Tag: ai-agents
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Agentic Development Lifecycles: When AI Becomes Your Teammate
The Weekly Radar The Context Traditional software development follows a series of handoffs—Requirements → Design → Build → Test → Release → Monitor—where humans shuttle context between stages. The emerging Agentic Development Lifecycle (ADLC) reframes this into artifact-driven loops: Intent → Design → Build → Evaluate → Govern → Deploy → Observe → New Intent.…
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Agentic SDLC: Embedding AI Agents Across the Development Lifecycle
The Weekly Radar The Context The Agentic Development Lifecycle (ADLC) reframes the traditional six-stage SDLC—Plan, Design, Build, Test, Deploy, Maintain—into a closed loop powered by AI agents. In this model, an LLM like Claude captures intent directly (writing requirements as version-controlled intent.md), consolidates design and spec phases into a single interactive session, and then automates code and test generation together, surfacing institutional knowledge via CLAUDE.md rather than siloed docs. At each handoff, continuous AI-driven evaluations…