Jellyfish Advances Developer and Agent Productivity Insights for the AI-Native SDLC

Jellyfish Advances Developer and Agent Productivity Insights for the AI-Native SDLC

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Engineering intelligence platform’s new and updated features include lifecycle explorer, AI skill adoption measurements, and AI spend-to-work attribution BOSTON, Oct. 7, 2026 /PRNewswire/ — Jellyfish, the leading Software Engineering Intelligence and AI Impact Platform, today announced a comprehensive suite of features to help organizations measure the impact of AI engineering tools. The features, launched during…

6 Best Agentic SDLC Tools for AI-Assisted Development Teams in 2026

6 Best Agentic SDLC Tools for AI-Assisted Development Teams in 2026

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Key Takeaways AI-assisted development teams need more than coding agents. They need tools that connect code, review, testing, workflows, and production feedback. Runtime intelligence is becoming a critical SDLC layer because AI-generated code can pass tests while still behaving poorly in production. The strongest agentic SDLC tools help teams reduce…

From tools to workflows: Rethinking the SDLC for the AI age

From tools to workflows: Rethinking the SDLC for the AI age

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AI is rewriting the way software is built. For decades, software development followed a predictable sequence of requirements, design, build, test, deploy. This model was designed for a world where coding and testing was expensive, and feedback came late. With AI, code can be generated in seconds, testing is continuous and feedback is real time….