I was excited to attend the event Accelerate AI with Cloud Run , organised by Google Developer Group (GDG) North West. Unlike the typical seminar-style tech meetups, this event was so different. It wasn't just about listening, it was about building. The combination of an expert talk and hands-on labs felt perfect for a developer audience. The workshop started with a session delivered by Richard Bannister from Google. His talk focused on building AI agents on Google Cloud using the Agent Developer Kit (ADK), which is a framework designed to help developers create, deploy, and scale AI-driven agents efficiently. Key takeaways from the session: A structured architecture for agent development includes: Agent Build: Capabilities to design, build and test individual AI agents and multi-agent systems Agent Ops: Capabilities to deploy, manage, evolve and optimise AI agents Data Platforms for Agents: Capabilities to acquire, prepare, store and access data for AI agents Security for Agent...
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Implementing then specificating?
Testing before coding? xD
I'm serious, what's the problem with this method?
The main problem is that we cannot practically complete a task in a phase. Software Development needs iterative and incremental process instead of sequential process as Waterfall.
I know that a modified Waterfall Model is added with iteration but it does not solve its sequential process problem.
See detail at http://en.wikipedia.org/wiki/Rational_Unified_Process
See the wikipedia article for more information.
Also, building the architecture as the needs grow is a central agile practice. And most user-centric design approaches emphasize the importance of iterative design with frequent user feedback, which means that you need to implement something in order to refine your specifications.
Thanks for your opinion. You raised a very good point - Iterative Refinement.