Amplitude’s Code Mode + Data Assistant Agent
Covered by Signal Brief for B2B SaaS product managers — one of 5 tools in Issue #6 · amplitude.com
What it does
Amplitude introduced two AI capabilities on Wednesday aimed at the question its launch post asks directly: AI can build — but can it know what worked? Code Mode brings code-level analysis inside Amplitude itself: teams can run SQL and Python against the behavioral data already in the platform to investigate questions that go beyond a standard chart — what changed, why it matters, who is affected, and what to do next — without exporting data, filing a ticket to a data scientist, or waiting on a separate analysis cycle. It is available to all Free, Plus, and Growth customers. Data Assistant Agent attacks the other half of the problem: the trustworthiness of the data the reasoning runs on. It reviews taxonomy, metadata, usage patterns, and project context to find unclear, duplicated, or undefined events and properties, explains why each issue matters, and recommends prioritized fixes — and it can run an AI-specific audit, investigate taxonomy issues, explain its own prioritization, and draft metadata improvements, all in chat. It is available now to Plus, Growth, and Enterprise customers with AI features enabled.
Why it matters for PMs
Every AI feature you ship is about to be judged on two things — how deeply it can reason, and whether the data underneath is trustworthy enough to reason from — and Amplitude is now selling both at once. Code Mode collapses the distance between “the chart looks wrong” and a code-level answer, while Data Assistant Agent treats data quality as an agent problem, not just a human chore — because agents will read your taxonomy whether you clean it up or not. If you are instrumenting your product for AI features, the audit is worth running before the agents arrive.
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