Case study : from scattered documents to a pilot
What an applied-AI team can build for a sales organization : a prototype enablement agent, what went wrong along the way, and a starter kit for the next team.
Everything tagged ai-agents, newest first.
What an applied-AI team can build for a sales organization : a prototype enablement agent, what went wrong along the way, and a starter kit for the next team.
The harness, data model, security and privacy points, and cost of a real-time sales assistant built with Google ADK, and the break-even it has to clear.
Instead of asking a team to watch recordings they will forget tomorrow, I turned two narrated demos into knowledge an agent serves at the moment of need.
I came to curated knowledge from vector search and direct documents. Here is how I would choose between them for a purpose-built agent.
A plain-language introduction to the LLM Wiki pattern and the Open Knowledge Format, and how a small agent can use a folder of Markdown files as its knowledge.
A running experiment in treating learning and product video like code: versioned, reproducible, and re-rendered on demand with an agent in the loop.
A map of the code-as-video field, from Manim and Remotion to Sora, sorted from deterministic to generative by what each tier offers learning content.
An agent reads Akaunting's codebase and produces a 71-second walkthrough, which changes how Learning Program Owners, Designers, and Developers split the work.
A first experiment in treating video like code: scaffolding an Editframe project, iterating with an AI agent, and rendering a hello-world MP4.
A custom web client that swaps the ADK camera feed for screen capture, so the agent watches the application instead of the user.
Arguing over translation versus localisation misses the point; thinking in layers of context maps cleanly onto a multi-agent architecture.
Instead of buying an expensive translation tool, I built an orchestrated localisation agent in Copilot Studio that never leaves the Microsoft 365 tenant.
Getting Google's ADK bidirectional streaming demo running locally with mic, camera, and voice, as the foundation for a live in-app assistant.
While OpenAI and Anthropic fought over a Pentagon deal, Google shipped WebMCP, UCP, and A2A, the protocol stack for how agents will use the web.
A working model for designing learning content that supports both human understanding and agent retrieval.
An open-source kit for a real-time in-app assistant that listens to voice, sees the screen, and guides users step by step.
Working notes from recreating a voice-and-screen assistant: one path failed on authentication, the next produced a working streaming prototype.
Why this site exists: a place to practice learning design, knowledge systems, and pair-programming with AI agents in public.