Vishal Sachdev vishalsachdev

Claude Code Insights

546 sessions total · 109 analyzed · 1,429 messages · 97h · 32 commits 2026-03-03 to 2026-03-05

At a Glance

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.

Your Core Position:

IT creates unprecedented opportunities for competitive advantage
Digital transformation is the defining business challenge of our era
Technology enables entirely new business models and value propositions
Network effects and platform strategies create winner-take-all markets
AI and emerging technologies are creating new forms of sustainable advantage

Debate Strategy:

Student Claude Artifact Submissions

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

Week 2 Instructor Guide: Competitive Advantage

In-class reference for Session 1 (Tue) + Session 2 (Thu)

Session 1: Strategy Frameworks + Zara Case

Time: 75 min | Date: Tue, Jan 27, 2:00 PM

AgentX README Review & Improvement Suggestions

AgentBeats Competition - Phase 1 (Green Agent)

Executive Summary

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.

Conversation excerpt (from: "can you explore a local video understanding model...")

USER — 2026-01-15T04:13:13.017Z

[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]

ASSISTANT — 2026-01-15T04:14:33.509Z

[[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.

BADM 350 — Technology & AI Strategy (Proposed Core Course Syllabus)

Proposed Title (catalog/branding): BADM 350: Technology & AI Strategy for Competitive Advantage
Credits: 3
Level: 300 (Undergraduate)
Proposed Positioning: Gateway course to the Information Systems major + core course option for the business undergraduate curriculum (recommended).
Prerequisites: None. (BADM 210/211 helpful but not required.)
Term Length: 15 weeks + final presentations (16 instructional weeks).

title	date	publication	notes
Multipass on macOS: My Agentic Flywheel Ubuntu VM Setup	2026-01-11	The Hybrid Builder	AI-written; collaboration recap

Multipass on macOS: My Agentic Flywheel Ubuntu VM Setup

I didn’t start last night by saying “I need a VM.”

Here is a complete, formatted Markdown file ready to be copied and pasted directly into a GitHub Gist.

Prediction Markets & Analytics: A Portfolio Guide for Gies MSBA Students

Target Audience: Students in the MS in Business Analytics (MSBA) program at Gies College of Business. Goal: Leverage prediction market data (Polymarket, Kalshi) to build standout portfolio projects that demonstrate skills in Big Data, Financial Analytics, and Storytelling.

	#!/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