Evidence that can be inspected, not just claimed.

15-Minute Review

1. Open OpsDesk Reviewer Replay for the fresh first-role backend/API code proof and latest CI run.
2. Open the DriveDesk Core review route and public demo.
3. Open the AI Backend Review Pack for a compact path through role fit, operational readiness, live evidence, verification, and resume evidence.
4. Open the latest DriveDesk Core CI and Pages runs.
5. Scan the skill evidence matrix.
6. For AI automation roles, open the AI Ops Hiring Signal Brief, First Slice Playbook, demo walkthrough, public evidence status, reviewer acceptance report, role requirements map, live approval evidence, role targets, and CI workflow first.
7. For inbound fit, open Work With Me and Role Targets to check the exact remote and fixed-scope entry points.
8. Open Operational Readiness for distributed remote-team signals: architecture, state ownership, integration contracts, reliability, privacy, CI, runbooks, and handoff quality.
9. Open the evidence repo matching the role.
10. Check tests, CI, docs, runbooks, demo paths, and reviewer snapshots.

Pinned Review Order

• OpsDesk Reviewer Replay: first-role backend/API code proof with FastAPI, SQLAlchemy, PostgreSQL migration, tests, Docker Compose, CI, smoke, and privacy audit.
• DriveDesk Core: flagship backend automation and integration foundation.
• AI Ops Hiring Signal Brief + AI Ops Business Scenario Replay + AI Ops First Slice Playbook + demo walkthrough + public evidence status + live Postgres persistence evidence + privacy boundary + reviewer acceptance report + live approval evidence + CI workflow: hiring signal, business input, backend route, document intake, first slices, committed demo GIF/walkthrough, privacy redaction before RAG/approval/CRM handoff, importable n8n workflow artifact, LLM/transcription provider boundaries, transcript analysis, RAG, scoring, approval, Telegram callback, dry-run CRM handoff, retry/dead-letter, idempotent outbox drain, worker state, live PostgreSQL/pgvector storage, reviewer observability snapshot, CI, and production boundaries.
• DeployMate: Docker/CI handoff evidence with CI/CD, SSH runtime tooling, evidence bundle, review packet, release gates, and runbooks.
• MPlusForm: validation and trust boundaries.

Pinned Repo First-Screen Check

Read-only checked on 2026-06-29. The pinned repositories are not random code samples; each first screen is routed to a hiring or project signal.

• OpsDesk Reviewer Replay: public support-desk backend proof with FastAPI/SQLAlchemy, ticket intake, validation, database state, operator queue, status transition, idempotent outbox, SLA worker, SQL metrics, pytest, Docker Compose, CI, smoke script, and privacy audit.
• DriveDesk Core: backend automation and integration foundation behind DriveDesk AI Operator with business operations, integrations, audit/outbox, adapter boundaries, recovery paths, CI, OpenAPI, SDK drift checks, docs, and public demo.
• AI Ops Workflow Kit: production-minded AI workflow backend with document/CRM/call intake, first-slice playbook, committed demo GIF/walkthrough, RAG, transcript analysis, approvals, outbox handoff, n8n/Telegram/CRM boundaries, privacy redaction, CI, reviewer observability snapshot, and reviewer evidence.
• DeployMate: self-hosted Docker deployment control panel with FastAPI/Next.js/PostgreSQL, SSH runtime tooling, CI/CD, health checks, release gates, evidence bundles, runbooks, backup/restore thinking, and production review flows.
• MPlusForm: validation-boundary and desktop-automation evidence with untrusted local files, optional Python sync, server-side approval, safe snapshots, Windows operations scripts, and trust-model docs.

Current Green Evidence

Last checked: 2026-07-03.

• OpsDesk Reviewer Replay CI is green on ace5c0c; the repo is public, pinned first, and routes to First Backend Role Fit.
• DriveDesk Core CI and Pages deploy are green on ce110ec; Business Intake API Handoff is published, with scheduled validation and public demo health tracked by workflow pages.
• AI Ops Workflow Kit CI is green on 0cb94e0; the Hiring Signal Brief compresses RAG quality, approval, CRM-safe handoff, retry/dead-letter, idempotency, and dry-run boundaries, the Business Scenario Replay shows business input -> backend route -> RAG/approval/CRM evidence, the First Slice Playbook routes RAG/transcript, CRM handoff, human approval, and reliability slices, the demo walkthrough shows transcript -> RAG -> approval -> CRM-safe handoff, and the live app SHA 1a83406 shows storage=postgres, rag_eval=2/2, restart persistence, and reviewer observability.
• AI Ops Workflow Kit GitHub metadata foregrounds AI sales/support workflow backend evidence and routes the repository homepage to the demo walkthrough.
• DeployMate CI and public evidence bundle are green on b139a9a; release maintenance status and release-secrets audit remain green.
• Profile evidence freshness is checked through main profile/evidence source, gh-pages static Pages source, and Profile Funnel Audit. Reviewers should use the latest successful Profile Funnel Audit run and current repository source instead of relying on stale hard-coded run IDs. Current verification covers recruiter-facing source files, public-safe static route files, and profile audit checks through GitHub branches and GitHub Actions. Manual live route checks are kept in Live Profile Smoke.
• GitHub profile evidence metadata audit runs inside Live Profile Smoke for pinned repositories: opsdesk-lite, drivedesk-core, ai-ops-workflow-kit, deploymate, AlexGerlitz, and MPlusForm.
• Live Profile Smoke includes rendered GitHub profile checks for the bio, recruiter shortcut, LinkedIn contact path, message reason router, Recruiter Filter Map, Message Triggers, pinned repositories, PDF resume, social cards/images, and review paths.
• MPlusForm Public Verification is green on e0e6876.
• Work With Me and Role Targets are published reviewer routes.

