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How Amplitude built an internal AI tool that the whole company’s obsessed with (and how you can too)

Wade Chambers, Chief Engineering Officer at Amplitude, shares how his team built Moda—an internal AI tool that gives employees access to enterprise data across multiple systems, enabling faster product development and decision-making while…

Wade ChambersguestClaire Vohost

Aug 10, 202540mWatch on YouTube ↗

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WHAT IT’S REALLY ABOUT

Amplitude’s viral internal AI agent unlocks enterprise data for everyone.

Amplitude’s Chief Engineering Officer Wade Chambers demos Moda, an internal AI tool that unifies access to company knowledge (Slack, Jira, Confluence, Salesforce, Zendesk, etc.) and answers questions with cited sources.
They chose a lightweight build approach—3–4 weeks of part-time work—by combining off-the-shelf components (notably Glean APIs for search/RAG) with an internal orchestration framework and Slack-first distribution.
A key driver of adoption was “social engineering”: making usage and successful queries visible in Slack so employees can copy prompts, learn patterns, and trust outcomes through peer proof.
Moda also operationalizes product work by generating multi-step PRDs (problem/solution/requirements) and prototype prompts, while emphasizing review, critique, and iterative regeneration rather than blindly accepting AI outputs.

IDEAS WORTH REMEMBERING

5 ideas

Start where people already work: Slack as the default AI interface.

Amplitude embedded Moda in Slack so adoption didn’t require new habits; visibility of others’ queries made it easy to copy prompts and learn fast.

Make AI work observable to drive trust and “prompt reuse.”

Seeing credible peers use Moda successfully acted as social proof and enabled employees to borrow prompts/results instead of starting from scratch.

Build quickly by mixing off-the-shelf search with lightweight internal orchestration.

They avoided overengineering by leveraging Glean APIs for enterprise search/RAG and layering a simple internal framework plus purpose-built workflows on top.

Citations and source transparency are non-negotiable for enterprise Q&A.

Moda “always cites sources,” allowing verification and reducing the risk of hallucinated decisions when querying company knowledge.

Use AI to compress the product cycle—but keep human review gates.

Moda can generate detailed PRDs and prototype prompts in minutes, yet teams still review problem/solution/requirements and ask for cons or alternative evidence.

WORDS WORTH SAVING

5 quotes

I started showing a couple of people internally… and then a week later, it seemed like the entire company was using it.

— Wade Chambers

Moda is that internal tool… that unlocks all of the data that we have internally, and then allows us to answer questions, to build artifacts like PRDs.

— Wade Chambers

If you can see people more credible… having great effect with this, it’s an obvious thing that I want to use.

— Wade Chambers

You can go from that little snippet of an idea to something much more robust.

— Claire Vo

You can’t assume it’s going to… You actually have to apply critical reasoning to see where it may have failed you.

— Wade Chambers

Read the available transcript

Build vs buy for internal AI toolsSlack-first distribution and viral adoption mechanicsEnterprise search + RAG using Glean APIUnified access to internal data sources with permissionsPRD orchestrator and multi-step agent workflowsPrompt engineering via recursive AI-assisted prompt writingWorkflow compression: research → PRD → prototype in one meetingGovernance: citations, dataset restrictions, review loops

High quality AI-generated summary created from speaker-labeled transcript.

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