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Your 2026 Roadmap Through 7 Homeworks (With a 4-Year Comparison) | Harvard CS181 Course Overview

CS181 2026 is A3 with hw0–6 as the weekly clock (no public recording links listed for the corresponding lectures); 2025 adds a practical, 2024 has two midterms, 2023 was taught by Weiwei Pan. Start with HW0, then follow hw1→hw6.

Search — From DFS, BFS, A* to Minimax and Alpha-Beta Pruning | Harvard CS50 AI Week 0

Week 0 is about search: DFS and BFS differ only in whether the frontier is a stack or a queue; A* adds the steps already taken to a heuristic estimate and guarantees the shortest path when the heuristic never overestimates; Minimax has the two players take the maximum and the minimum in turn, and alpha-beta pruning cuts branches that cannot change the result. With time links for every section, plus the approach, common mistakes and ways to check your work for the Degrees and Tic-Tac-Toe projects; the reference implementations are folded at the end of each project.

Claude Code Config Not Taking Effect: Diagnosing with /context, /doctor, /mcp, and Error References

When CLAUDE.md rules are ignored, hooks never fire, or an MCP server shows no tools, the file usually didn't load, loaded from an unexpected location, or got overridden. This guide covers what the diagnostic entries (/context, /memory, /skills, /doctor, /mcp, and more) actually show, safe-mode bisection, and a table of six high-frequency error messages with fixes.

Claude Code install and login troubleshooting: PATH, install sources, proxy, OAuth callback

Work through install and login failures in five steps: verify PATH on your OS, confirm there is only one installation, test downloads.claude.ai for a 200, recover failed OAuth callbacks by pasting the login code or using claude auth login, then finish with claude doctor.

Claude Code Runtime Troubleshooting Guide: CPU/Memory, Session Hangs, Auto-Compact Thrashing, Tables, Search Failures

Five classes of runtime fixes: diagnose high memory with /compact plus /heapdump; recover a hung session with Ctrl+C and claude --resume; write large tables to files instead of forcing terminal output; escape autocompact thrashing by reading files in chunks or running /compact with a focus; fix broken search by installing system ripgrep and setting USE_BUILTIN_RIPGREP=0.

techguide

Choosing Mac Remote Desktop: Tailscale, Jump Desktop, RustDesk, and Built-in Screen Sharing

No budget needed: Tailscale plus built-in Screen Sharing is free and the most reliable stack for daily remote work on Mac — upgrade to Jump Desktop only if you want it smoother. This guide compares four options and fixes lid-close and sleep pitfalls in 5 minutes.

Self-Hosted Inference Overview: When Running Your Own Models Makes Sense

The key question in self-hosted inference isn't how fast the engine is — it's your GPU utilization. A fully saturated A100 costs ~$0.70 per million output tokens; at 10% utilization that becomes $7, more than most cloud APIs. This overview maps seven tools across three layers to help you decide which layer you need.

techguide

AI Model Evaluation Sources: How to Judge Whether a Model Is Actually Good

You cannot take model vendors' self-reported scores at face value. This guide covers the most important independent evaluation platforms, domain benchmarks, adoption indicators, and official sources in 2026: what each measures, how to read it, where it is biased, and which figures matter for different use cases.

AI Model Landscape: The 2026 Map You Need

In 2026, AI models span seven major categories and more than 20 subcategories. This introduction to the AI Model Families series maps use cases to models and models to families, with current rankings and selection advice for each use case.

How to Pick a Self-Hosted Inference Server: From Ollama to Xinference, Six Tools and Their Trade-Offs

Self-hosted inference servers fall into three layers: execution engine (llama.cpp), serving engine (vLLM, SGLang), and model management platform (Ollama, Xinference, Triton). Picking the right layer matters more than picking the right tool — ask where your bottleneck is before deciding where to add complexity.

Reading Guide: Pick What Most People Use — the Other Five Criteria Are Tie-Breakers

The primary criterion has not changed: it is still adoption — and AI makes it matter more, not less, because more users means more training data means higher agent accuracy. The five criteria this series collects (machine-readable docs, types, whether the source is in your repo, data shape, machine-callability) are for breaking ties when adoption is comparable, or for costing out what picking the less popular option will charge you.

Claude Code /loop: Turning AI into a Background Worker with Native Scheduling (v2.1.72+)

/loop is Claude Code's native cron feature — set schedules in plain English and let Claude monitor, auto-fix PRs, and run recurring tasks in the background. Session-scoped and expires after 7 days; for cross-session scheduling, use Routines or Desktop scheduled tasks.

Claude Code Routines: Complete Guide to Cloud Automation — Setup, Triggers, and Real-World Examples

Routines is Claude Code's cloud automation system (formerly Cloud Scheduled Tasks). Beyond cron scheduling, you can trigger runs via API endpoint or GitHub events — scan issues, review PRs, run checks, open PRs — all while your computer is off.

Warp: From Modern Terminal to Agentic Development Environment

Warp evolved from a Rust-powered modern terminal into an AI Agent-integrated development environment (ADE), open-sourced under AGPL in April 2026, with over 700,000 developer users.

techguide

How Does the YouTube to NotebookLM Extension Work? Reverse Engineering and Cross-Tab Architecture Dissected

NotebookLM has no official API. This extension works by combining three techniques: reverse-engineered Google batchexecute RPC calls, DOM scraping, and cross-tab message passing.

The Full Picture of Cloudflare Workers AI Binding: It's More Than Just run()

env.AI is not just run(). It also exposes toMarkdown (document-to-Markdown conversion), autorag (managed RAG), gateway (external provider proxy), and models (metadata lookup). Understanding these four method groups is what unlocks Cloudflare as a full AI platform inside Workers.

techguide

Better Agent Terminal: Consolidate Multiple Project Terminals and Claude Code Agents into One Window

Better Agent Terminal (BAT) is an Electron desktop app that unifies multiple project workspaces, terminals, and Claude Code Agents into a single window — solving the everyday pain of exploding iTerm tabs and the lack of a proper GUI container for agents. MIT License, available on macOS, Windows, and Linux.

techguide

Solving Duplicate Config Files for Codex and Claude Code with a Symlink

Claude Code only reads CLAUDE.md; Codex only reads AGENTS.md. Teams using both end up maintaining two identical files. Fix: make CLAUDE.md a symlink pointing to AGENTS.md — one source of truth.

techguide

Where Should AI Agent Global Skills Live? The Division of Labor Between .claude, Codex Skills, and AGENTS.md

Skill paths are almost always runtime-specific. AGENTS.md is the reliable way to share rules across agents. Put personal reusable capabilities in each agent's supported global directory; put project workflows inside the repo.

techguide

code-review-graph: Using a Knowledge Graph to Cut AI Code Review Token Usage by 8x

code-review-graph uses Tree-sitter to parse your codebase and build a persistent knowledge graph, tracks the blast radius of changes, and feeds only truly relevant context to the AI — claiming an average 8.2x reduction in token usage.