Human capability
in the age of AI.
THE HCLAB is a modern research and systems platform exploring artificial intelligence, cognition, learning, adaptation, and the future of intelligent work through experimentation, media, frameworks, and public research.
Research amplification across six domains — from AI literacy to governance and systems.
Six domains
One platform for human capability
From foundational AI literacy to applied systems and governance — each domain is a different lens on the same question.
Learn
AI literacy and foundational learning for every level.
Beginners, professionals, leaders, educators.
Research
Research artifacts — frameworks, working papers, experiments, and original intellectual property.
Researchers, leaders, and the intellectually curious.
Systems
Technical experimentation and applied AI engineering.
Developers, engineers, researchers.
Governance
Responsible AI adoption and organizational strategy.
Organizations, leaders, consultants.
Media
Podcast, video, and media as research dissemination infrastructure.
Listeners, viewers, and lifelong learners.
Resources
Operationalized research outputs — instruments, guides, citations, and implementation resources.
Practitioners putting ideas to work.
Labs
Systems validation, AI infrastructure research, and reproducible experimentation.
Developers, ML engineers, and technically curious practitioners.
Research in action
Active investigation across the lab
Studies, experiments, frameworks, and findings — a living research ecosystem, not a static archive.
Active studies
- RecruitingPurposeful Friction Design Framework (PFDF) PilotSession 1 (~25 min): surveys and a critical-analysis writing task. Session 2 (~15 min, complete when ready): retention and transfer checks. You will be randomly assigned to one of three AI conditions.
- RecruitingHuman-AI Collaboration Baseline StudyHelp us understand how AI tools affect human judgment, revision patterns, and final written output — a 15-minute research session with optional AI assistance.
Recent findings
- Lab reportMay 22, 2026Running a 70B model on Apple Silicon, end to endA reproducible local inference setup with quantization, KV-cache tuning, and honest token-throughput numbers.
- Research noteMay 11, 2026An AI readiness rubric for mid-size organizationsFive dimensions — data, talent, governance, workflow, and culture — scored against realistic adoption stages.
- Lab reportMay 4, 2026Evaluating RAG retrieval with adversarial questionsWhat happens to answer quality when the right chunk is present but buried under near-duplicates.
Current experiments
- Lab reportMay 22, 2026Running a 70B model on Apple Silicon, end to endA reproducible local inference setup with quantization, KV-cache tuning, and honest token-throughput numbers.
- Lab reportMay 4, 2026Evaluating RAG retrieval with adversarial questionsWhat happens to answer quality when the right chunk is present but buried under near-duplicates.
- Lab reportApr 15, 2026Embedding model shootout: accuracy vs. speed on CPUA head-to-head comparison of six open embedding models on retrieval accuracy, latency, and memory footprint — all measured on the same CPU-only machine.
Featured frameworks
- v1.0Cognitive AgencyPreserving human judgment, initiative, and ownership of thinking as intelligent systems take on more of the work.
- v1.0Purposeful FrictionWhy the right amount of difficulty — deliberately designed — produces durable learning and better decisions.
- v1.0The AI TaxThe hidden, compounding costs of delegating cognition: skill atrophy, verification overhead, and eroded trust.
Participate
Contribute to ongoing research
Take an assessment, join The Signal for study updates, or explore frameworks that shape our experimental work.
Research artifacts
Institutional frameworks from the lab
Versioned intellectual property — built through observation, experimentation, and public dissemination.
Cognitive Agency
Preserving human judgment, initiative, and ownership of thinking as intelligent systems take on more of the work.
Read the frameworkPurposeful Friction
Why the right amount of difficulty — deliberately designed — produces durable learning and better decisions.
Read the frameworkThe AI Tax
The hidden, compounding costs of delegating cognition: skill atrophy, verification overhead, and eroded trust.
Read the frameworkLatest from the lab
Essays, experiments, and episodes
A running feed of new thinking across every domain — research notes, system updates, and media.
The capability gap nobody is measuring
Productivity dashboards are rising while underlying human capability quietly declines. Here is what we should track instead.
Running a 70B model on Apple Silicon, end to end
A reproducible local inference setup with quantization, KV-cache tuning, and honest token-throughput numbers.
Episode 14 — Learning science meets generative AI
A conversation on retrieval practice, desirable difficulty, and what tutoring tools get wrong about memory.
An AI readiness rubric for mid-size organizations
Five dimensions — data, talent, governance, workflow, and culture — scored against realistic adoption stages.
Evaluating RAG retrieval with adversarial questions
What happens to answer quality when the right chunk is present but buried under near-duplicates.
Prompting is not the skill — framing is
A short, practical walkthrough of how to decompose a real task before you ever touch a model.
Our mission
Intelligent systems should make people more capable — not less.
THE HCLAB is a modern research institution studying how humans learn, think, adapt, and maintain capability in an era shaped by artificial intelligence — through continuous experimentation, public dissemination, and institutional frameworks.
Augment, don't replace
AI should expand human judgment, learning, and agency — not quietly erode them.
Capability over output
Short-term productivity is easy to measure. Durable human capability is what compounds.
Research informs practice
Every framework is built to be used — by individuals, teams, and organizations.
Assessments
Where do you stand?
Interactive evaluations to measure your AI readiness, literacy, and cognitive agency — with personalized recommendations.
AI Readiness Assessment
Evaluate your organization's readiness to adopt and scale AI systems across strategy, data, talent, and culture.
AI Literacy Assessment
Gauge your personal understanding of AI systems, their capabilities, limitations, and how to work effectively alongside them.
Cognitive Agency Assessment
Understand how much cognitive ownership you maintain when working with AI — and where delegation may be quietly eroding your judgment and skill.