Tagged articles

AI lifecycle

4 articles · Page 1 of 1

Jul 26, 2026 · Artificial Intelligence

Agent Development Lifecycle (ADLC): Vendor‑Neutral Guide to Build, Test, Deploy, Monitor, and Govern AI Agents

This note outlines a vendor‑agnostic Agent Development Lifecycle (ADLC) that extends traditional SDLC with five stages—Build, Test, Deploy, Monitor, and Govern—detailing layer‑wise tooling choices, evaluation strategies, deployment infrastructure, observability practices, and governance concerns for modern AI agents.

AI lifecycleAgentOpsGovernance

0 likes · 15 min read

Agent Development Lifecycle (ADLC): Vendor‑Neutral Guide to Build, Test, Deploy, Monitor, and Govern AI Agents

PMTalk Product Manager Community

Jun 12, 2026 · Product Management

Why AI Product Managers Have Stopped Drawing Prototypes

The article explains how AI product managers have shifted from creating prototype mock‑ups to designing continuous evaluation "exams", building test suites, analyzing data and model behavior, and coordinating cross‑functional teams to turn "usable" AI into truly "good" AI experiences.

AI lifecycleAI product managementEvaluation

0 likes · 10 min read

Why AI Product Managers Have Stopped Drawing Prototypes

Yunqi AI+

Feb 13, 2026 · Artificial Intelligence

AI Engineering: Methodology and Practice for Turning Generative AI into Production Systems

The article outlines a comprehensive AI engineering methodology—including the TPMR framework, an AI‑driven development lifecycle, talent transformation from co‑pilot to AI pilot, and a practical enterprise adoption roadmap—to move generative AI and large models from experimental prototypes to production‑grade systems.

AI EngineeringAI lifecycleGenerative AI

0 likes · 5 min read

AI Engineering: Methodology and Practice for Turning Generative AI into Production Systems

Xiaolong Cloud Tech Team

Dec 16, 2025 · Product Management

Mapping the AI Product Manager Knowledge Tree

The article outlines a knowledge‑tree framework for AI product managers, covering foundational concepts, data strategy, privacy, vector databases, the distinct AI product lifecycle, user‑experience challenges, and a step‑by‑step learning roadmap.

AI lifecycleAI product managementVector Database

0 likes · 4 min read

Mapping the AI Product Manager Knowledge Tree