The API That Never Changed: How Slack's Platform Team Achieved Backwards Compatibility for 8 Years

The API That Never Changed: How Slack’s Platform Team Achieved Backwards Compatibility for 8 Years

The Challenge

In 2017, Sarah Chen joined Slack as a Staff Engineer on the Platform API team. She inherited a gnarly problem: Slack’s Public API was evolving rapidly to support new features, but every breaking change created chaos for thousands of third-party developers. App developers were vocal about the pain - some had stopped building new integrations entirely due to “API whiplash.”

The business impact was clear: slower ecosystem growth meant fewer integrations, which reduced Slack’s stickiness with enterprise customers. But the technical challenge seemed insurmountable - how do you evolve a platform API rapidly while maintaining perfect backwards compatibility?

The Conventional Wisdom (That Didn’t Work)

Sarah’s team had tried the standard approaches:

• Versioning: Create v2, v3, etc. as needed. Result: maintaining multiple versions consumed massive engineering resources and developers still complained about migration burden.

• Deprecation warnings: Give developers 12-18 months notice before removing old endpoints. Result: Most developers ignored warnings until the last minute, creating support nightmares.

• Feature flags: Toggle new behaviors on/off. Result: Exponential complexity as flags interacted, plus developers had to opt-in to improvements.

None of these addressed the core problem: breaking changes are fundamentally at odds with platform growth.

The Insight That Changed Everything

Sarah’s breakthrough came from an unusual source - a conversation with a database internals engineer at a conference. Modern databases maintain backwards compatibility for decades by following one principle: the data format is append-only, and readers evolve to handle all historical formats.

What if APIs worked the same way?

Sarah proposed a radical constraint: No API field can ever be removed or have its meaning changed. Only additions are allowed.

Her team was skeptical. “We’ll be stuck with our mistakes forever!” But Sarah showed them the math: if you assume you might make mistakes, versioning means maintaining multiple parallel mistake-filled systems. Append-only means you fix forward, not sideways.

The Technical Architecture

Sarah designed what became known as “Schema Evolution Protocol”:

1. Immutable Field Semantics

• Once a field is added to an API response, its type and meaning never change
• Fields can be marked deprecated but must continue to be populated
• New fields can be added freely without coordination

2. Multi-Generation Responses

Instead of returning different data based on API version, return everything:

{
  "user": {
    "id": "U123",
    "name": "Jane Doe",              // Original field (2015)
    "real_name": "Jane Doe",          // Added 2016
    "profile": {                      // Added 2017
      "display_name": "Jane",
      "real_name": "Jane Doe",
      "first_name": "Jane",
      "last_name": "Doe"
    }
  }
}

Yes, it’s redundant. That’s the point. Clients written in 2015, 2017, and 2020 all get data they understand.

3. Request Compatibility Layer

Sarah’s team built a transformation layer that converts old request formats to canonical internal format:

• Accepts requests in any historical format
• Normalizes to current internal representation
• Applies business logic once
• Transforms response back to multi-generation format

4. Automated Compatibility Testing

The team created “time machine tests” - actual requests from production logs going back years, replayed continuously:

• Captured real API calls from 2015, 2016, 2017…
• Stored expected responses
• Every code change must pass all historical tests
• Regression means you broke backwards compatibility

The Organizational Challenge

The technical design was elegant, but Sarah faced a harder problem: getting product teams to buy in.

Product managers wanted to fix mistakes: “We named this field wrong; let’s change it in v2!” Sarah’s response: “Add the correctly-named field. Mark the old one deprecated. Both work forever.”

Engineers wanted to delete old code: “Nobody uses this legacy field anymore!” Sarah’s response: “Define ’nobody.’ We have API calls from apps with 10 users that haven’t been updated since 2016. Those users matter.”

Leadership worried about technical debt: “Won’t we accumulate cruft forever?” Sarah’s counter: “We already have cruft. But now it’s isolated in the compatibility layer instead of spread across every service.”

Sarah’s influence strategy:

1. Make it easy to do the right thing: Created code generation tools that automatically produced multi-generation responses. Engineers just defined new fields; the framework handled compatibility.

2. Show the business impact: Tracked “breaking change support tickets” before and after. They dropped 90%. Presented this to leadership quarterly.

3. Build champions, not consensus: Found early adopter teams, helped them succeed, used them as proof points for skeptics.

4. Document the “why” relentlessly: Wrote the definitive internal design doc explaining the approach. Linked it in every code review about API changes. Made it required reading for new platform engineers.

The Results (8 Years Later)

By 2025, Slack’s Public API had:

• Zero breaking changes since the protocol was adopted in 2018
• 10x growth in third-party apps (from 1,500 to 15,000+)
• 94% developer satisfaction on API stability (up from 67%)
• Maintained velocity: New API features shipped at the same rate, but without breaking existing apps

The compatibility layer represented about 15% of the platform team’s codebase, but eliminated 60%+ of historical support burden.

More importantly, the constraint shaped how teams thought about API design. Product managers started asking “how do we add this capability without changing existing behavior?” Engineers proposed new fields instead of modifications. The system enforced good practices through architecture, not policy.

Lessons for Staff Engineers

1. Constraints Enable Creativity

Sarah’s “append-only” constraint seemed limiting but actually clarified decision-making. When you can’t break things, you get creative about extending them. Constraints eliminate bikeshedding and analysis paralysis.

2. Technical Architecture is Organizational Architecture

Sarah’s system didn’t just solve a technical problem - it changed how product and engineering teams collaborated. The best technical decisions make organizational dysfunction irrelevant.

3. Measure What Matters to Others

Sarah didn’t track “API elegance” or “code cleanliness.” She tracked developer complaints, support ticket volume, and ecosystem growth. Speaking the language of business impact gave her credibility to make aggressive technical bets.

4. Make the Right Thing Easy

Sarah could have written standards documents about backwards compatibility. Instead, she built tools that made it automatic. Senior ICs influence through infrastructure, not instruction.

5. Play the Long Game

The first year was rough - extra code, redundant data, skeptical peers. But Sarah optimized for 5-year outcomes, not 5-month outcomes. Staff engineers have the seniority to take long-term bets others can’t.

6. Document Decisions, Not Just Code

Sarah’s design doc became institutional knowledge. Years later, new engineers read it to understand “why we do things this way.” Your best code might last 3 years. Your best docs last a decade.

The Broader Principle

Sarah’s approach exemplifies a key Staff Engineer skill: using technical architecture to eliminate entire classes of problems.

Instead of getting better at managing breaking changes (versioning, deprecation, migration support), she made breaking changes architecturally impossible. The problem disappeared.

This is different from senior engineer thinking, which focuses on solving problems well. Staff engineer thinking looks for ways to make problems not exist.

Other examples of this pattern:

• Stripe’s idempotency keys eliminate duplicate payment bugs
• Feature flags eliminate big-bang releases
• Immutable infrastructure eliminates configuration drift
• Event sourcing eliminates data inconsistency bugs

The question isn’t “how do we solve this problem better?” It’s “how do we restructure the system so this problem can’t occur?”

Conclusion

Sarah Chen never became a manager. She stayed an IC and was eventually promoted to Principal Engineer. Her API compatibility work influenced platform design across the industry - several major APIs adopted similar approaches after her 2020 blog post about it.

The lesson: Staff+ engineers create leverage through systems thinking. Sarah didn’t make backwards compatibility easier. She made it automatic, shifting from continuous effort to one-time architectural investment.

That’s the essence of technical leadership without management authority - changing the game, not just playing it better.