Step 1
Build your profile once
Organize work history, projects, credentials, writing, and evidence inside ProfOS so your application data starts from a structured record.
ApplyPilot by ProfOS
Application autofill that starts from your record and still keeps you in control.
ApplyPilot is the local-first companion for repetitive job applications. Build your professional record in ProfOS, export a safe profile, review every match, and fill forms without turning your application process into blind automation.
Core ApplyPilot behavior is deterministic. It scans fields, maps them to structured profile data, applies saved corrections, and waits for review before filling. AI is not required for the main workflow.
Core use
Local
Works without mandatory cloud sync
Submission
Manual
No auto-submit behavior
Risk posture
Review-first
Sensitive fields stay off by default
What it is
A practical browser tool, not an application bot.
Step 2
Export only safe profile data
ApplyPilot uses a reviewable JSON export. Sensitive demographic, salary, and legal fields are left blank by default.
Step 3
Review every mapped field
The extension scans the page, proposes matches, and waits for approval before it fills anything.
Step 4
Fill forms without auto-submitting
ApplyPilot never sends an application, clicks submit, or fills high-risk fields unless you explicitly approve them.
Why it belongs here
ApplyPilot is one of the ways ProfOS reduces repeated professional labor.
The platform keeps your evidence, profile, privacy settings, and application materials organized. ApplyPilot turns that structured record into a reusable autofill companion. They are connected, but ApplyPilot still stays useful on its own and does not require live website access while filling forms.
Works now
Generic application formsGreenhouse-style formsLever-style formsDeterministic field mappingSaved reusable answersResume text importLocal correction learningCommon multilingual field labels
Safety boundaries
Local-first profile storage inside the extensionNo automatic application submissionNo default demographic autofillNo hidden cloud sync requiredNo server upload required for core use
Setup checklist
- 1. Download the extension bundle from this page.
- 2. In Chrome, open `chrome://extensions` and enable Developer Mode.
- 3. Use Load unpacked and choose the extracted `applypilot-extension/dist` folder.
- 4. Import your exported profile JSON from ProfOS or use the demo JSON here to test the workflow.
Support: sreid1118@gmail.com
Recent updates
What changed in the current public ApplyPilot build.
This section reflects the current download and public repo status so people can see what was improved recently instead of guessing from marketing copy.
Live runtime fill verification
The current bundle is now verified against browser-run fixture pages instead of only service-level tests, so scan and fill behavior is checked end to end.
Better multi-section reliability
ApplyPilot now re-finds fields through stronger DOM paths and can keep working when forms are broken into separate sections or rendered in less predictable layouts.
Resume import coverage expanded
Local import support continues to cover PDF, DOCX, text, HTML, RTF, and JSON, with an opt-in real-file verification path for checking actual resume extraction quality.
Demo export
See the exact JSON shape ApplyPilot imports.
This demo export is built from a real seeded profile inside ProfOS. It is here so people can inspect the format, test the extension, and understand what gets carried over.
ApplyPilot profile export
This JSON matches the local-first Chrome extension importer. Sensitive demographic and other high-risk fields stay empty by default. Contact details and references are included only when you export from your private ProfOS workspace.
{
"firstName": "Steven",
"lastName": "Reid",
"fullName": "Steven Reid",
"email": "",
"address": {
"city": "Manchester",
"country": "United States"
},
"links": {
"portfolio": "https://profos.net/professional/steven-reid",
"github": "https://github.com/RRG314",
"website": "https://profos.net/"
},
"preferences": {
"remotePreference": "Flexible",
"availabilityDate": "Open to aligned facility, systems, software, research, and collaboration opportunities"
},
"sensitive": {},
"education": [],
"workExperience": [
{
"id": "steven-tl-1",
"company": "Healthcare facility operations",
"title": "Facility engineer for healthcare, residential, and commercial building systems",
"startDate": "2025-01",
"description": "Maintains HVAC, plumbing, electrical, mechanical, fire alarm, sprinkler, generator, water, pool-treatment, and repair workflows with safety and compliance awareness."
},
{
"id": "steven-tl-2",
"company": "Vehicle conversion shop",
"title": "Vehicle accessibility modification technician",
"startDate": "2023-07",
"description": "Installed accessibility-focused vehicle systems including floor systems, ramps, brake lines, suspensions, and torque-controlled assemblies."
},
{
"id": "steven-tl-3",
"company": "Automotive sales",
"title": "Sales consultant and CRM user",
"startDate": "2021-09",
"description": "Managed customer communication, confidential records, CRM workflows, and sales process follow-through."
