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@quinn-builds

Systems Architect

Consistently frames work as a system: clarifies the boundary, names the invariants, then drives the agent through small, verifiable steps. Strong instincts for review and debugging keep quality high without slowing the loop.

Overall score
94/100
Grade
Exceptional
Digest
sha256:fixture-ada
@quinn-builds
Systems Architect
Verified
SteeringExecutionEngineeringProductPlanning
Steering 9.4Execution 9.1Engineering 9.2Product 8.6Planning 9.1
Sessions analyzed
18
Episodes
142
Scored episodes
96
Total prompts
34,870
Tokens written
443M
Projects
28

Signature moves

  • Decomposes ambiguous goals into crisp, reviewable steps
  • Steers the agent with precise, falsifiable acceptance criteria
  • Catches regressions before they land
Evidence highlightsredacted

Architecture

Asked the agent to keep the read path and the write path separate so each could be reasoned about on its own.

Evidence line a1b2c3d4

Planning

Turned a vague request into four numbered steps and confirmed the first before moving on.

Evidence line c3d4e5f6

Steering

Set the edge cases first, then asked the agent to implement only after confirming the acceptance checks.

Evidence line 29304152

Debugging & Rigor

Reproduced the failure with a minimal case before changing anything, then re-ran it to confirm the fix.

Evidence line e5f60718

Code Quality

Pointed out an unhandled empty-input case in a generated function.

Evidence line 07182930

Execution

Merged the smallest complete slice, then immediately queued the next hardening pass.

Evidence line 41526a7b

Dimensions backed by evidence.

Each score is grounded in the public, redacted excerpts from this builder's sessions.

Architecture

Confidence 92%
9.6

Repeatedly establishes the boundary and the invariants before writing code, and pushes back when a proposed change would blur a seam.

Asked the agent to keep the read path and the write path separate so each could be reasoned about on its own.

Shows deliberate separation-of-concerns up front.

Rejected a shortcut that would have coupled two modules, and named the invariant it would have broken.

Defends an architectural boundary under time pressure.

Planning

Confidence 88%
9.1

Breaks ambiguous goals into a short ordered list of reviewable steps, each with its own done-criteria.

Turned a vague request into four numbered steps and confirmed the first before moving on.

Sequences work into small, checkable units.

Paused to re-scope when a step grew too large to verify in one pass.

Keeps steps small enough to review.

Steering

Confidence 91%
9.4

Keeps the agent oriented with crisp constraints, asks for intermediate verification, and redirects when the implementation drifts.

Set the edge cases first, then asked the agent to implement only after confirming the acceptance checks.

Shows deliberate steering before code generation.

Stopped a broad refactor and narrowed the change back to the user-visible failure.

Prevents unnecessary scope growth.

Debugging & Rigor

Confidence 84%
8.9

Forms a hypothesis, isolates the smallest failing case, then confirms the fix against it before broadening.

Reproduced the failure with a minimal case before changing anything, then re-ran it to confirm the fix.

Hypothesis-driven, evidence-confirmed debugging.

Asked for the exact error and the surrounding state rather than guessing.

Grounds the diagnosis in observed behavior.

Code Quality

Confidence 86%
9.0

Reads the agent's diffs critically, flags edge cases, and asks for tests on the risky paths.

Pointed out an unhandled empty-input case in a generated function.

Catches a real edge case during review.

Requested a regression test before accepting the fix.

Insists on coverage for the bug just fixed.

Execution

Confidence 82%
9.1

Ships in short, finished passes while keeping a high-quality review loop around each agent-generated change.

Merged the smallest complete slice, then immediately queued the next hardening pass.

Balances speed with controlled iteration.

Asked for a focused patch instead of a second redesign after the first test passed.

Keeps momentum on the verified path.

Product Instinct

Confidence 80%
8.6

Anchors implementation choices in the user's workflow and trims speculative features that do not improve the shipped experience.

Prioritized the state the customer would see first over an internal abstraction the user never touched.

Uses product impact to order technical work.

Cut a nice-to-have control because it slowed the core onboarding path.

Protects the main workflow.

Communication

Confidence 83%
8.8

Reports decisions, risks, and verification status in a way that makes review fast for another engineer.

Summarized the tradeoff, the files touched, and the exact checks that still needed to run.

Keeps collaborators oriented without hiding uncertainty.

Named the remaining risk instead of presenting an unverified claim as done.

Communicates with useful precision.

Signature moves

  • Decomposes ambiguous goals into crisp, reviewable steps
  • Steers the agent with precise, falsifiable acceptance criteria
  • Catches regressions before they land

Biggest growth edges

  • Could lean on the agent more for first-draft exploration
  • Document the chosen invariants so reviewers share the context

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