System Design Roadmap

11/03/2026

Ask an AI agent to plan a team offsite and one prompt won't cut it. Here's how agents plan 👇

1. A planner breaks the goal into steps
2. Each step lists its dependencies, so independent steps run in parallel
3. An executor runs steps with tools and writes results back
4. A step fails? Replan only what's left, keep what's done
5. Step budget + a checkpoint before anything irreversible

Part 3 of our agent series. More: https://systemdrd.com/?utm_source=facebook&utm_medium=reel&utm_campaign=reel05_agent_planning

Where would you put the human checkpoint in your agent?

11/02/2026

Feeling faster with AI isn't the same as being faster. Measure it.

The 4-step loop:
1️⃣ Spec it
2️⃣ Slice it
3️⃣ Build and verify it
4️⃣ Review and retro

Then log 10 tasks: loop vs freestyle.

Full video: ▶️ https://youtu.be/qGGBAdz6DpY
Free looplog tool + spec template: https://systemdrd.com

Have you ever timed your AI speedup, or is it a feeling?

10/31/2026

Close the chat and your AI agent forgets everything. Here's how agents actually remember 👇

Short-term: the context window. When it fills up, summarize old turns.
Long-term: after each session, extract durable facts, embed them, store with user_id + timestamp.
Next session: retrieve the top 3 matching memories and add them to the prompt.
Rule: memories expire or get overwritten, so the agent never acts on stale facts.

Part 2 of our agent series. More: https://systemdrd.com/?utm_source=facebook&utm_medium=reel&utm_campaign=reel04_agent_memory

What should an agent never remember about a user?

10/30/2026

Claude Code forgets your project every session, unless you give it a CLAUDE.md.

One file in your repo root, read at the start of every session:
→ Project overview: what it does, what must never be undone
→ Tech stack: versions and non-obvious rules
→ Current state: what changed, what's broken
→ Commands: how to test, lint, run

Full lesson: https://systemdrd.com/lessons/day-4-write-claude-md-2/

What's the one rule you'd put in yours?

10/29/2026

Your cache just took down your database. Here's how a cache stampede happens 👇

A hot key expires → 1,000 requests miss at once → 1,000 identical DB queries → timeouts → retries make it worse.

Fix 1: request coalescing: one request takes a lock and rebuilds, everyone else waits for that result
Fix 2: jittered TTL: add random seconds so hot keys never expire together
Bonus: refresh hot keys early, before they expire

More hands-on system design: https://systemdrd.com/?utm_source=facebook&utm_medium=reel&utm_campaign=reel03_cache

Have you ever seen a cache stampede in production?

10/28/2026

Why does every AI tool need its own custom integration? With MCP, it doesn't.

Host → Client → Server. Your server exposes three things:
🛠 Tools: actions the model can take
📂 Resources: data it can read
🧩 Prompts: reusable templates

3 apps × 3 tools = 9 integrations without MCP. 3 + 3 = 6 with it.

Build your first MCP server in Python, step by step:
▶️ https://youtu.be/3stccV03raI

What would you connect to your AI assistant first?

10/26/2026

An LLM doesn't know your documents. RAG fixes that in 5 steps 👇

1️⃣ Chunk your docs
2️⃣ Embed each chunk
3️⃣ Store vectors + sources in a vector DB
4️⃣ Retrieve the closest chunks for each question
5️⃣ Generate an answer that cites its sources

Full hands-on build, about 60 lines of Python with Claude Code:
▶️ https://youtu.be/hwaDzlU9-GM

Which step trips you up most: chunking or retrieval?

10/25/2026

An AI agent is just a loop. Here's what actually happens inside it 👇

The model gets your message + a list of tools → returns a tool call → your code runs it via MCP → the result goes back → repeat. Anything that moves money waits for approval first.

Build your own MCP server (full tutorial): https://youtu.be/3stccV03raI
More from Systemdr: https://systemdrd.com/?utm_source=facebook&utm_medium=reel&utm_campaign=reel01_agent_loop

What tool would you never let an agent run without approval?

10/25/2026

10/25/2026

Vibe coding went mainstream — but under the hype it's a control system 👇

1. Intent / PRD layer (what done means)
2. Agent runtime: read → plan → edit → run → observe
3. Workspace sensors: files, terminal, tests, browser, MCP
4. Failure modes: sh***un edits + hallucinated APIs
5. Guardrails: max steps, approval gates, tests as oracle

Full deep dive on YouTube: https://youtu.be/kCBa7zR2FIc

More from Systemdr: https://systemdrd.com/?utm_source=facebook&utm_medium=video&utm_campaign=yt01_vibe_coding

What's your max_steps before a human approval gate?