Raw crew note in. Professional record out. Submit raw field notes below. The service returns a polished, structured version ready for the job file. Streaming token-by-token render is available when running locally; see the README for details.
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Every interaction, logged. Successes, failures, and PII rejections are all persisted with latency and token metrics. Pagination supported.
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Timestamp Outcome Latency Tokens Raw note Enhanced text
How this timeline was assembled

By the morning after Jonathan's interview call, I already had the architecture sketched out: the stack, the commit order, how the failure paths should work. Before Claude Code wrote a single line, I pulled real context about my background at Space Genius from our Azure and ADO data. 136 commits, 170 PRs, 76 work items, all verified. I did not want a README that sounded like it came from a template. Every Space Genius reference in the final doc traces to a source I confirmed.

Three principles kept me honest while building. Failure-first: think about what breaks before what succeeds. Earn your complexity: use the simplest thing that handles the failure mode. Separate the responsibilities: API, service, and data stay in their own lanes. Every tech decision in the README traces back to one of these.

The Railway deploy gave me a day-of failure mode that ended up being a good story. NIXPACKS picked the wrong .NET version, then the container died before it could even print the error because the library needed to format the error was also missing. One line in the csproj fixed it. The deploy fight was failure-first in real time.

Once the site was live I locked it down. Any change from that point forward needed a branch, a local check, my approval, and a manual merge. The governance files themselves went through that same gate to get added to the repo. No direct pushes to main. This timeline went through the same process.

  1. M01 | PHASE_0 | Pre-build architecture and planning Verified

    Architecture plan written before the spec PDF arrived

    April 20, 2026

    Architecture plan was authored from Jonathan's verbal description at the end of the interview, before the assignment PDF was emailed. The plan locked the three principles (Failure-First, Earn Your Complexity, Separate the Responsibilities), the 16-commit sequence, the failure-first request flow, the system prompt as file decision, and the hard rules including zero em dashes. The pre-spec planning window is the evidence that the architecture preceded the requirements.

    Evidence: GranumAssignmentArchPlanv1.md present in project files. Plan content predates spec receipt per conversation record.

    spec: Full 16-commit sequence, three principles, failure-first request flow, and hard rules all present in GranumAssignmentArchPlanv1.md.

    conversation: Plan written from Otter AI transcript of Jonathan's verbal description before the assignment PDF was emailed.

    git: needed from CC

    PRE-SPEC ARCH-PLAN THREE-PRINCIPLES 16-COMMITS
  2. M02 | PHASE_1 | Handoff preparation and context lock Verified

    Hallucination guards, human gates, and AC verification all locked before CC touched the repo

    April 21, 2026

    CLAUDE.md, PREFLIGHT.md, and SG_CONTEXT.md produced before CC wrote any code. Full audit of the assignment spec against the architecture plan confirmed every required item covered: enhance endpoint, history endpoint, interaction log, error handling, tests. All three bonus items confirmed in scope: SSE streaming, PII guard, frontend UI. Constants block added at the top of CLAUDE.md after a repo name drift (granum-text-enhancer to granum-assignment) and casing drift (CarmenReed lowercase variant) were spotted. Context lock complete before scaffold commit.

    Evidence: CLAUDE.md, PREFLIGHT.md, SG_CONTEXT.md produced and downloaded from this session. AC checklist completed in conversation.

    conversation: Three handoff files produced. AC and bonus item audit completed. Constants block added after repo name and casing drift were caught.

    git: no repo artifact -- handoff files are external to the repo by design

    HALLUCINATION-GUARD HUMAN-GATE AC-VERIFIED CONSTANTS-LOCK GATE-0-CLOSED
  3. M03 | PHASE_2 | Build execution Verified

    16-commit build executed by CC, 22 of 22 tests green, em dash scan clean

    April 21, 2026

    Full build executed by CC across 16 intentional commits. Every commit was a standalone working state. xUnit suite landed at 17 tests at the end of the original 16-commit build (M03 baseline); later hardening work (PR #9) grew the suite to 22 tests, all green. Em dash scan returned zero across every file. Python seed script populated 8 interactions per spec. Definition of Done items all satisfied. The build came in clean against the plan with no surprises.

