The hidden costs of AI-generated code: what engineering leaders need to know
Learn to manage the hidden costs of AI-generated code by balancing rapid velocity with long-term maintenance and risk.
Technical debt
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The signals senior engineers read that juniors don’t (yet)
Ramping in a new codebase is about reading the right signals—where work is happening, what kind it is, and where things keep breaking.
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Engineering intelligence that delivers a pulse for every leadership role
Engineering intelligence for leadership roles: Get a pulse on your teams and scale visibility from Team Leads to VPs.
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AI transformation in software engineering: 2025 year in review
In 2025, AI transformation in software engineering redefined the industry. How are leaders navigating impacts on quality, metrics, and ROI?
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Camping out: engineering intelligence for teams
Reflections from Boston Code Camp on why engineering intelligence for teams depends on developer buy-in and moving beyond ticketing data.
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Your AI adoption roadmap for engineering
A practical roadmap for AI adoption in engineering, built around phased implementation, realistic expectations, and metrics that actually reflect long-term impact.
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AI generated code: revisiting the Iron Triangle in 2025
Does AI generated code break the Iron Triangle? Explore new research on quality, trust, and the hidden costs of AI tools.
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See Flux in action: free trial now available
Try Flux’s free trial now to see how you can get insight into code quality and complexity, security and privacy, third-party dependencies, and architecture.
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Under pressure: engineering in the Age of AI
Engineering intelligence platforms are emerging as the key to managing AI disruption, aligning leadership expectations, and protecting developer teams.