},
{
"id": "steven-tl-4",
"company": "Automotive facility operations",
"title": "Facility maintenance technician",
"startDate": "2020-11",
"description": "Built and followed maintenance plans for facility equipment, appliances, operations support, and customer-facing handoffs."
},
{
"id": "steven-tl-5",
"company": "Pet resort operations",
"title": "Head of facility maintenance and daycare manager",
"startDate": "2017-12",
"description": "Maintained a multi-building campus, supervised staff and contractors, handled construction/electrical/plumbing/HVAC/pool/well-water work, and trained team members."
}
],
"certifications": [],
"skills": [
"Accessibility",
"Algorithms",
"Application reuse",
"ApplyPilot",
"Auth",
"Benchmarking",
"Compliance",
"Confidentiality",
"CRM",
"Customer service",
"Diagnostics",
"Documentation",
"DOI",
"Electrical systems",
"Evidence organization",
"Facilities",
"Facility maintenance",
"Firebase",
"Frontend architecture",
"GitHub",
"HVAC",
"Leadership",
"Maintenance planning",
"Mathematics",
"Mechanical systems",
"Next.js",
"Numerical systems",
"Open source",
"Optimization",
"ORCID",
"Package design",
"Plumbing",
"Power tools",
"Preventive maintenance",
"Privacy controls",
"PRNG",
"Product workflow",
"Public site",
"PWA",
"Python",
"Python package",
"PyTorch",
"Regulatory compliance",
"Reproducibility",
"Research",
"Research identity",
"Research publishing",
"Research writing",
"Source integration",
"Spatial indexing",
"Stripe",
"Testing",
"Training",
"Troubleshooting",
"TypeScript",
"Web product",
"WebGL",
"Zenodo"
],
"projects": [
{
"id": "steven-ev-github",
"name": "RRG314 GitHub profile",
"url": "https://github.com/RRG314",
"description": "Public GitHub profile connecting multiple research, software, and web application repositories.",
"technologies": [
"GitHub",
"Open source",
"Documentation"
]
},
{
"id": "steven-ev-rge-app",
"name": "RGE-256 browser workbench",
"url": "https://rrg314.github.io/RGE-256-app/",
"description": "Browser workbench for RGE-256 with deterministic generation, diagnostics, documentation, validation notes, and export-oriented workflows.",
"technologies": [
"TypeScript",
"PWA",
"Diagnostics",
"PRNG"
]
},
{
"id": "steven-ev-rge-python",
"name": "rge256 Python package repository",
"url": "https://github.com/RRG314/rge256",
"description": "Standalone Python implementation of the RGE256 PRNG family with documented variants and research-use caveats.",
"technologies": [
"Python",
"Package design",
"Documentation",
"Testing"
]
},
{
"id": "steven-ev-topological-adam",
"name": "Topological Adam work",
"url": "https://github.com/RRG314/topological-adam",
"description": "Experimental PyTorch optimizer family with diagnostics, caveats, reproducible benchmark-oriented notes, and a published PyPI package for installable setup with Python 3.8+.",
"technologies": [
"PyTorch",
"Optimization",
"Research",
"Documentation",
"Python package"
]
},
{
"id": "steven-ev-rdt-spatial-index",
"name": "RDT Spatial Index",
"url": "https://github.com/RRG314/rdt-spatial-index",
"description": "Research-grade adaptive spatial indexing repository with readable reference implementations, practical fast paths, optional compiled backends, benchmarks, tests, and reproducibility artifacts. This is one of the clearest examples of higher-complexity engineering work in the profile because it combines algorithm design, implementation layers, benchmarking, packaging, and documentation.",
"technologies": [
"Python",
"Spatial indexing",
"Benchmarking",
"Reproducibility",
"Package design"
]
},
{
"id": "steven-ev-rdt-algorithm",
"name": "Recursive Division Tree algorithm",
"url": "https://github.com/RRG314/Recursive-Division-Tree-Algorithm--Preprint",
"description": "Public preprint repository for the Recursive Division Tree algorithm, including the paper, implementation notebook, benchmark package, and DOI-backed citation record. It is the clearest source-backed artifact for the original RDT algorithm itself.",
"technologies": [
"Algorithms",
"Mathematics",
"Research",
"Benchmarking",
"Documentation"
]
},
{
"id": "steven-ev-rdt-kernel",
"name": "RDT algorithm and kernel work",
"url": "https://github.com/RRG314/rdt-kernel",
"description": "Experimental Recursive Diffusion Transform Kernel work with PyTorch implementation notes, algorithm framing, benchmark documentation, and recursive systems analysis. This is one of the more technically demanding research tracks in the profile because it connects theory, implementation detail, and reproducible technical evidence.",
"technologies": [
"PyTorch",
"Numerical systems",
"Research",
"Algorithms"
]
},
{
"id": "steven-ev-worldexplorer",
"name": "WorldExplorer3D application",
