Basic, SQL, Fortran, Ada, and Delphi jockeying for position each month. As the TIOBE editors note, “Every time you think one of them will stay in the top 10, it is replaced by another language.” The real intrigue? Despite the buzz around Rust, Kotlin, Dart, and Julia, it’s the established players that are holding their ground[3].

Why does this matter? In an era obsessed with the next big thing, the persistence of these “golden oldies” speaks to the enduring value of stability, mature tooling, and a deep bench of experienced developers. Ada, for example, is seeing renewed interest thanks to its reputation for safety and reliability in mission-critical systems—a trend driven by ever-stronger demands for security in software[3].

For organizations with decades of code and millions of lines in production, the cost of switching languages can be prohibitive. Instead, they’re doubling down on what works, investing in modernization efforts that keep legacy systems humming while gradually adopting new paradigms where it makes sense.

Key takeaways:

• Perl returns to the TIOBE top 10, highlighting the staying power of classic languages[3].
• The battle for popularity is increasingly between established “golden oldies” rather than new entrants[3].
• Security and reliability are driving renewed interest in languages like Ada[3].

New Kids on the Block: Zig, Gleam, and the Rise of Alternative Languages

While the old guard holds its ground, a new wave of programming languages is quietly gaining traction among adventurous developers. This week, two names stood out: Zig and Gleam[4].

Zig has leapt from #149 to #61 in the TIOBE Index, positioning itself as a serious competitor to Rust for low-level systems programming. Its appeal? Simplicity, robustness, and a focus on being “optimal and reusable.” For developers tired of C or C++ but wary of Rust’s learning curve, Zig offers a compelling alternative—one that fits seamlessly into existing ecosystems without the friction of a steep learning curve[4].

Meanwhile, Gleam continues to rise in popularity, reaching version 1.8.0 earlier this year. Inspired by the ML family (think OCaml), Gleam brings strong typing and functional programming concepts to the table, challenging developers to “think differently and find better ways forward.” It’s a language that rewards curiosity and experimentation, making it a favorite among those looking to expand their coding horizons[4].

What unites these emerging languages is a desire to solve old problems in new ways—whether it’s safer memory management, better concurrency, or simply a more enjoyable developer experience. They may not dethrone the giants overnight, but their influence is already being felt in the tools, libraries, and best practices adopted across the industry.

Key takeaways:

• Zig and Gleam are gaining momentum as alternatives to C/C++ and mainstream functional languages[4].
• These languages emphasize simplicity, safety, and a fresh approach to familiar problems[4].
• Their rise reflects a broader appetite for innovation and experimentation in the developer community[4].

AI, Coding Assistants, and the Changing Face of Software Engineering

No roundup of programming language news in 2025 would be complete without a nod to the growing influence of AI-powered coding assistants. According to recent developer surveys, a significant share of developers plan to try AI coding assistants soon, joining those already using them. That’s nearly half the community on the cusp of a major workflow transformation[1].

But the relationship is complicated. While many developers use AI coding tools daily, a nearly equal share actively distrust their accuracy[1]. It’s a classic case of love-hate: the productivity boost is undeniable, but so are the risks of relying on tools that can hallucinate or introduce subtle bugs.

The upshot? AI is becoming a must-have skill for new hires, and its impact on how code is written, reviewed, and maintained is only set to grow. As AI assistants become more sophisticated, they’re not just speeding up routine tasks—they’re changing the very nature of software engineering, blurring the lines between human and machine creativity[1].

Key takeaways:

• AI coding assistants are on the verge of mainstream adoption among developers[1].
• Productivity gains are tempered by concerns about accuracy and trust[1].
• Mastery of AI tools is becoming a core competency for the next generation of engineers[1].

Analysis & Implications: The Future of Programming Languages and Developer Tools

What do these stories tell us about the state of developer tools and software engineering in 2025? Several clear trends emerge:

• Parallelism and Performance Are Back in Focus: Python’s move to free-threaded execution signals a renewed emphasis on squeezing every ounce of performance from modern hardware. As data volumes grow and AI workloads proliferate, languages that can harness multi-core architectures will have a distinct edge[1][2].
• Legacy Isn’t a Dirty Word: The resurgence of Perl and the resilience of other classic languages highlight the industry’s pragmatic streak. When reliability, security, and a vast ecosystem matter, the old guard still has plenty to offer[3].
• Innovation at the Edges: Emerging languages like Zig and Gleam show that there’s still room for fresh ideas, especially when they address pain points that mainstream languages have yet to solve. Their rise is a testament to the creativity and restlessness of the developer community[4].
• AI as a Force Multiplier—and a Double-Edged Sword: The rapid adoption of AI coding assistants is transforming how software is built, but it’s also raising new questions about trust, accountability, and the future role of human developers[1].

For businesses, these trends mean more choices—and more complexity. The right language or tool can unlock new capabilities, but it also requires investment in training, tooling, and cultural change. For individual developers, the message is clear: adaptability, curiosity, and a willingness to learn are more valuable than ever.

Conclusion: The Only Constant Is Change

This week’s programming language news is a vivid reminder that software engineering is a living, breathing discipline—one where yesterday’s constraints become today’s opportunities, and where the next big thing might just be a remix of the past. Whether you’re excited by Python’s parallel future, intrigued by the return of Perl, or eager to experiment with Zig and Gleam, one thing is certain: the tools you choose today will shape the digital world of tomorrow.

So, as you refactor that legacy code or spin up your next side project, ask yourself: What language will you bet on? And how will you adapt as the landscape continues to evolve? In the end, the best developers aren’t just masters of syntax—they’re storytellers, problem-solvers, and lifelong learners. The next chapter is yours to write.

References

[1] Svitla Systems. (2025, September 4). Python's Parallel Computing & Multiprocessing Explored. Svitla Blog. https://svitla.com/blog/parallel-computing-and-multiprocessing-in-python/

[2] YouTube. (2022, September 10). 3.4 Parallel - Python for Scientific Computing 2022. https://www.youtube.com/watch?v=TzT9xpy_q0M

[3] TIOBE Software. (2025, September 8). TIOBE Index for September 2025. TIOBE. https://www.tiobe.com/tiobe-index/

[4] Semaphore. (2025, September 6). Top 8 Emerging Programming Languages to Watch in 2025. Semaphore Blog. https://semaphore.io/blog/programming-languages-2025