PRESENTS
OPENCLAW
From Zero to Your First AI Agent
INSTRUCTOR: SAURABH SURI // RED BRICK LABS + BUILD FUTURE
CURATOR: ROBLEH JAMA // @CHIEF BENEDICT
2026.04.10
Saurabh Suri
WHY THIS CLASS HITS DIFFERENT
- Founder @ Red Brick Labs + Build Future
- Running 11 OpenClaw agents across 3 machines
- Real setup: Mac Mini + local VPS
- Agents working across chat, browser, and background routines
- @surim0n on X
builder-first media and events for people actually shipping with ai
The Journey
JANUARY 2026
- one chatbot
- mostly prompt → response
- light memory
- lots of manual follow-up
APRIL 2026
- a team of specialized agents
- memory and recurring routines
- work across chat, browser, and background jobs
- less prompting, more delegation
the big shift is simple: from chatbot to helper that can actually do small jobs.
Why Everyone Started Talking About Agents
1. CHATBOTS
First wave: answer questions.
2. COPILOTS
Next wave: help with drafts, research, and coding.
3. AGENTS
Now: remember context, use tools, and follow up.
4. THE SHIFT
It starts to feel like delegating work, not just chatting.
an agent can take action, not just give you text.
CORE CONCEPT
Think of this like hiring a junior employee, not installing software.
- [x] they need onboarding
- [x] they need a clear role
- [x] they need rules and access
- [x] they need supervision
- [x] they will make mistakes
- [x] they get better with feedback
What is OpenClaw?
A system for building your own AI helper using plain-text files, tools, memory, and routines.
CHAT WHERE YOU ALREADY ARE
Discord, Telegram, Slack, WhatsApp, iMessage, whatever you already use.
USE TOOLS
Browser, notes, calendar, code, spreadsheets, messages, and more.
REMEMBER CONTEXT
Not just one chat. It can keep useful notes and recall past work.
FOLLOW ROUTINES
Check in, watch for changes, and do recurring work without being asked every time.
OpenClaw Architecture, in Plain English
1
YOU ASK
message the agent, or a scheduled check kicks off.
2
IT CHECKS CONTEXT
rules, memory, tools, and current chat context shape the move.
3
IT DOES THE WORK
reply, use a tool, schedule follow-up, or hand off to another agent.
THE LOOP
message in
↓
rules + memory + tools
↓
action or reply
that’s the product. everything else is packaging.
The Agent Folder
edit the files, change the employee.
IDENTITY.md
who the agent is
SOUL.md
how it talks and behaves
MEMORY/*.md
what it remembers
HEARTBEAT.md
what it checks on its own
optional later: AGENTS.md for team structure, BOOTSTRAP.md for startup context.
From Files to Behavior
IDENTITY + USER
WHO IT IS
Name, role, audience, and relationship.
SOUL + RULES
HOW IT ACTS
Tone, boundaries, personality, and taste.
HEARTBEAT + MEMORY
HOW IT KEEPS GOING
What it remembers, and when it checks for work.
edit the files, change the employee.
Heartbeat & Cron
HEARTBEAT
A recurring check-in loop.
Do I have work? Did anything change? Should I follow up?
CRON JOBS
Scheduled tasks that run without waiting for a message.
watch → decide → act
WATCH
Inboxes, feeds, dashboards.
DECIDE
Rules, judgment, triage.
ACT
Reply, update, notify, hand off.
Memory Architecture
THREE TIERS OF MEMORY
Past conversations, prior work, and retrievable context
Preferences, relationships, operating rules, and durable knowledge
A running journal of decisions, tasks, and recent activity
the point: agents get more useful when they can remember, not just chat.
Why Multiple Agents?
ONE GIANT AGENT GETS MESSY FAST
ONE AGENT DOING EVERYTHING
work, family, engineering, content, errands, research
= too much context
SEPARATE LANES
one agent per lane means clearer memory, safer access, and better outputs
less clutter, better behavior
Architecture
MANAGER AGENT
receives requests, routes work, follows up
OPS
admin + reminders
CONTENT
writing + publishing
ENGINEERING
code + technical work
PERSONAL
family or home lane
one hub, a few specialists, then subagents only when needed.
Real Example Agents
HOBSON
chief of staff. routes work, follows up, keeps the system moving.
SCARBOROUGH
engineering agent. handles software projects and technical debugging.
BENEDICT
content lead. writes and ships Build Future content in its own voice.
BABY HOBSON
family lane. narrower scope, calmer tone, safer context.
Why OpenClaw?
OPEN SOURCE
You can inspect it, learn from it, and change it.
YOU CAN SHAPE IT
Name the agents, set the rules, pick the tools, control the access.
IT TEACHES YOU FAST
You learn memory, tools, routines, permissions, and delegation by doing.
Security
LAYER 1
SEPARATE MACHINE
If something goes wrong, the damage stays limited.
LAYER 2
LIMITED ACCESS
Different agents should get different tools and permissions.