"url": "https://worldexplorer3d.io/",
"description": "A browser-based 3D exploration application with WebGL, Firebase, authentication, Firestore, and Stripe-oriented product architecture. It represents higher-complexity interactive systems work that combines graphics, state, account flows, and deployment-minded product structure.",
"technologies": [
"WebGL",
"Firebase",
"Auth",
"Stripe",
"Frontend architecture"
]
},
{
"id": "steven-ev-billbounty",
"name": "BillBounty live platform",
"url": "https://billbounty.net/",
"description": "A public product workflow built around bill-scanning, bounty-style task handling, and Stripe-backed user flows. It is included here as evidence of product-oriented software work beyond research repositories, with a stronger emphasis on usability, workflow design, and practical deployment.",
"technologies": [
"Next.js",
"Stripe",
"Product workflow",
"Frontend architecture"
]
},
{
"id": "steven-ev-sidestreet",
"name": "SideStreet.net platform",
"url": "https://sidestreet.net/",
"description": "A public-facing site included here as part of Steven Reid's shipped web work. It helps round out the profile with another live product surface and shows continuity between research-oriented systems work and practical public web delivery.",
"technologies": [
"Web product",
"Frontend architecture",
"Public site"
]
},
{
"id": "steven-ev-orcid",
"name": "ORCID research identity",
"url": "https://orcid.org/0009-0003-9132-3410",
"description": "ORCID identifier captured from local research materials for connecting publication and research evidence.",
"technologies": [
"ORCID",
"Research identity"
]
},
{
"id": "steven-ev-zenodo",
"name": "Zenodo DOI-backed research records",
"url": "https://rrg314.github.io/papers",
"description": "Local papers index references DOI-backed Zenodo records for RDT, recursive entropy, RGE-256, Topological Adam, and related research work.",
"technologies": [
"Zenodo",
"DOI",
"Research writing"
]
},
{
"id": "steven-ev-professional-os",
"name": "ProfOS source deduplication project",
"url": "https://profos.net/",
"description": "This platform itself is part of the portfolio: it is being used to consolidate profile data, evidence, source links, structured exports, and application reuse into one candidate-owned system. That makes it both a product artifact and a direct example of the problem it is meant to solve.",
"technologies": [
"Next.js",
"Privacy controls",
"ApplyPilot",
"Evidence organization"
]
}
],
"references": [],
"resumeFile": {
"name": "Steven Reid resume evidence",
"type": "profile-derived",
"updatedAt": "2026-07-10T00:57:59.611Z"
},
"savedAnswers": [
{
"id": "steven-reid-answer-professional-summary",
"question": "Tell us about yourself.",
"answer": "Steven Reid's professional record brings together facility systems work, accessibility-focused mechanical work, customer-facing operations experience, public software projects, and research publishing into one structured home. Instead of scattering that work across disconnected resumes, websites, repositories, and paper trails, this profile organizes it into a candidate-owned record with evidence, context, connected sources, and visibility controls. The public-facing view stays selective on purpose: it highlights demonstrated work, interdisciplinary capability, and current direction while keeping sensitive personal details private by default.",
"tags": [
"summary",
"profile"
]
},
{
"id": "steven-reid-answer-interest",
"question": "Why are you interested in this role?",
"answer": "I look for roles where the work can be evaluated through real evidence instead of only a rewritten resume. My strongest documented areas right now are Accessibility, Algorithms, Application reuse, ApplyPilot, Auth. I am currently building toward Facility Engineer / Maintenance Supervisor work in Facilities and healthcare operations.",
"tags": [
"interest",
"review-required"
]
},
{
"id": "steven-reid-answer-value",
"question": "What makes you a strong fit?",
"answer": "My profile is organized around inspectable work rather than broad claims. Employers can review finished projects, supporting evidence, and the context behind how I approach Accessibility, Algorithms, Application reuse, ApplyPilot, Auth. Recent work includes RRG314 GitHub profile, RGE-256 browser workbench, rge256 Python package repository.",
"tags": [
"fit",
"evidence-backed"
]
}
]
}Use it with the full platform
ProfOS handles the record. ApplyPilot handles the repetitive form work.
The strongest workflow is to keep your work current inside the platform, then export only what you want ApplyPilot to use. That keeps your public page, employer discovery, packets, and application materials aligned.