Podcast Summary: How I AI - "How Amplitude Built an Internal AI Tool That the Whole Company’s Obsessed With (and How You Can Too)" featuring Wade Chambers

Introduction

In the August 11, 2025 episode of How I AI, host Claire Vo welcomes Wade Chambers, Chief Engineering Officer at Amplitude. The episode delves into how Amplitude developed an internal AI tool named Moda that swiftly became integral to the entire company. Wade shares insights into the decision-making process behind building the tool in-house, its implementation, and the profound impact it has had on the organization.

1. Build vs. Buy: The Decision to Develop Moda Internally

Wade Chambers discusses the strategic choice Amplitude made to build their own AI tool rather than purchasing existing solutions. This decision was influenced by the desire to leverage internal data more effectively and customize functionalities to better fit the company's unique needs.

• Efficiency and Speed: Wade emphasizes that developing Moda internally was faster and required less time investment than anticipated. "It didn't take us as long to do it and it's in spare time, people's spare time... probably like three to four weeks spare time of some pretty talented engineers" ([03:22]).

• Leverage and Customization: By building Moda, Amplitude could integrate various APIs and tools seamlessly, ensuring the tool was tailored to their specific workflows. "The way that you're going to want to use this and how you're going to get more leverage the more that you can do it internally... it's probably better off doing it yourself" ([03:22]-[04:00]).

2. Overview of Moda: Features and Capabilities

Moda serves as Amplitude's internal agent, enabling employees to access and query extensive business data effortlessly. It functions within Slack and a proprietary web interface, providing versatile access points for all team members.

• Data Integration: Moda connects to multiple data sources, including Confluence, Jira, Salesforce, Zendesk, Slack, Google Drive, Productboard, Zoom, Outreach, Gmail, Asana, Dropbox, GitHub, and HubSpot. "It does not have access to private, personal or restricted data sets. It's generally the public ones, well enterprise public ones that we have internally" ([10:06]-[11:16]).

• Functionality: Beyond simple queries, Moda can generate Product Requirements Documents (PRDs) and facilitate prototype generation, streamlining the product development lifecycle. "We have product management, engineering, sales, customer support, marketing, our CEO, our head of sales... all using it for lots of different things internally" ([05:57]-[12:45]).

3. Implementation and Rapid Adoption within Amplitude

The internal rollout of Moda was remarkably swift, gaining widespread adoption within a week of its initial release.

• Social Engineering Approach: Wade attributes the rapid adoption to what he terms a "social engineering approach." By making Moda's usage visible and encouraging employees to see their peers successfully using the tool, enthusiasm and engagement naturally followed. "If you can see people more credible or equally credible as yourself having great effect with this, it's an obvious thing that I want to use" ([08:19]-[09:18]).

• Ease of Access and Use: The tool's integration with familiar platforms like Slack and its user-friendly interface lowered barriers to entry, facilitating quick adoption across various departments. "It allows a lot of people to be able to engage with it. And that's what makes it catch like fire" ([06:24]-[09:18]).

4. Demonstration of Moda in Action

Wade provides a live demonstration of Moda, showcasing its ability to interact naturally and provide insightful outputs based on internal data.

• Self-Introduction: "Moda, what are you doing?" prompts Moda to explain its functionalities, ensuring users understand its capabilities. [09:20]

• Data Access and Querying: Wade illustrates how Moda accesses diverse datasets and how users can query specific information. For example, generating insights from recent Slack messages or customer feedback sourced from Zendesk and Outreach. [11:43]-[15:35]

• PRD and Prototype Generation: The demonstration includes Moda generating a PRD from a simple one-sentence prompt, showcasing its ability to expand ideas into detailed documentation quickly. "What I love about these and other PRD generators is you can go from that little snippet of an idea to something much more robust." ([14:06]-[24:38])

5. Impact on Product Management and Workflow

Moda has significantly enhanced the efficiency and effectiveness of Amplitude's product management process.