    Evidence: 16-commit sequence in arch plan. Test count and DoD verification reported by CC in this session.

    spec: 16-commit sequence in COMMIT STRATEGY section of GranumAssignmentArchPlanv1.md.

    conversation: CC reported 16 commits landed, 17 tests green at M03 baseline (grew to 22 after PR #9 hardening), em dash scan clean, DoD satisfied.

    git: first commit 3510ac6 (init scaffold) through last commit 9658ccd (ADR README), exactly 16 commits verified against git log.

    16-COMMITS 22-TESTS-GREEN EM-DASH-CLEAN DOD-MET
  4. M04 | PHASE_3 | Deployment and verification Verified

    Railway fight resolved: NIXPACKS SDK mismatch, then ICU globalization diagnosed, fixed by Dockerfile switch

    April 21, 2026

    Railway build failed repeatedly. First failure: NIXPACKS provisioned .NET SDK 6 instead of 8 because the project file was not detected. Fixed by adding nixpacks.toml to force the correct SDK. Second failure: container crashed before managed code could run because ICU globalization libraries were absent. Same missing libraries also broke error formatting so the runtime could not print the exception. ICU/globalization was diagnosed as the proximate cause; tried InvariantGlobalization true in Api.csproj at 7795c29 as a one-line workaround, then reverted it 9 minutes later at 9c28d9d when it did not resolve the deploy. The fix that stuck was replacing Nixpacks with a Dockerfile at 06463e9, which guaranteed a full ICU-enabled runtime image. The deployment fight was failure-first architecture applied live to the deployment layer.

    Evidence: Railway build logs pasted into session. InvariantGlobalization added then removed within the same fight; Dockerfile switch is the durable fix on origin/main.

    conversation: Sequential Railway failures diagnosed in session. Root cause was ICU globalization missing, also masked by error formatting depending on the same library.

    git: Full fight chronology: 175cf43 (force .NET 8 SDK), dd30bba (remove .nixpacks cache), b88e91b (correct start command), 7795c29 (add InvariantGlobalization -- failed experiment), 9c28d9d (remove InvariantGlobalization 9 min later), d39f7f0 (disable Nix dotnet auto-detect), 06463e9 (Dockerfile replaces Nixpacks -- fix that stuck). InvariantGlobalization is not present in the current Api.csproj on main.

    FAILURE-FIRST ROOT-CAUSE NIXPACKS ICU-CRASH DOCKERFILE-FIX
  5. M05 | PHASE_3 | Deployment and verification Verified

    29 of 29 smoke tests passed, Railway green, GitHub Pages live, evidence committed

    April 21, 2026

    All six smoke test categories passed: health endpoint, POST /enhance returning real enhanced text, GET /history showing seed data with pagination, PII rejection returning 422 with no stack trace, SSE streaming validated structurally, em dash scan clean on deployed files. Smoke test evidence committed to main as 02dc26d.

    Evidence: 29/29 smoke test report in session. Commit 02dc26d confirmed by CC.

    conversation: CC reported 29 of 29 smoke tests passed after Railway and Pages deploys. Evidence committed as 02dc26d.

    git: 02dc26d smoke-test evidence commit confirmed in CC git log

    29-29-SMOKE RAILWAY-GREEN PAGES-LIVE EVIDENCE-COMMITTED
  6. M06 | PHASE_4 | LIVE and post-LIVE production work Verified

