Platform & API Product Management
Manage platforms and APIs as products: developer experience, API design decisions, versioning and limits, ecosystems and partners, platform metrics, and AI/MCP platforms.
Platform & API Product Management
Manage platforms and APIs as products: developer experience, API design decisions, versioning and limits, ecosystems and partners, platform metrics, and AI/MCP platforms.
In one line
A platform PM builds products that other teams, developers or partners build on: APIs, SDKs, internal platforms and ecosystems. The users are developers, and the product is how easily they succeed.
The 6 classes
Platforms and APIs as products
Understand platform types and users.
- Developers are the users.
- Internal platforms are products too.
- AI assistants are a new channel (MCP).
Developer experience (DX)
Make developers successful fast.
- Measure time to first call.
- Docs and sandbox are the onboarding.
- Errors should explain the fix.
API design decisions for PMs
Decide what matters in API contracts.
- Contracts are promises: version carefully.
- Rate limits protect reliability.
- Webhooks make integrations real-time.
Ecosystems and partners
Grow a platform through others.
- Platforms grow through network effects.
- Partners need clear rules and incentives.
- Review apps for security.
Platform metrics
Measure platform health.
- Mix adoption, DX, reliability and revenue.
- Track success rate and latency.
- Use tickets to find friction.
AI platforms and final project
Apply platform thinking to AI.
- AI platforms centralise models, evals and guardrails.
- MCP is a new distribution channel.
- Treat developers like customers.
Interview questions
What does a platform PM do?
Builds products other teams or developers build on, optimising developer success, reliability and ecosystem growth.
Key DX metric?
Time to first successful API call, plus time to production.
How do you version an API?
Explicit versions, backward compatibility, deprecation notices, migration guides and changelogs.
Platform metrics?
Active developers/apps, success rate, latency, calls, revenue, support friction.
What is an AI platform team?
Provides shared model access, evals, guardrails, prompt/skill libraries and cost controls to product teams.