LinkedIn Public Route Alignment

This section records stable public alignment, not browser state or private profile-maintenance notes.

• Headline direction: Python Backend / API Automation with FastAPI, PostgreSQL, API/CRM integrations, and QA/API Python support.
• Preferred search titles: Back End Developer, Python Developer, Quality Assurance Automation Engineer, Integration Engineer, Application Support Engineer.
• First-role title support: Junior Backend Developer, Junior Python Developer, Support Engineer with Python, QA Automation Python, and API Testing / Test Automation Engineer.
• Target role lane: Remote-capable Junior Python Backend / API Automation first; QA/API Python, CRM/API Integration, Application Support Engineer with Python, and Internal Tools are adjacent lanes when the work is backend/API-heavy.
• About direction: Python backend/API automation and internal tools for real business workflows, OpsDesk Reviewer Replay as fresh code proof, Autoschool Intake/Admin as real-work workflow evidence, AI tools as an engineering accelerator, and Docker/CI as handoff evidence.
• Experience basis: Autoschool54 / DriveDesk backend and application-support work since March 2024, represented publicly through synthetic evidence and the Autoschool Intake/Admin review path.
• Featured route target: GitHub Recruiter Handoff at GITHUB_RECRUITER_HANDOFF.md, OpsDesk Reviewer Replay, Backend/API Work Samples, LinkedIn Recruiter Packet, First Backend Role Fit, Autoschool Intake/Admin work sample, and PDF resume.
• Skill surface: Python, FastAPI, PostgreSQL, REST/OpenAPI, GitHub Actions, Docker Compose, QA/API Python, systems integration, CRM/API integration, RAG workflow evidence, and runbooks tied to public evidence.

Public boundary: the stable proof route is GitHub/Pages first. Live LinkedIn settings can change, so this pack avoids recording browser-state details and keeps the public reviewer path focused on inspectable work samples.

LinkedIn Recruiter Signal

Public recruiter signal is ready for LinkedIn profile views, role screens, and hiring-manager forwards without depending on a live post.

• Role lane: Remote-capable Junior Python Backend / API Automation first; QA/API Python, CRM/API Integration, Application Support Engineer with Python, and Internal Tools are adjacent lanes when the work is backend/API-heavy.
• Search title fit: Junior Backend Developer, Junior Python Developer, Back End Developer, Python Developer, Python Automation Engineer, QA Automation Python, Integration Engineer, CRM/API Integration Engineer, and Internal Tools Engineer.
• Skill filters: FastAPI, GitHub Actions, RAG, Python, PostgreSQL, Docker, CRM/ERP/API integration, OpenAPI, workflow integration, and QA Automation Python.
• First review route: GitHub Recruiter Handoff -> OpsDesk Reviewer Replay -> DriveDesk Business Intake API Handoff -> LinkedIn Recruiter Packet -> First Backend Role Fit -> PDF resume. Use Recruiter Review Pack and AI Backend Review Pack after backend fit is clear.
• Boundary: AI workflow evidence and Docker/CI handoff support the backend/API claim; cloud/platform ownership stays secondary unless the role gives a reviewed support boundary.

Source-Backed Activation Checks

Checked on 2026-07-03.

• LinkedIn route: keep search titles and profile copy aligned with first-role Python/backend, QA/API, integration, application-support, and internal-tools screens. AI remains review evidence inside backend, QA/API, and integration work rather than the first title filter.
• LinkedIn Skills: keep Python, REST APIs, OpenAPI, GitHub, Systems Integration, FastAPI, Docker, PostgreSQL, and QA/API terms tied to public evidence. Do not treat DevOps as the main role claim.
• LinkedIn Featured: keep Featured focused on short recruiter review paths first: GitHub Recruiter Handoff, OpsDesk Reviewer Replay, Backend/API Work Samples, LinkedIn Recruiter Packet, First Backend Role Fit, Autoschool Intake/Admin work sample, and PDF resume; keep Recruiter Review Pack and DriveDesk AI Operator as deeper proof after fit.
• GitHub profile: keep the profile README, GitHub Recruiter Handoff, pinned repos, Pages routes, and PDF resume aligned because they are the first public evidence surface.
• Recruiter screen: lead with Python backend/internal tools, QA/API Python, support-with-Python, integration/API/CRM, or AI workflow with backend/API proof plus one public work sample instead of a generic junior label. Keep compensation discussion in private outreach.
• Remote-team screen: keep English-first docs, async review paths, integration contracts, privacy boundaries, CI/live smoke, runbooks, and handoff quality visible while keeping the first screen role/workflow focused.

Evidence Signals

• FastAPI/PostgreSQL backend and integration boundaries.
• Public demo, CI, OpenAPI, tests, and docs.
• AI workflow/RAG ingestion from documents, call audio, and transcripts, a committed business scenario replay, demo walkthrough, deterministic RAG quality eval, privacy redaction tracked through the AI Ops privacy boundary, OpenAI/Claude/Gemini and transcription provider boundaries tracked through AI Ops public evidence status, retrieval, lead scoring, approvals, and CRM handoff boundary.
• Release gates, runbooks, recovery steps, and closed incident trail.

Current Principle

The point is not a perfect screenshot. The useful evidence is that code, docs, CI, release gates, runbooks, recovery steps, and closed incident trail are visible enough for a technical reviewer to evaluate behavior.