In today’s rapidly evolving tech landscape, the integration of AI tools into software development workflows isn’t just an option; it’s a necessity. At DevObsessed, we’re leading the charge by embracing the transformative power of AI—while addressing the critical challenges of security and independence.
Recently, we launched a pilot program to test the effectiveness of AI-powered developer tools like AI enabled IDEs, LLMs, and AI enabled code reviewers. With costs as low as $140 per developer per month, the goal is clear: deliver 10x productivity without compromising quality or security. But our approach goes beyond just plugging in tools and calling it innovation.
The Real Impact of AI on Development
AI tools are becoming indispensable in tasks like generating boilerplate code, reviewing PRs, debugging, and even architecture planning. However, these tools are only as effective as the developers using them. That’s why we believe in augmenting human expertise, not replacing it.
As one of our engineers aptly put it:
“AI won’t replace developers, but another developer using AI will.”
This quote isn’t a warning; it’s a call to action. We’re equipping our teams—and our clients—with the training, tools, and strategies needed to stay competitive.
Security First: Testing Localized AI Models
While enterprise tools are a great start, security is a top concern for us and our clients. Relying on cloud-based AI services introduces potential exposure risks, particularly when handling sensitive or proprietary data. That’s why we’re actively developing on-premise AI solutions that maintain complete isolation from external systems.
- Local Models in Action: The newest Mac mini, are now powerful enough to run localized large language models (LLMs) - although not the large parameter models. Models from Anthropic or (ClosedAI) formerly known as OpenAI can be accommodated with a relatively small server rack investment. By deploying AI models on-prem, we eliminate the need to transmit data externally, ensuring maximum data security while still enjoying the productivity benefits of AI. Note: Meta and Alibaba currently have open source models. Anthropic and OpenAI do not.
- Independent Ecosystems: Our solutions are designed to work seamlessly on isolated environments, ensuring no external dependencies. This keeps client data secure while still leveraging cutting-edge AI capabilities.
The result? A secure, scalable AI ecosystem that doesn’t compromise on functionality or speed.
What We’re Testing
- Combination Testing: We’re not just adopting off-the-shelf tools. We’re exploring combinations of localized and enterprise-grade AI models to find the perfect balance of productivity, security, and cost-effectiveness.
- Success Metrics: From code quality to sprint velocity, we’re defining clear metrics to measure the impact of AI across different development teams.
- Training Programs: Every tool is only as good as its user. That’s why we’re creating tailored training to help developers use these tools responsibly and effectively.
Why This Matters
AI isn’t just a buzzword—it’s a powerful ally in building better software, faster. By embracing tools like LLMs and integrating them securely into our workflows, we’re preparing for the next era of development.
But here’s the catch: this isn’t a one-size-fits-all solution. Every team, every project, and every client is different. That’s why we’re experimenting, iterating, and refining to ensure these solutions meet real-world needs.
Whether you’re looking to boost productivity, improve code quality, or modernize your tech stack, DevObsessed is here to help you harness AI—securely and effectively.
Let’s Build the Future Together
Interested in how AI can transform your development teams? Let’s chat.