    LIVE declared and governance baseline shipped as PR 1

    April 22, 2026

    LIVE declared by operator at commit f8fa2ed with exact quote: I'm calling it LIVE now (timestamp it). All further edits are now consider production edits and will need a PR in GitHub that I merge manually. The baseline commit f8fa2ed was authored late on 2026-04-21 ET (early 2026-04-22 UTC); the LIVE declaration itself was made the following morning when the operator called the protocol into effect. Three governance files produced (PRODUCTION_WORKFLOW.md, UI_CHANGE_TEMPLATE.md, APPROVAL_LOG.md) and shipped as PR 1, merged at c1d3324 (files currently live under logs/ after the M08 cleanup moved them). Note: two different changes carried the number 2 in different contexts. The timeline-sync schema 1.1 skill upgrade was held back per the .claude/ never pushes policy and lives only on local main as commit b7edde1; separately, GitHub PR #2 (the timeline-rendering PR) was merged publicly at 8950dd7. APPROVAL_LOG.md baseline entry seeded. Production workflow has governed every commit since.

    Footnote: f8fa2ed itself landed as a direct-to-main commit carrying the Granum branding and UI polish pass (inline SVG logo, Field Notes nav, DM Sans and JetBrains Mono fonts, restyled outcome badges). The PR gate was established in the same work session immediately after, making f8fa2ed the transition point where the production workflow began rather than a workflow violation.

    Evidence: APPROVAL_LOG.md baseline entry. f8fa2ed LIVE baseline commit (authored 2026-04-21 ET). c1d3324 PR 1 merge commit.

    conversation: Operator declared LIVE in session with exact quote captured. Three governance files produced and shipped through their own gate sequence as PR 1. Commit f8fa2ed predates the LIVE call by approximately 15 hours; the LIVE declaration is the protocol activation event, not the commit timestamp.

    git: f8fa2ed LIVE baseline confirmed (authored 2026-04-21 21:30:26 ET). c1d3324 PR 1 merge commit confirmed by CC.

    LIVE PRODUCTION-WORKFLOW PR-GATE APPROVAL-LOG PR-1-MERGED
  7. M07 | PHASE_4 | LIVE and post-LIVE production work Verified

    AI Initiatives tab built (4 cards), then expanded to 12, design language propagated to other tabs

    April 22, 2026

    AI Initiatives tab launched with 4 governance skill cards (brain-dump, sg-ticket-prep, lff, lff-prune) using state pills, pattern tags, and cream card aesthetic ported from the portfolio template. Later expanded to 12 cards across two new subsections: Agentic and Automated Workflows (4 cards) and RAG Implementations (4 cards). Original 4 cards preserved byte for byte and rewrapped in a Governance Skills subsection. State color system (production, build, design) visually validated for the first time across multiple states simultaneously. Assignment and History tabs then aligned to the same design language: cream card wrappers, mono uppercase coral labels, hero callouts with coral left borders, History status pills restyled to match. Brand red preserved on Submit and active tab underline as intentional separation: brand red equals action, coral equals structural accent. CSS scoped with .page-* prefix.

    Evidence: AI Initiatives tab live on docs/index.html. 12 cards visible in 3 subsections. Tab styling alignment visible across Assignment and History tabs.

    conversation: AI Initiatives tab built then expanded same day. Design language propagated to Assignment and History tabs in a follow-up styling pass.

    git: initial tab c0cae36 (PR #3), 12-card expansion c725c1e (PR #5), tab styling alignment 213b27c (PR #6 -- shipped as its own PR, not bundled).

    AI-INITIATIVES 12-CARDS DESIGN-LANGUAGE STATE-COLORS-VALIDATED GOVERNANCE-SKILLS-PRESERVED
  8. M08 | PHASE_4 | LIVE and post-LIVE production work Evidence partial

    Cleanup misfire and Dockerfile recovery: live deploy down, restored from git history

