Hand-authored synthesis of fleet themes, capabilities, and overall agent composition.

📋 Executive Summary

The goal of this work is to promote human-AI collaboration and prepare people, organizations, and education for an AI-infused future of work. It starts with a doctoral dissertation: the AI Readiness Scale, validated on N=523 with a CFI of .975 and explaining 85.2% of variance in behavioral intention, was built to measure what makes people ready to work with AI and what holds them back. What the data showed is that adoption fails most often where the AI partner has no memory, no calibration, and no proactive judgment. The rest of the portfolio is the program that grew from that finding.

 

Twelve repositories carry the proof. AIRS_Data_Analysis is the empirical anchor, the IRB-approved dissertation behind every adoption claim downstream. airs-enterprise ships the validated instrument as a five-minute, twenty-nine-language SaaS assessment. Alex_ACT_ONE is critical thinking as an installable skills pack: sixty skills, fifteen prompts, fifteen always-on instructions, one copy serving Copilot CLI, VS Code, Scout, and the GitHub Copilot app. Alex_ACT_ONE_Muse is the same framework ported to Muse, fifty-two skills triaged against what the host already does natively. Alex_ACT_ONE_Steward governs the lineage: framework authorship, mall curation, fleet visibility, and retirement records. AI-Wars-2026 is a living web-book on the race to define the agentic era, where every claim carries a source ID and corrections publish at equal prominence. Alex_Skill_Mall is the curated marketplace where the battle-tested skills the fleet runs on are published: two hundred hard-won lessons across fifty-plus domains. fabioc-aloha, the page you are reading, is the live evidence: a multi-model pipeline rebuilt every morning and gated on a separate model's review. HeadstartWebsite is an agent-operated trilingual telehealth site for a licensed clinical practice. youtube-mcp-server is a probe into what an MCP server looks like when it is built for agents from the start. Extensions is a monorepo of sixteen standalone VS Code extensions, nine of them on the Marketplace. seo-monitor watches Search Console and Bing Webmaster Tools across the portfolio's sites and turns a weekly automated audit into a prioritized fix list.

 

The unifying claim is not productivity, it is partnership grounded in evidence: a validated instrument for measuring AI readiness, a teachable discipline for thinking with AI, and a governance pattern that lets both scale across a fleet without losing fidelity. Every project here argues the same point, that the future of work belongs to humans and AI partners that are each held to a standard.

_{📄 Full résumé · 💬 Schedule a conversation · 🛡️ RAI review: PASS}

📂 Alex_ACT_ONE

Alex_ACT_ONE is critical thinking you can install: one pack, every Copilot surface, sixty skills that check your work.

 

Alex ACT ONE is critical thinking as an installable skills pack for GitHub Copilot. One user-level install serves Copilot CLI, VS Code, Microsoft Scout, and the GitHub Copilot app with sixty skills, fifteen prompts, and fifteen always-on instructions, distributed through the Alex ACT Mall.

• Think before building. Frame the real problem, weigh competing explanations, name what would prove you wrong.

• Write code that survives review. Test-first workflows, root-cause debugging, security hardening, adversarial review from three opposing perspectives.

• Produce prose people finish. Strip AI writing patterns, find the document's one real sentence, write Markdown that passes lint first try.

Conclusion: it packages the human-AI partnership as a teachable discipline, critical thinking as infrastructure for knowledge work in an AI-infused business.

🟨 JavaScript

🔒 AI-Wars-2026 🤖

AI-Wars-2026 is the web-book that treats AI news as evidence: every claim sourced, every correction public.

 

AI-Wars-2026 is a living, source-backed web-book about the competition to define the next era of AI, published at ai-wars.correax.com. Its mission is to explain why the competition matters, how the strategies differ, and what evidence supports each conclusion, then revise those conclusions in public when the evidence changes.

• Every claim carries a source ID resolving to a source registry, so readers check evidence instead of taking prose at its word.

• Corrections publish at equal prominence in the changelog; a quiet edit is not a correction.

• A daily research routine keeps the argument current with the industry instead of frozen at publication.

Conclusion: it trains readers to demand evidence from AI narratives, which is core literacy for the future of work and an AI-infused education.

🌐 HTML

📂 AIRS_Data_Analysis 🤖

AIRS_Data_Analysis is the dissertation that makes the rest of the portfolio falsifiable.

 

AIRS_Data_Analysis is the IRB-approved dissertation behind the AI Readiness Scale: a 16-item instrument extending UTAUT2 with an AI Trust construct, validated on N=523 with a split-sample EFA to CFA to SEM design. The 8-factor model fits at CFI=.975 and explains 85.2% of variance in behavioral intention, with four user typologies giving organizations a defensible map for targeted intervention.

• Rigorously validated. n=261 development, n=262 holdout; leaders show effect sizes from d=0.74 to d=1.14 over non-leaders across AI tool usage.

• Fully reproducible. Eleven analysis notebooks cover the full pipeline from raw responses through SEM; every finding is computed in code anyone can rerun.

