Revolutionizing software creation: Harnessing the power of GenAI
summary
Generative AI is already producing usable artifacts: code via GitHub Copilot, Figma wireframes via Relume, low‑code apps via AppSheet, and reusable prompts and tasking in Thoughtworks’ Team AI, with claims of 50% faster, twice as fast and real data from BCG study: 700 consultants showing measurable gains. Experimental agent systems (LangChain, tool-using LLMs) can orchestrate browsing, coding and email but are costly and brittle—agents succeed about 1 in 10—so teams adopt IDE plugins, in‑house models for IP, policies, and measurement.
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chapters (12)
- 0:00Introduction
- 1:09Generative AI rise
- 3:20Software as knowledge work
- 5:08AI tools today
- 9:56Abstraction levels
- 11:48AI vs software artifacts
- 13:15AI agents future
- 15:00AI-driven processes
- 16:26Conversational and proactive applications
- 17:35Tool use capabilities
- 19:01AI in software delivery
- 19:22Adopt AI in dev
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