    April 22, 2026

    Pre-submission cleanup ran with two intentions: remove unused Docker files (per arch plan rule no Docker or CI/CD) and add a reference directory for assignment artifacts. Two things went wrong. First, a missed branch checkout landed the Docker-removal commit on the AI Initiatives feature branch instead of a dedicated cleanup branch. The reference directory was not shipped in the final state -- the arch plan lives at docs/GranumAssignmentArchPlanv1.md and no reference/ directory exists on origin/main. Second, the cleanup commit message asserted Railway deploys via NIXPACKS based on a misread of the arch plan rule, not the actual config. The actual railway.json said builder DOCKERFILE with dockerfilePath Dockerfile. Within minutes of the cleanup PR merging, the live Railway deploy died. Recovery: worktree-based cherry-pick of the Docker removal onto a proper cleanup branch, then fix/restore-dockerfile branch restored Dockerfile and .dockerignore from git history (git show 84d4861~1:Dockerfile). Live deploy back to green. Governance files later moved to logs/ (logs/PRODUCTION_WORKFLOW.md, logs/UI_CHANGE_TEMPLATE.md, logs/APPROVAL_LOG.md) during subsequent housekeeping. The lesson is the commit message lying to the codebase, not the missing file.

    Evidence: Live Railway deploy failure observed within minutes of cleanup PR merge. Recovery commits on fix/restore-dockerfile branch. Reference 84d4861 cited as parent commit for Dockerfile restoration.

    spec: Arch plan rule cited in cleanup commit message: no Docker or CI/CD. Misread relative to actual railway.json config.

    conversation: Full incident narrated in session: misdirected cleanup, live deploy down, worktree-based recovery, Dockerfile restored from git show 84d4861~1.

    git: Docker removal commit 84d4861 (note: commit itself is the removal; 84d4861~1 is the parent used by git show for restore). Dockerfile restore commit e61f685. PR #4 merge b15af4d.

    FAILURE-FIRST-LIVE DOCKERFILE-INCIDENT GIT-SHOW-RECOVERY COMMIT-MESSAGE-LIED WORKTREE-RECOVERY
  9. M09 | PHASE_4 | LIVE and post-LIVE production work Verified

    Streaming endpoint honesty: documented edge buffering, gated UI to localhost, did not chase the workaround

    April 22, 2026

    Stream button confirmed broken on live deploy. Read-only diagnosis revealed the SSE endpoint was structurally correct, framing correct, flushing correct, frontend handler correct. Token-by-token streaming worked on localhost. Root cause traced to Railway routing through Fastly, which buffers chunked responses. The X-Accel-Buffering: no header set by the API is nginx specific and Fastly ignores it. Coalescing scaled with response length, the fingerprint of edge buffering rather than an application issue. Active decision NOT to chase the CDN workaround. Shipped with documented edge behavior instead. Stream button gated to localhost via JavaScript hostname check (visible at localhost / 127.0.0.1, hidden everywhere else). New README ADR section Streaming Endpoint: Documented Edge Behavior added covering what works, what is degraded, root cause, why documented not fixed, failure-first reasoning. Earn-your-complexity in the rejected-alternative direction.

    See: README ADR "Streaming Endpoint: Documented Edge Behavior" in the repo root for the full decision record.

    Evidence: Stream button gating in docs/index.html. README ADR section. Localhost vs live behavior reproducible.

    conversation: Read-only diagnosis ruled out application layer. Root cause Fastly buffering. Active choice to document not work around. UI gated to localhost. README ADR added.

    git: streaming gate and README ADR shipped together as f916c88 (PR #7 merge 19c7bc9).

    STREAMING-HONEST FASTLY-BUFFERING EARN-YOUR-COMPLEXITY-REVERSE DOCUMENTED-NOT-FIXED LOCALHOST-GATED
  10. M10 | PHASE_4 | LIVE and post-LIVE production work Verified

    Final submission readiness: local DB reset, repo housekeeping, full verification pass