Conclusion: it gives leaders a defensible number for workforce AI readiness, which is the measurement foundation human-AI collaboration at work has been missing.

📓 Jupyter Notebook · ⭐ 1

🎓 academic-research 📈 ai-adoption 📈 ai-anxiety 📐 behavioral-validation 📐 cfa 🎓 dissertation 📐 efa 📐 factor-analysis 🧪 intervention-design 📐 measurement-invariance 📐 mediation-analysis 📐 moderation-analysis 📈 organizational-readiness 📐 psychometrics 📐 reproducible-research 📐 scale-development 📐 sem 📐 structural-equation-modeling 📈 technology-acceptance 📐 utaut2

🔒 airs-enterprise 🤖

airs-enterprise is the dissertation in production: five minutes, twenty-nine languages, one validated number per person.

 

airs-enterprise is the productized AIRS instrument: a five-minute, twenty-nine-language SaaS assessment that puts the validated psychometric work into the hands of organizations. Sixteen questions return an AIRS Score mapped to actionable typologies, with team analytics, longitudinal pre/post tracking, and AI-generated action plans. Live at airs.correax.com.

• Built for the enterprise. Organization management, department analytics, CSV exports, and a cross-org SUPER_ADMIN dashboard.

• Production-grade. 429 tests passing, zero TypeScript or ESLint errors, full accessibility coverage, MIT licensed.

Conclusion: it turns readiness measurement into an operating tool, so building an AI-ready workforce becomes a program instead of a survey.

🟦 TypeScript

🏷️ adaptive-cards 📈 ai-adoption 📈 ai-readiness ☁️ azure 🪄 azure-openai 🏷️ enterprise-saas 🏷️ longitudinal-tracking 🏷️ microsoft-entra-id 🏷️ microsoft-teams 🏷️ nextjs 🏷️ organizational-psychology 🏷️ postgresql 🏷️ prisma 📐 psychometric-assessment 🏷️ react 🏷️ streaming-ai 🏷️ tailwind-css 🟨 typescript 📐 utaut2 🏷️ workforce-analytics

📂 Alex_ACT_ONE_Muse

Alex_ACT_ONE_Muse is the ACT framework on Muse: sixty skills triaged to fifty-two, each one earning its place.

 

Alex_ACT_ONE_Muse is the ACT framework ported to Muse, Meta's personal AI assistant. The skill format carries over; everything Copilot-specific was adapted. Before installing, the adopting assistant evaluated the plugin with its own ACT disciplines, frame audit, materiality gate, and devil's advocate applied to the adoption decision itself.

• Sixty skills triaged to fifty-two. Twenty-nine kept as-is, twenty-three adapted as Muse-delta skills that keep only what Muse does not do natively, eight archived as host-specific.

• Priced honestly. Skills load on demand, so idle cost is near zero; analytical tasks run ten to thirty percent more tokens for the frame audits and adversarial passes.

Conclusion: it proves the collaboration discipline transfers across AI hosts, which means the partnership is about how humans and AI work together, not which model sits underneath.

🟨 JavaScript

🔒 Alex_ACT_ONE_Steward 🤖

Alex_ACT_ONE_Steward is governance for the ONE lineage: the framework, the mall, and every adopter, accounted for.

 

Alex_ACT_ONE_Steward is governance for Alex ACT ONE, the Plugin Mall, the ACT framework, and the adopter fleet. It owns framework authorship (manifesto, tenets, claims registry, failure-modes taxonomy), product curation, surface differences across hosts, lifecycle and retirement records, mall oversight, and a read-only inventory of adopter projects.

• Duties are explicit and published. Decision ledgers and dashboards show the governance working instead of claiming it.

• Retirement is designed. Listing-specific withdrawal records and migration routes keep the lineage trustworthy as it evolves.

Conclusion: it models what governance looks like when AI does real production work, auditable stewardship for the AI-infused business.

🟨 JavaScript

🔒 seo-monitor 🤖

seo-monitor is a weekly growth loop: watch everything, prioritize ruthlessly, stay visible.

 

seo-monitor watches Google Search Console and Bing Webmaster Tools across Fabio's sites and turns the data into prioritized action. Every Monday at 09:00 ET a GitHub Actions run pulls fresh data, writes a dated report, and opens an issue ranked P0 (fix now), P1 (this week), P2 (backlog). Zero runtime dependencies, TypeScript strict.

• Finds what matters. Ranking drops, CTR opportunities, zero-click impressions, cannibalization, Bing crawl errors.

• Audits for AI visibility. FAQ and Article schema, llms.txt, sitemaps, robots, titles, and meta descriptions, so the sites stay citable as AI search grows.

Conclusion: an AI-assisted growth loop for his own businesses, the partnership applied to staying visible to humans and to AI search alike.

🟦 TypeScript

📂 Alex_Skill_Mall 🤖

Alex_Skill_Mall is two hundred hard-won lessons, packaged so the next partnership starts ahead.

