Why AI Matters for Developers Today
AI is a game-changer for how we write code, test, debug, and build digital experiences. At Softhouse, we don’t just observe this shift—we explore it, test it, and make it real. Towards the end of 2025, we teamed up with colleagues across Softhouse to explore and test a range of AI models. Here’s what we uncovered.
How Softhouse Investigated AI in Coding
To truly understand how AI tools affect our work, we combined two key perspectives: hands-on developer insights and large-scale model testing.
Developer Survey Insights
We started with a broad internal survey to capture how our developers use AI today. The respondents spanned backend, frontend, mobile, QA, and DevOps.
Here’s how AI is currently being used in practice:
- Writing new code
- Writing tests
- Refactoring
- Documentation
- Debugging
But there’s a nuance. Developers said they mostly trust AI with smaller tasks—especially bug fixes—rather than entire features. And even then, suggestions are adjusted to fit our standards. This reinforces something we value deeply: expertise means staying critical and in control.
What Tasks AI Supports Best
AI shines when it assists—not replaces. It speeds up routine work, helps catch bugs, and improves test coverage. But at Softhouse, it’s the developer who stays in the driver’s seat.
Performance Testing of 11 Large Language Models
To go beyond opinions, we ran rigorous testing on 11 AI coding tools. Using 24 LeetCode-based challenges, we evaluated performance across 264 test cases. The goal? Real, evidence-based answers.
Top-Performing AI Tools
These five models achieved 100% accuracy:
Grok stood out as a new model designed specifically for software development—and it impressed us.
Trade-offs: Speed vs. Code Quality
Some key insights:
- Claude offered the best overall code quality and handled edge cases well.
- ChatGPT-4.1 was the fastest—but a bit less robust on complex problems.
- Gemini 2.5 Flash was especially strong in algorithm-heavy tasks and internal data work.
Our conclusion? Different tools shine in different contexts.
Recommendations for Daily Use
So what should developers actually use?
Best Models for Complex Tasks
For advanced coding work, start with Claude or ChatGPT-4. Claude excels in quality and reliability. If speed matters more, ChatGPT is a strong option.
Tool Integrations That Matter
One surprise: switching GitHub Copilot’s backend from GPT to Claude made a huge difference for some teams. It’s worth testing.
Exploring Agentic Workflows
We’re also exploring “agent mode” in tools like Copilot, where the AI:
- Compiles your code
- Detects test failures
- Fixes problems—all without a new prompt
One developer even uses Claude in the terminal to scan full codebases, compile apps, and fix linter errors autonomously.
More about AI
At the very core of our work is our passion for sharing and our constant desire to learn and develop. At Softhouse, we don’t just adapt to tech shifts—we shape them. By testing tools, listening to our developers, and sharing real findings, we’re building a future where AI and human expertise work together, every day. AI can feel overwhelming. It doesn’t have to be. Download our 5-minute AI guide and let us guide you.