LAYER 3
WRITTEN RULES
The important do-not-cross lines live in plain text.
Hardware Setup
BEST STARTING POINT
A dedicated machine, like an old laptop, Mac mini, Linux box, or cloud computer.
WHY DEDICATED?
- safer than running everything on your main computer
- easier to leave on 24/7
- feels like a real operator setup
Local Machine vs VPS
VPS = a rented cloud computer
LOCAL MACHINE
- best for macOS apps, browser work, and local tools
- better privacy and hardware control
- more setup and maintenance
VPS
- cheap, always on, easy place to start
- great for monitors and background jobs
- no macOS-native superpowers
start on a VPS if you want simple and cheap. go local when you want more control.
Account Setup
- [x] one chat channel for talking to the agent
- [x] one account for the tools it needs
- [x] a secret manager for credentials
- [x] a task, calendar, or notes system
- [x] clear permission boundaries from day one
Installation
curl -fsSL https://openclaw.ai/install.sh | bash
1
install
CLI, gateway, starter config
2
connect
chat, tools, accounts
3
shape
identity, rules, memory, permissions
My Model Roster
MY CURRENT SETUP, AS OF APRIL 2026
| ROLE |
MODEL |
NOTES |
| Primary |
GPT-5.4 |
Main default across the system |
| Heartbeat |
GPT-5.4 Nano |
Cheap scheduled checks |
| Browser |
Gemini 3 Flash |
Long-context multimodal work |
| Image generation |
Nano Banana 2 API |
Default image model |
| Backups |
Opus, Sonnet, Codex, Spark |
Used when needed |
Other Models People Were Trying
OPENROUTER SNAPSHOT, APRIL 2026
- Step 3.5 Flash
- GLM 5 Turbo
- MiMo-V2-Pro
- Claude Sonnet 4.6
- MiniMax M2.7
- Qwen3.6 Plus
source: openrouter.ai/apps/openclaw, captured april 2026.
the point: there is no single holy model yet.
What Good Automation Looks Like
WATCH
Email, feeds, chats, forms, dashboards, or docs.
DECIDE
Filter noise, summarize, prioritize, or choose a next step.
ACT
Reply, update a system, draft content, or relay to the right agent.
good first use cases: inbox triage, recurring reminders, content prep, family logistics, and simple research loops.
Agents Can Relay Work
1. RECEIVE
An agent gets a request from the wrong channel or wrong user context.
2. HAND OFF
It passes the job to the agent that actually owns that lane.
3. RESPOND
The result comes back in the right voice, in the right place.
don't dead-end the user. route the work.
The Honest Truth
BROWSER: UNRELIABLE
- Always look for an API first
- The web is hostile to agents (anti-bot)
- Trial and error. Some sites work, some don't.
MEMORY: ACTIVE MAINTENANCE
- Check in: "What do you remember about X?"
- Review what the agent remembers from time to time
- Treat memory like something you maintain, not magic
WHATSAPP: OFF IN MY SETUP
- I keep it disabled for reliability and routing reasons
- Treat channel access as a policy choice, not a default
SETUP COST: REAL BUT WORTH IT
- Expect a few hours first time
- The payoff compounds daily
first install is real work. after that, the system compounds.
Power User Tips
1
Claude Code as brain surgeon
Point Claude Code at ~/.openclaw/ → "Hobson says he can't connect to email. Go fix."
2
Voice notes in Telegram
Often the easiest high-bandwidth input. Don't type, just speak.
3
Agent assigns YOU tasks
Linear tickets assigned TO the human. The agent project-manages you.
4
Google Workspace integration
Docs, Sheets, Calendar, Gmail, Drive. Work with your agent like any other colleague.
5
Be a good manager
Clear expectations > barking orders. "That would not be effective on an employee. Why would it work on an agent?"
Config Evolution
JANUARY 2026 (Clawdbot era)
- one main agent
- basic memory
- simple messaging workflows
- lots of manual babysitting
APRIL 2026 (OpenClaw)
- specialized agents with clearer roles
- better memory and follow-through
- scheduled routines
- safer boundaries
- agent-to-agent relay
"Start simple. Evolve as you learn."
Your First Agent — Tonight
ASK YOURSELF:
- [ ] Is it recurring? (heartbeat candidate)
- [ ] Requires judgment but not deep expertise?
- [ ] Could you explain it to a smart intern in 5 min?
- [ ] If it screws up, how bad is the damage?
STARTER RECIPE
- One clear responsibility
- One heartbeat task
- Telegram-only communication
- Read-only access to start
- 3-4 soul rules
"Don't build 11 agents on night one. Build one. Give it one job. Run it for a week."
Get Started
REPO MOMENTUM
GitHub stars are moving too fast to freeze in this deck. Check the live repo for the current number.
Source: github.com/openclaw/openclaw
this still feels early, which is exactly why it matters.
OPENCLAW // 2026
Go build
yours.
BUILDFUTURE