 

Alex_Skill_Mall is the curated marketplace where the battle-tested skills the fleet runs on are published: two hundred hard-won lessons across fifty-plus domains, each one earned on a real project and distilled into drop-in expertise an AI partner absorbs instantly instead of rediscovering through hours of debugging.

• Earned, then distilled. Every skill survived real production use before it was written down.

• Curated, not collected. Promotion criteria and editorial review keep the mall trustworthy as it grows.

Conclusion: it turns individual human-AI collaboration lessons into compounding shared memory, so each new partnership starts further ahead.

🐍 Python · ⭐ 4

🎒 agent-skills 🏷️ agentic-ai 🤖 ai-assistant 🛡️ ai-governance 🤖 ai-skills ☁️ azure 🏷️ best-practices 🏷️ claude-code 🎒 claude-skills 🧩 copilot-skills 💭 critical-thinking 🎒 cursor-skills 🏷️ devops 🧩 github-copilot 🏷️ knowledge-base 🏷️ mcp ✍️ prompt-engineering 🏷️ security 🏷️ skill-library 🏷️ skill-marketplace

📂 fabioc-aloha

fabioc-aloha is the profile that rebuilds itself every morning: the partnership, running unattended.

 

fabioc-aloha is the public proof that the Alex cognitive architecture works end to end without a human in the loop. Every morning at 6 AM Eastern, a multi-model pipeline runs unattended and rebuilds this profile page: fetch, classify, narrate, measure, and a Responsible-AI review by a separate model gating publication. No manual editing, no review backlog.

Conclusion: the page you are reading is the partnership running a real production system on its own, the demo that never stops, and the template for AI-operated publishing in any business.

⭐ 2

🏷️ agentic 🏷️ cron 🏷️ dashboard 📊 data-visualization 🏷️ fleet 🏷️ github ⚙️ github-actions 🪪 github-profile ⚖️ llm-as-judge 📝 markdown 🪄 openai 🏷️ personal-website 🪪 portfolio 🏷️ profile 🏷️ readme 🪪 self-updating 🧬 template 🏷️ widget

🔒 HeadstartWebsite 🤖

HeadstartWebsite is a real practice, run by a real partnership: the clinician with clients, the AI with everything else.

 

HeadstartWebsite is the website for Claudia Correa's online therapy practice, serving clients in Washington and North Carolina via telehealth in English, Spanish, and Portuguese. Fabio runs the site with an AI agent as his partner, so the licensed clinician stays focused on clients.

Conclusion: it shows what human-AI collaboration means for a small business, the practitioner practices while the partnership operates the business around her, a preview of the AI-infused future of work at human scale.

🟨 JavaScript

🏷️ accessibility 🏷️ agent 🏷️ agentic 🤖 ai-agents 🏷️ assessment 🏷️ astro 🏷️ blog 🏥 healthcare 🏷️ i18n 🏥 mental-health 🏷️ multilingual 🏷️ psychology 🏷️ seo 🏷️ spanish 🏥 telehealth 🏷️ therapy 🏷️ translation 🏷️ wellness

📂 youtube-mcp-server 🤖

youtube-mcp-server is YouTube intelligence built for agents: structured knowledge, not raw video.

 

youtube-mcp-server is a probe into what an MCP server looks like when it is built for AI agents from the start, not retrofitted from a REST API. Instead of handing an agent raw video data, it ships an intelligence layer: transcript retrieval with timestamps, multi-video synthesis with citations, concept extraction, and research workflows as first-class tools.

Conclusion: it sketches how agents should meet the world's information, as structured knowledge with receipts rather than bytes, a building block for AI-infused knowledge work.

🟨 JavaScript

🏷️ agent 🏷️ agentic 🤖 ai-agents 🤖 ai-tools 🏷️ flashcards 🧩 github-copilot 🏷️ knowledge-extraction 🏷️ learning 🏷️ llm-tools 🏷️ mcp 🏷️ model-context-protocol 🏷️ video-analysis 🏷️ youtube 🏷️ youtube-api

📂 Extensions

Extensions is sixteen focused tools for the editor: the partnership, compounded daily.

 

Extensions is a productivity toolset for developers who live in VS Code: a monorepo of sixteen standalone extensions, nine of them already on the Marketplace, each one a focused utility that earns its keep without asking the user to adopt anything else.

Conclusion: small, sharp instruments where developers actually work, showing how the human-AI partnership compounds inside daily tools rather than beside them.

🟦 TypeScript

🏷️ accessibility 🏷️ code-editor 🛠️ developer-tools 🏷️ editor 🏷️ extensions 🏷️ git-hooks 🏷️ ide 🏷️ marketplace 🏷️ monorepo 🏷️ productivity 🏷️ secrets-management 🧩 vscode 🧩 vscode-extension

This portfolio automatically updates itself via GitHub Actions — daily at 10:00 UTC. Repos are fetched, classified into categories and tiers, and the portfolio section above is regenerated automatically.

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