Magnitude

Problem

Event infrastructure in product companies has a steep learning curve. Non-technical stakeholders (like product managers, marketers, and ops teams) often struggle to:

• Query analytics.
• Trigger user communications.
• Understand the meaning of complex event names.

Take this example:

lecture_course_user_report – By looking at this event, an AI or a non-tech user would only guess it's a "report generated when a user watches a lecture." But that misses the real-world context required to plug it into analytics tools or communication workflows.

As a result, events remain opaque, hard to use, and unreliable for decision-making.

Inspiration

When Model Context Protocol (MCP) was introduced, it allowed LLMs to talk to APIs using plain text context. This sparked a thought:

• Why not bring the same simplicity to event infrastructure?
• What if you could describe events in plain English and query user behaviors directly without depending on engineers?

Idea

Magnitude makes events self-describing and context-aware.

With it, teams can:

• Query in plain English – "Show me users who watched a recorded lecture but didn't complete the quiz."
• Plug events into tools directly – Analytics, CRM, and comms platforms.
• Cut dependency on engineers – Context is encoded upfront, not hidden in code.

The 3 Layers of Context

To query the right data from any event, you need three types of context working together:

Why Mixpanel, PostHog & Others Fall Short

Tools like Mixpanel, PostHog, and Amplitude already let you query events, build funnels, and set up cohorts. They nail the Analytics Context — what happened and when. But that's where they stop.

• No Code Context — They have no idea where the event fires in your codebase, what triggers it, or what conditions gate it. When lecture_course_user_report shows up in a dashboard, there's no way to know if it fires on page load, on button click, or only for paid users — without asking an engineer.
• No Business Context — They can't tell you why an event matters. Is it a leading indicator for churn? Does it signal purchase intent? Should it trigger a nudge email? That meaning lives in people's heads, not in the tool.

So when a PM asks "show me users who are about to drop off," these tools can't answer — because the intent behind events was never captured. You end up in a loop: PM asks analyst, analyst asks engineer, engineer reads the code, context gets lost in translation.

Magnitude encodes all three layers upfront, so anyone — PM, marketer, or AI agent — can query the right data without guessing.