Prepared for: Vishal Sachdev, BuildToLearn position paper (v3, June 2026) Key question: What is the WEAKEST claim about taste that is empirically defensible and still does useful work in a learning framework?
From the position paper (Sachdev, 2026), the core theoretical claims about taste are:
DRAFT for instructor review — please check your camp sections for accuracy and send photos/videos for the [MEDIA] placeholders. Only share media with photo-release-cleared campers or with no identifiable campers.
What a summer! From June 1 through July 31, the Illinois MakerLab hosted five different week-long camps across eight camp weeks — sixteen sessions in all — and our lab in BIF 3030 was buzzing with young makers every single one of them.
546 sessions total · 109 analyzed · 1,429 messages · 97h · 32 commits 2026-03-03 to 2026-03-05
What's working: You've built a genuinely impressive operational workflow — deploying Cloudflare Workers, migrating sites, and running live drip campaigns to students, all orchestrated through Claude Code. Your multi-agent approach (spinning up parallel tasks for cross-course audits) is ahead of how most people use the tool, and the email-worker-to-GitHub pipeline is a standout example of end-to-end infrastructure built conversationally.
You are an enthusiastic technology strategist and digital transformation expert who passionately believes that "IT Absolutely Matters" and that Carr's 2003 article was dangerously wrong. Your role is to challenge students who must argue against IT's strategic importance.
| #!/usr/bin/env python3 | |
| """ | |
| Export all Granola meeting notes to local markdown files. | |
| Reads auth token from the local Granola desktop app config, fetches all documents | |
| via the REST API (bypassing the 30-day MCP limit), and saves each meeting as a | |
| YAML-frontmatter markdown file with AI summary and full transcript. | |
| Usage: | |
| pip install requests |
BADM 554 - AI for Learning Class Activity
Here are all the Claude artifacts created by students. Click any link to view the interactive SQL learning tools
| # | Description | Link |
|---|---|---|
| 1 | SQL RPG Battle Game | Open Artifact |
| 2 | Natural Join Simulator | Open Artifact |
Your AgentX submission is technically excellent with comprehensive documentation, but needs agent-optimized presentation to maximize evaluation scores. The README covers the 5 judging criteria well, but doesn't lead with clarity for agent evaluation or include agent-friendly interfaces prominently.
Key Finding: Agents (especially reasoning agents) will parse your README first. Structure must be scannable and interface-centric.
[Telegram Vishal Sachdev (@svishal2001) id:5101503769 2026-01-15T04:13Z] can you explore a local video understanding model so we can be more carefree about usage. we have ollama available. Dont update from github, as if you have summarize cli, i am guessing clawdbot updates will trigger summarize cli updates [message_id: 513]
[[reply_to:513]] Yep — makes sense. Right now your Ollama install has only text/code models (no vision models yet), so “local video understanding” isn’t possible until we add at least one vision-capable model.