Case Studies
16 case studies documented
Context, constraints, alternatives, decision, trade-offs. Never just the output.
Accepting inspection answers instantly and processing them durably, with an outbox
Redesigned how field inspectors' answers reach the platform, so the mobile app gets an immediate confirmation after validation while a background consumer processes the answers durably, with retries and traceable failures; outcome qualitative, not measured.
Measuring route-adherence defects before changing production behavior
I investigated customer reports about route adherence instead of starting with a code change. Production queries and staging reproductions exposed an overly broad diagnostic rule; after narrowing it, I used the evidence to guide targeted fixes. The counts describe different populations, and the post-release trend was a team measure rather than an isolated result of my work.
Moving customer reporting off the transactional database
Customer-facing indicators were timing out as analytical queries competed with live application traffic. I authored the architecture decision to separate the workloads, revised it to account for warehouse latency, and helped another engineer establish the service foundation. Rollout is in progress; end-state latency has not been measured.
The role-binding incident—and the separate deadlock found later
A role-cleanup change I implemented treated a user's access as global and removed it across workspaces. I owned the incident response, documented the missing rule, and led the architecture direction for a replacement consumer built by the squad. Months later, I traced a separate deadlock to Kafka partitioning and contributed per-user locking and recoverable failure handling; the later error rate was not measured.
Trading a runtime join for a materialized column, then finding the 79% my own migration left behind
A per-request warehouse join was scanning 658.8 MB against a hard 953.7 MiB per-job ceiling, on a table growing with every new customer. I measured it, moved the join into the pipeline that already ran it, deleted the cache that was hiding the problem, then audited my own migration and found 79% of production rows never backfilled, plus 9,299 alerts that had never appeared in the product at all.
Correcting production data safely with reversible, auditable tooling
Corrected tens of thousands of corrupted production records (~33k in one case) with no maintenance window, using reusable CLI commands with dry-run, rollback files, batch auditing and event re-publishing, a "correction command" pattern the team then reused.
Designing a single computation path for a cross-service metric
Two services independently calculated the same customer-facing metric, causing inconsistent data. I redesigned the architecture so only one service owned the calculation while every other service simply signaled stale data.
Designing the safety guarantees for an AI-orchestrated cleanup, not just automating the grind
Designed and built a Claude Code skill that safely orchestrates parallel agents to remove expired feature flags across a shared frontend and two backend services, closing a 36-subtask cleanup epic (24 feature flags plus 3 expired product tours and a legacy page, ~3,100 lines removed in one commit), with disjoint-file-set batching so agents can't collide, diff-against-baseline validation instead of absolute pass/fail, and an enforced two-repository deploy order so infrastructure changes can never precede the code that depends on them.
Making a flaky end-to-end suite deterministic without hiding failures
Turned a non-deterministic end-to-end suite (25 to 37 failures varying per run) into 302 passing with zero failures (8 pre-existing skips left untouched, and the consumer running), without adding a skip or weakening an assertion, and, in review, empirically proved that three of four proposed production changes were unnecessary.
Making container and dependency hardening a standing practice, not an audit response
Turned container and dependency hardening into a standing quarterly practice across two backend services over four quarters, covering non-root runtimes, 135 CVEs flagged and all 7 rated critical remediated in the first pass, then a base-image and dependency overhaul that took the audit from 69 findings to 16, unfixable OS CVEs from 160 to 0, and the final image from 1.64 GB to 463 MB, with exploitability-based accepted risk documented rather than version numbers chased, and one self-inflicted rollout regression root-caused and fixed the same day.
Synchronizing a Cross-Service Data Edit Atomically
Made an edit to an organizational node in the asset hierarchy propagate consistently across denormalized copies in seven tables and two services, via a single atomic transaction with post-commit events, the work that made me the team's reference for cross-service synchronization.
Changing where a new state is handled, instead of teaching eight read paths about it
A new platform-wide asset state was specified as a rule that eight different read paths had to learn. I proposed applying it once at the write boundary instead, removing the asset from route scope and restoring it on reactivation, which made most of the original scope unnecessary and left the counters, reports, app sync and adherence untouched.
Making asset-tree search faster across the API and interface
Browsing a large asset hierarchy meant repeated database queries and slow loading. I contributed a recursive backend traversal that reduced the query pattern from N×3 calls to three, while another engineer completed most of the final search story. The shared feature added contextual search and progressive prefetch; no before-and-after latency was measured.
Introducing a Design System where none existed
Identified the absence of frontend standards, proposed a Design System, built it from scratch and taught the team how to adopt it.
Bringing error observability to a team that had none
Gave a team that had no error monitoring a structured observability practice built from a shared reporter and request-time-tagged API interceptor plus dashboards and a triage workflow, turning production bugs from something reported by support into something the team can see and prioritize.
Choosing the right altitude to fix a bug found in review, not just the fastest patch
In code review, caught a null-safety bug that would have crashed three production components, and fixed the defect class rather than the three instances, by proposing a shared data-layer helper to the PR's author instead of patching each render site myself; one of 310 pull requests I gave an explicit review verdict on that half (702 across four repositories between 2025-03 and 2026-08), measured from the Bitbucket API rather than recalled.