• Accelerated Workflow: By automating research, documentation, and prototype generation, Moda reduces the time from idea to prototype from weeks to mere days or even hours. "It's definitely changing the velocity, number one... now we can actually put those three different roles together and produce that in a single meeting" ([29:45]-[31:32]).

• Enhanced Collaboration: The tool fosters greater collaboration among product managers, designers, and engineers by providing a unified platform for accessing and utilizing data. "We've actually intentionally done that at times of where we've said okay, you're going to take on a different role... it was actually very functional" ([32:37]-[33:52]).

• Quality Assurance: Despite automation, Moda's outputs undergo rigorous review processes to ensure accuracy and relevance. "If the person who is doing the generating hasn't also done some follow up queries... you actually have to apply critical reasoning to see where it may have failed you." ([27:31]-[29:10])

6. Challenges and Strategies in Building AI Tools

Wade addresses the challenges faced during Moda's development and the strategies employed to overcome them.

• Prompt Engineering: Developing effective prompts is crucial for Moda’s performance. Amplitude's team leveraged both experienced engineers and recursive AI assistance to refine prompts. "AI is a good tool to use for building prompts... recursively ask AI to give you better prompts" ([22:12]-[22:44]).

• Continuous Improvement: Moda is maintained through collaborative efforts, with contributions from engineers, product managers, and designers. The tool is open-sourced within the company, allowing diverse input and rapid iteration. "It's all checked into GitHub... we've had designers that are contributing to this and product managers who are contributing to this." ([22:55]-[23:24])

• Handling Failures: When Moda doesn't perform as expected, the team employs strategies like revising inputs and providing constructive feedback to guide improvements. "I swim upstream... I'll give it feedback as we're going through it in a nice way because you need to be nice to your AI." ([37:20]-[37:48])

7. Future Implications and Team Dynamics

The introduction of Moda has not only streamlined workflows but also fostered a culture of empathy and cross-functional collaboration within Amplitude.

• Role Flexibility: Moda has encouraged team members to take on different roles, enhancing understanding and empathy across disciplines. "We've actually intentionally done that at times of where we've said okay, you're going to take on a different role... it's a nice, it's a nice skill development workflow." ([32:56]-[34:30])

• Increased Innovation: By reducing the time spent on repetitive tasks, Moda empowers teams to focus on more strategic and creative initiatives, potentially leading to more innovative products and solutions. "Multiply their value based on these tools... what we're going to be capable of doing." ([36:21]-[37:03])

8. Lightning Round: Thoughts on AI in Engineering

In a rapid-fire segment, Wade shares his excitement and concerns regarding AI in engineering.

• Excitement: The ability to manage technical debt more effectively and multiply engineering capabilities through AI tools like Moda. "This is going to give us the ability to do so much more for our customers. I'm genuinely excited by what this means for us." ([36:21]-[37:03])

• Concerns: Ensuring AI tools are user-friendly and reliable, and maintaining a balance between automation and human oversight. "You have to apply critical reasoning to see where it may have failed you." ([27:31]-[29:10])

Conclusion

Wade Chambers' insights into Amplitude's development and implementation of Moda highlight the transformative potential of internal AI tools. By prioritizing speed, customization, and cross-functional collaboration, Amplitude has set a benchmark for how companies can harness AI to enhance productivity and innovation. Wade's experiences offer valuable lessons for other organizations looking to integrate AI tools into their workflows effectively.

Notable Quotes

• "The way that you're going to want to use this and how you're going to get more leverage the more that you can do it internally... it's probably better off doing it yourself." — Wade Chambers ([03:22])

• "If you can see people more credible or equally credible as yourself having great effect with this, it's an obvious thing that I want to use." — Wade Chambers ([08:19])

• "What I love about these and other PRD generators is you can go from that little snippet of an idea to something much more robust." — Claire Vo ([00:20])

• "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 ([29:10])

Final Thoughts

Wade Chambers' discussion on Moda underscores the importance of building tailored AI solutions that align closely with an organization's data and workflows. Amplitude's success with Moda serves as an inspiring case study for other businesses aiming to leverage AI for enhanced operational efficiency and innovation.