platform-infrastructure
refoundai/lenny-skills
Design and scale internal platforms and shared technical infrastructure with proven patterns from engineering leaders.
What is platform-infrastructure?
Help teams build or improve internal platforms and developer infrastructure. Use this when deciding whether to build vs buy tooling, designing developer platforms, creating shared services, or managing technical debt at scale.
- Abstract common capabilities into shared infrastructure to reduce repetitive work
- Design for adoption by solving real developer problems, not theoretical ones
- Plan infrastructure scaling before hitting limits to avoid failure scenarios
- Build discoverability into platform architecture for better usability
- Implement server-side tracking for reliable, consistent analytics across platforms
How to install platform-infrastructure
npx skills add https://github.com/refoundai/lenny-skills --skill platform-infrastructureHow to use platform-infrastructure
- 1.Understand the platform's purpose and intended users (internal developers, external partners, or both)
- 2.Assess organizational readiness for adoption and governance structures
- 3.Identify leverage points where platform investment creates the most value
- 4.Design the platform to solve real developer pain points, not anticipated future needs
- 5.Plan infrastructure scaling timelines before hitting current limits
Use cases
- Deciding whether to build internal tooling vs purchasing third-party solutions
- Designing a developer platform for internal teams or external partners
- Abstracting repetitive components to accelerate feature velocity
- Planning infrastructure scaling before usage spikes cause failures
- Establishing governance and adoption structures for shared services
- Engineering leaders and architects
- Platform/infrastructure teams
- Product managers overseeing internal tools
- Technical founders scaling development velocity
- Organizations managing technical debt
platform-infrastructure FAQ
Evaluate whether the problem is unique to your organization and whether you have dedicated product ownership and adoption structures. Avoid building for abstract future needs—focus on current developer pain points that are costing productivity.
Design for real developer problems, not theoretical ones. Establish clear metrics to measure adoption, ensure dedicated product management ownership, and plan for the migration cost of moving teams off existing solutions.
Building for the abstract future rather than current needs, treating infrastructure as a technical project without product ownership, and waiting too long to scale until hitting failure scenarios.
Default to server-side tracking. Client-side SDKs are the biggest analytics mistake—server-side tracking provides better data reliability, cross-platform consistency, and reduces developer maintenance burden.
Monitor your current infrastructure limits and establish a 'doomsday clock'—when will you hit capacity? Plan scaling projects before failure, avoiding both premature optimization and waiting until it's too late.
Full instructions (SKILL.md)
Source of truth, from refoundai/lenny-skills.
name: platform-infrastructure description: Help users build and scale internal platforms and technical infrastructure. Use when someone is deciding whether to build vs buy tooling, designing developer platforms, creating shared services, or managing technical debt at scale.
Platform Infrastructure
Help the user design and scale internal platforms and shared technical infrastructure using insights from 5 product and engineering leaders.
How to Help
When the user asks for help with platform infrastructure:
- Understand the platform's purpose - Ask whether they're building for internal developers, external partners, or both
- Assess organizational readiness - Determine if they have the adoption and governance structures to support a platform
- Identify the leverage points - Help them find where platform investment creates the most value multiplication
- Design for adoption - Ensure the platform solves real developer problems, not theoretical ones
Core Principles
Abstract common capabilities into shared infrastructure
Daniel Lereya: "We actually stopped for the first time and say, 'What is the column like?' And we also organized all the product architecture around it... making the work of adding a new column just thinking about the specific." Scaling feature velocity requires abstracting repetitive components into a shared infrastructure so developers only focus on unique logic.
Invisible infrastructure often matters most
Asha Sharma: "It wasn't the hundreds of features, it was all in the infrastructure and the platform... performance, reliability, privacy, safety, all of those things." The success of major platforms often depends on "invisible" qualities like reliability and speed rather than visible features.
Plan for scale before you need it
Ivan Zhao: "During COVID, we just couldn't scale up our infrastructure. For the longest time, Simon's really good at don't do premature optimization... we're running off even the largest instance there is for Postgres." While avoiding premature optimization is good, infrastructure must be planned far enough ahead to avoid "doomsday" scenarios when usage spikes.
Build discoverability into the architecture
Eli Schwartz: "If you create a categorized sitemap where you can say, 'These are all the questions on health and from the sitemap... then a search engine can navigate through the entire site, and all of the questions and answers are discoverable.'" For large-scale platforms, structural decisions like HTML sitemaps and internal linking are critical for search engine discoverability.
Default to server-side tracking
Vijay: "The biggest mistake is setting up analytics using client side SDKs... start tracking events from your servers instead of from your clients." Server-side tracking is superior to client-side SDKs for data reliability, cross-platform consistency, and developer maintenance.
Questions to Help Users
- "Who are the 'users' of this platform and what problems are they trying to solve today?"
- "What's the current developer experience pain point that's costing the most productivity?"
- "How will you measure whether this platform is actually being adopted?"
- "Is this a build vs buy decision, or should this remain a manual process for now?"
- "What's your 'doomsday clock' - when will current infrastructure hit its limits?"
Common Mistakes to Flag
- Building for the abstract future - Creating capabilities based on anticipated needs rather than current developer pain
- Platform without product ownership - Treating infrastructure as a technical project without dedicated product management
- Avoiding premature optimization until it's too late - Not monitoring infrastructure limits to trigger scaling projects before failure
- Client-side tracking by default - Using browser SDKs instead of server-side event tracking
- Ignoring the migration cost - Building new platforms without accounting for the effort to move teams off existing solutions
Deep Dive
For all 6 insights from 5 guests, see references/guest-insights.md
Related Skills
- platform-strategy
- product-operations
- scoping-cutting
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