Martin Li

Write the runbook, not just the code

I try to write the page I would want to find at 2am during an incident: the exact command, the exact error, the fix, and the why. Twenty-two of those exist because of a rollout or an outage I did not want anyone to have to rediscover.

Leave the decision visible

My interview platform withholds per-question scores until the interview ends, because a running score changes how people answer the next question and destroys the measurement. Its architecture notes have a section called "things deliberately not done" so those read as choices, not oversights.

Fix it even when it is not yours

An audit turned up services deployed to cluster pairs that were not actually in separate availability zones, which quietly defeats the point of having two. I did not own them. I wrote up the rule, raised the pull requests, and asked the owners to review.

Get it wrong in private, twice if needed

My first two passes at a script meant to run across 35 repositories were subtly broken in ways that would have been harmless on one repo and destructive on thirty-five. Scale turns a small bug into a large one, so I test the blast radius before I widen it.

Migrating 35+ services, one version at a time

Every service sat a different distance from the target version. I co-owned the tracking: a merge-status board for all 35 that surfaced nine repositories with blocking conflicts, four where the mainline already had the change, and one abandoned service I cut from scope. Then I wrote the team's upgrade guide, because jumping several major versions at once produces breakage nobody can isolate.

Knowing your dependencies are up, not just your service

Audited 22 services across four platforms, verified every log index and APM process group, and found services missing the egress rule their collector needed. Then went a layer down: a custom health indicator checking 20+ downstream dependencies in parallel with CompletableFuture, and a Python job that mails the fleet's status daily.

One config change, 35 repositories

Scripted as a batch change rather than 35 hand-written pull requests. Took three tries: a malformed pattern, then a fragile range delete that could swallow an unrelated section, then awk flagging on the key and stopping at the next non-indented line. A parallel Python audit hit an auth wall, so I moved to token-based API access.

Five services, five completely different failures

A stack that had never worked in dev. No auth client for that environment. A gateway with four stacked problems including an audit table that did not exist. A service still pointed at a decommissioned cluster. The method was unglamorous: read the actual error out of each pod instead of guessing.

Compliance-gated releases, 13 services at a time

Release engineer across two ecosystems, on-prem Kubernetes and AWS. Coverage thresholds, security scans clean of critical and high findings, a change request carrying every signed-off ticket, then control-platform approval before the pipeline runs at all. One release carried ten tickets at once, well above the usual batch.

A tool built for whoever cleans up after it

Stock splits used to mean hand-running SQL across four tables. The wizard that replaced it resolves human-readable identifiers to internal keys server-side, so a request can never touch the wrong security, and shows sample rows before and after so operations can check without dumping the dataset.

Certificates, made boring on purpose

Owned the mutual TLS lifecycle behind a file-transfer integration: request, install, rotate, test. Whoever does it next is usually under pressure with an expiry behind them, so I wrote it as a nine-step SOP with the exact commands and keystore conversions.

Two clusters, one datacenter, zero redundancy

Services should pair across separate availability zones. An audit found pairs built from mismatched bases and one service spread across three. I did not own them. I documented the rule, ordered the replacement addresses, raised the pull requests myself, and asked the owners to review.

Gauntlet

A FastAPI and LangGraph engine that runs adaptive technical interviews. The hard part was never the model call, it was deciding what the model is allowed to judge: code computes the facts and enforces the constraints, the model handles only genuine judgment. 21 REST endpoints, 194 tests, and a CI-gated benchmark that grades the grader.

PythonFastAPILangGraphPostgreSQLRedisReact

ClearSpeak

A speech coach that listens while you rehearse and gives feedback in real time: filler words, pacing, progress across sessions. The LLM and the speech-to-text both run on the device, so the recording of you stumbling through a practice run never leaves your phone. Built and shipped solo.

React NativeTypeScriptExpollama.rnwhisper.rn

PressurePoint

A local-first app for executive dysfunction, built on one idea: the hard part is starting, not finishing, so nothing in it punishes a miss. Research-grounded behavioral UX, WCAG AAA accessibility, and 155 assertions that test the design rules so a future refactor cannot quietly undo them.

React NativeExpoTypeScriptAccessibility

Randomized Optimization

A graduate study putting backpropagation head to head with genetic algorithms and MIMIC on heart-disease classification, reaching about 0.945 accuracy. The interesting result was not which one won, but where each method stopped improving, and why.

Pythonscikit-learnNeural Networks