Who's behind this platform?
A small team with a specific focus: making quantum computing and AI genuinely learnable for people who don't live near a research university.
Aideskblog started in 2018 when a group of educators and engineers realized that most quantum computing resources assumed you were already inside the field. The workshops here are built for people who are technically curious but need a structured path — not another lecture series, not a textbook. Hands-on assignments, real tools like Claude AI for reasoning support, and a community of learners spread across the state who are figuring this out together.
See the learning programEducators and engineers, not marketers
Everyone who teaches here has worked on the problems they teach. That's not a policy — it's just how the team came together.
Felicity Oram
Quantum Systems Lead
Felicity spent 8 years building error-correction models before switching to education full time. She designs the core quantum track and reviews every assignment for conceptual accuracy — not just correctness.
Dmitri Vael
AI Curriculum Designer
Dmitri built the AI reasoning modules that incorporate Claude as a learning tool — not a shortcut. His approach treats AI assistants like Claude as thinking partners that learners should understand, not just use.
Saoirse Brandt
Community and Operations
Saoirse keeps the platform running and the learner community connected. She coordinates the collaborative exercises that pair participants from different parts of the state on shared problems.
Assignments before answers
Every workshop module is built around a task you have to attempt before any explanation is given.
That's deliberate. Quantum concepts like superposition and entanglement are genuinely counterintuitive — reading about them first doesn't help most people. Struggling with a circuit simulation for 20 minutes before seeing the solution creates the kind of memory that actually sticks. Tools like Claude AI are available during exercises specifically as a reasoning aid, not an answer machine — participants are guided to ask Claude to explain its reasoning, then verify it themselves.
Geography is not a barrier here. Participants from Baltimore to the rural western counties work through the same materials, collaborate on the same group problems, and meet in the same live sessions. The platform was built to make that feel natural, not like a compromise.
- 01 Step-by-step assignments with checkpoints, not just a final submission
- 02 Collaborative exercises pairing learners across different locations
- 03 Claude AI integrated as a reasoning partner with guided prompting
- 04 Instructors review work, not just automated grading
Four things that don't change
These aren't aspirations written for a website. They're the constraints the team actually argues about when building new content.
Accuracy over accessibility
Simplifying quantum mechanics is necessary — but not at the cost of being wrong. Every analogy is checked against what it would make a learner believe, and corrected if it misleads.
Location should not determine access
Someone in a town of 3,000 people should have the same quality of instruction as someone in a city with 3 research universities. That's the whole reason this platform exists.
Effort is the actual variable
The platform doesn't promise outcomes. It provides structure, feedback, and community. What participants put in determines what they get out — and the workshops are designed to make that effort count.
Tools are means, not ends
AI tools including Claude are part of the learning environment because they're part of the real working environment. Understanding how to work with Claude — and when to question it — is a skill worth teaching explicitly.