Projects

TracerLabs

I've worked with TracerLabs as a technical consultant since 2022, moving between projects and layers as the product needed. The work has ranged from deep performance investigations to shipping product features and improving the systems around them.Rather than owning one subsystem, I tend to take ownership of the problem in front of me — whether that means tracing unnecessary database work, changing an API, building a frontend feature, or contributing to the shared design system.

Aug 2022 → Present · Technical Consultant · Software Architect · Current engagement

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How I contributed

Challenges

Performance that compounds
Some API operations were doing far more database work than the request actually needed. The useful unit of improvement was not a benchmark in isolation, but removing unnecessary work from requests that were made repeatedly during normal product use.
Work that crosses layers
Several features required changes from data access through the API and into the frontend. I worked across those boundaries when the problem required it rather than treating each layer as a separate hand-off.
Different problems at different times
The engagement has changed with the needs of the product: performance and database work at some points, backend and API work at others, and frontend or shared design-system work when that was where the next problem lived.

Role & ownership

  • OwnedIndividual features and technical problems within a larger product
  • OwnedMultiple database and API performance investigations
  • Contributed toBackend APIs and data-access paths
  • Contributed toFrontend product features and complex interfaces
  • Contributed toShared design-system components and infrastructure
  • Collaborated withLarger product and engineering teams where ownership was shared

Key decisions

  1. 01

    Measure the work before optimizing it

    Why
    Query counts, profiling, and query plans made it possible to distinguish real bottlenecks from optimizations that only looked useful.
    Result
    Several changes produced concrete improvements; other proposed optimizations were measured and dropped when they did not justify shipping.
  2. 02

    Fix unnecessary work at the layer where it originates

    Why
    The recurring performance problems were often caused by data-access behavior rather than by the visible API or UI.
    Trade-off
    The fix sometimes required understanding and changing lower-level query behavior instead of adding another application-layer workaround.
    Result
    Two related API paths were reduced from 88 → 14 and 32 → 5 database queries per request.
  3. 03

    Move repeated computation into the database when the data model supports it

    Why
    One processing workload was spending most of its time repeating the same database checks.
    Trade-off
    The query became more deliberate and database-centric instead of keeping the work in application code.
    Result
    A workload that failed to complete within a 3-hour timeout was reduced to 3 database queries and completed in 17.5 seconds against real client-scale data.

Impact

3 hours → 17.5s

Processing time

a workload that previously failed to complete within the timeout

~8,000 → 3

Database queries

for the same ~4,000-item workload

88 → 14

Queries per request

on one API path

32 → 5

Queries per request

on another API path

What changed

  • Repeated API/database work was reduced by removing unnecessary queries rather than masking the problem with another layer of caching.
  • A production-scale processing workload that failed to complete within a 3-hour timeout was brought down to a 17.5-second run against real client-scale data.
  • Features have been shipped across data access, backend APIs, frontend interfaces, and shared UI infrastructure as the needs of the product changed.
  • The engagement has remained flexible: sometimes deep technical investigation, sometimes feature delivery, and sometimes work on the foundations other features depend on.

Timeline

  1. 2022

    Joined as a technical consultant

    Started contributing across the existing product rather than taking responsibility for a single isolated subsystem.

  2. 2022–2024

    Product and platform work

    Worked across backend and frontend applications, integrations, feature delivery, and the systems supporting them.

  3. 2024–2025

    Deeper frontend and shared-system work

    Contributed to complex product interfaces and reusable design-system pieces alongside backend work.

  4. 2025–2026

    Performance and end-to-end feature work

    Focused heavily on database/API performance while continuing to ship features across backend and frontend boundaries.

  5. 2026

    Continued consulting across the stack

    The role remains intentionally flexible, moving to the part of the product where engineering depth is most useful.

Artifacts

Looking back

The most representative part of this engagement is its breadth. The specific problems have changed over four years, but the work repeatedly comes back to understanding how a system behaves and changing the part that is actually causing the problem.

I haven't been the sole owner of the major subsystems I've touched. Instead, I've repeatedly taken ownership of individual problems and features inside a larger engineering team, often crossing the boundary between database, API, frontend, and shared infrastructure.

That is also what makes the engagement useful as technical consulting: the role changes with the product rather than requiring every problem to look like the last one.

Related work