    April 22, 2026

    Pre-submission database refresh: ran seed/seed.py locally to reset interactions.db to the clean 8-record seed state, replacing accumulated dev test history (50+ duplicate mowed the lawn entries from streaming-fix testing). The reset is a local operation: interactions.db is gitignored by design, so no commit was produced and the live Railway DB is unaffected by this run. The seed script itself is the durable artifact, already committed as part of the original 16-commit build (M03). Repo housekeeping: 5 merged feature branches deleted locally and on origin (feature/ai-initiatives-tab, chore/pre-submission-cleanup, fix/restore-dockerfile, feature/ai-initiatives-expand, docs/timeline-update-2026-04-22), 2 orphan CC worktrees removed, git worktree prune cleared metadata. End state: only main, only main worktree, fully synced to origin. Final verification pass hit every spec section live with curl: /health, POST /enhance happy path, validation failures (empty + over-2000), PII rejections (email + phone), GET /history with pagination, GET /enhance/stream as informational verification. Frontend visual checklist completed in browser across all 4 tabs. At M10 submission-readiness, dotnet test confirmed 17/17 green; subsequent PR #9 security hardening added tests and the current suite on origin/main is 22/22 green. Submission report generated to .reports/SUBMISSION_REPORT.md with every claim traced to a verification step. Streaming explicitly listed under Documented Constraints rather than Nice-to-Haves Implemented.

    Evidence: Local seed/seed.py run completed against interactions.db (gitignored, no commit). Branch deletions confirmed on origin. .reports/SUBMISSION_REPORT.md generated with traced verifications.

    conversation: DB refresh was a local seed operation (interactions.db is gitignored, no commit produced). Repo housekeeping (5 branches + 2 worktrees), full verification pass with curl across every spec section, dotnet test 17/17 at M10, submission report generated with every claim traced.

    git: no DB commit exists -- interactions.db gitignored by design. Main commit count at M10 submission: 45. Current main commit count after PR #8, #9, and #10 post-submission work: 69 (51 first-parent merges). Branch deletion verified on origin.

