I soft launched my context product this week.
A fellow with Artic Consulting, Amit Giri, has been asking me interesting questions on LinkedIn about my exploration of context engineering.
Good questions. Interesting questions. Difficult questions. Very difficult questions.
A few days ago, he shared a report from Redis about context engineering. Quick version: First, everyone knows context is way more important than which LLM you use. Second, almost no one is trying to solve the context problem holistically. It’s all siloed, disconnected projects and domain-specific investments.
I don’t know whether Disney sees the first, but I think they do. I mean, it’s a bit Captain Obvious.
But the second point? That is my reality. Each month, it seems someone introduces a conversational tool that answers questions about… subscriptions, or web traffic, or content engagement, or experimentation.
Everything is disconnected and siloed. Not only is that part of what I’m trying to solve, but in doing so I am swimming against the political currents.
A month ago, I was wondering how to get my second user.
My engineering lead, Donnie, and I realized we could use a feature we developed for a completely different purpose: a Markdown text blob Donnie built to document and modernize decade-old Hulu instrumentation processes, combined with the MCP server he built to make it simpler to explore instrumentation schemas.
Markdown files, an MCP server and GenAI? That’s peanut butter, jelly & Wonder White.
I released the Disney+ playback context that I’ve vibe-coded through a half-dozen agents into Donnie’s Markdown/MCP structure, built a skill to connect to it, and convinced an engineer, Eyal, to test it out.
It worked!
A tiny step. So tiny. Just one user and just one use.
But now I have a much more interesting product problem.
How do I get Eyal to use it again?
The context has to be valuable. So valuable that he can see and feel the difference.
How do I get more people than just Eyal to use it?
The exact same thing. The context must yield results that are obviously better than just using an LLM to build queries.
GenAI is almost disconnected from the value proposition. If an LLM can get the same query results without the context I’m generating, what’s the point?
So do I go deeper into the data products Eyal and his peers care about? Or do I go wider, cover more data products to get more users, knowing the wider I go, the shallower I get?
One user. One use.
The next milestone isn’t ten users. It’s getting Eyal to come back.
And swimming against the political currents? That’s a whole ’nother story.