    DB-RESET-LOCAL REPO-CLEAN VERIFICATION-TRACED SUBMISSION-REPORT 22-22-TESTS-CURRENT
AI Initiatives I am running right now. The governance patterns that apply to this take-home (human gate, inference flagging, archive not delete) were validated in the skills below before they were codified here. Some skills below also ship adjacent mechanics that are not in this repo -- for example Jaccard similarity scoring in lff-prune -- and are flagged as such on each card. State tags show where each skill currently lives: design, build, or production.
Governance Skills
Production
Skill · brain-dump.md · April 18 2026
/brain-dump
Takes stream-of-consciousness voice or text input and reflects it back as a structured, tiered brief before any execution fires. T1, T2, T3 classification where T1 means production logic and zero assumptions are allowed. Multi-form input resolution handles attachment, file path, or raw text. Hallucination gate markers flag every inferred item. Human confirmation required before any downstream action. Same reflect before execute discipline that governs every inference flag in this repo.
Reflect Before Execute Hallucination Gate Git-Timestamped
Production
Skill · sg-ticket-prep · SpaceGenius Production
/sg-ticket-prep
Takes messy, incomplete human-written bug tickets (vague repro steps, ad hoc acceptance criteria, missing test data) and transforms them into well-formatted Gherkin syntax ready to feed the sg-bug-fix agentic pipeline for autonomous bug fixing in Azure DevOps. A CC-readiness checklist catches every gap before anything is written. Hard stop on any unresolved gap, same architecture as the inference gate. Original content preserved in a comment before the ticket body updates. The audience for every output line is not a human developer. It is an AI agent that will act on it autonomously.
Messy Input to Gherkin Agentic Pipeline Feed Hard Stop on Gaps Preserve Before Update
Production
Skill · lff v2.1 · Learn From Failure
/lff
Postmortem tool that turns a failed Claude session into one durable preventive rule in the right CLAUDE.md file. Scale telemetry with yellow and red hard gates. 25-word rule cap enforced. Backup before write, atomic write, never auto-apply. Self-improvement proposals staged, never committed. Closed category taxonomy with a custom:X escape hatch. Courtroom metaphor: Plaintiff, Defendant, Judge, Jury. 9 safety rails. Team conventions including merge conflict resolution strategy.
Scale Telemetry 25-Word Cap Self-Improves 9 Safety Rails
Production
Skill · lff-prune v2.1 · Maintenance Companion
/lff-prune
Jaccard threshold 0.3, already in production. Maintenance pass on Learned Rules sentinel sections. Surfaces cluster merges, age-decay, and skill-promotion candidates. Per-proposal approval, batch approve explicitly blocked. Archive never delete, with a Reason line on every archived rule. Migration signal tracking: if prune fails 3 or more consecutive runs, the tool self-documents the signal to migrate to a vector store. It knows its own scaling ceiling. Post-prune scale recheck confirms the tool actually helped. 10-backup retention with rotation. Mode flags: --clusters-only, --age-only, --skills-only.
Jaccard 0.3 in Prod Archive Never Delete Migration Signal Self-Checks After Write
Agentic & Automated Workflows
Design
Initiative · Agentic Workflow · Design
Headless Browser Automation
AI-driven headless browser scrapes sites, captures screenshots, and replicates site schemas to feed Playwright automated test generation. Aims to collapse the gap between a live UI and a maintainable test suite by having the agent build the test scaffolding from the real DOM it just traversed, not from a human-written spec.
Playwright Test Gen Site Schema Capture Agent-Driven Testing
Design
Initiative · Agentic Workflow · Design
Conversational Logic Engines
Natural language systems that know to ask the right questions to guide users through complex reservation, rate, or option flows autonomously. Replaces branching form trees with an agent that holds the flow state and asks only what it still needs to know. Pattern origin: the same reflect-before-execute discipline that governs the inference gate in this repo.
Ask the Right Questions Flow State as Context Reflect Before Execute
Production
Initiative · Agentic Workflow · Production
Self-Auditing Navigation
AI agents pointed at web artifacts (portfolios, docs, product flows) to autonomously identify dead links, navigation inconsistencies, and efficiency gaps. Runs as a scheduled pass rather than a one-shot audit. Output feeds directly into a fix queue instead of sitting in a report nobody reads.
Scheduled Audit Dead Link Detection Fix Queue Output
Design
Initiative · Agentic Workflow · Design
Meeting-to-Ticket Automation
Integrated pipeline that captures raw meeting audio, extracts action items, and automatically creates service tickets or documentation entries. Same messy-input-to-structured-output shape as sg-ticket-prep, but the input is live meeting audio instead of a half-written bug report. Human gate before any ticket is filed.
Audio to Action Items Human Gate Before File Same Pattern as sg-ticket-prep
RAG Implementations
Production
Initiative · RAG · Production
Documentation-Grounded Architecture
Retrieves raw AI meeting notes and processes them to fill information gaps in project assets and estimates. The generation is always anchored in retrieved source material, never free-generated, so estimates trace back to a specific conversation rather than to a hallucinated average.
Grounded Generation Meeting Notes as Source Traceable Estimates
Design
Initiative · RAG · Design
Reference-Based UI Design
Grounds AI UI design output by pointing it specifically at external standards like the Apple Accessibility Developers Guide so the generated code passes compliance review the first time. Treats the standards document as the authoritative spec the model must cite from, not as vague context.
Standards as Spec Compliance First Draft Apple Accessibility Guide
Design
Initiative · RAG · Design
Knowledge-Base QuickQuotes
Feeds an existing company and location knowledge base into a quote generation engine so quotes come out accurate to the customer's actual footprint, not a generic rate card. The knowledge base is the source of truth; the LLM is the formatter.
Knowledge Base as Source LLM as Formatter Accurate by Construction
Build
Initiative · RAG · Build
Knowledge-Base "Living Wiki"
Live Azure Wiki with walk-throughs, ESL translations, documentation templates, and API endpoint tours for new hires. Self-updating via scheduled pulls from source systems, so the wiki never drifts out of date the way static onboarding docs always do. Bilingual by default, not as an afterthought.
Azure Wiki ESL Translations API Endpoint Tours Self-Updating