Architecture
How the stack is shaped, what each lane owns, and where orchestration actually lives.
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Real deliverable
Guide, PDF, starter templates, and buyer bundle all exist
The problem
Most AI workflows are still one confused blob.
One chat. One giant context window. One assistant pretending to be strategist, coder, reviewer, ops lead, researcher, and memory system all at once.
Fine for novelty. Rubbish for sustained product work.
What serious work actually needs
- role separation
- task routing
- file-backed memory
- verification before trust
- specialist coding and review lanes
- clear handoffs instead of context soup
Build a system, not a chat tab.
This guide shows you how to structure OpenClaw into a tiny specialist team: one agent owns the relationship, cheap work goes to cheap lanes, risky work gets reviewed, context survives restarts, and important output is verified rather than narrated.
Stack shape
The operating logic is the product.
You do not need my exact personalities or naming scheme. You need the routing, memory, and verification discipline that makes the whole machine useful.
The guide covers the parts people usually hand-wave.
Routing rules
Which work goes to cheap local lanes, which goes to heavier coding agents, and when to stop pretending one size fits all.
Memory system
File-backed continuity, daily notes, task state, and long-term memory without relying on vibes.
Verification ladder
How to stop agents from narrating confidence and start demanding proofs, checks, and real stopping criteria.
Templates
Agent role templates, task packets, handoff shapes, verification checklists, and practical defaults you can copy.
Rollout plan
A sane path to start lean, validate usefulness quickly, and avoid building an AI cathedral no one asked for.
Enough substance to build from, not just admire.
Guide
A practical written walkthrough of the system: why it works, what each lane owns, and how to adopt it without turning your week into ceremony.
Starter templates
Agent role template, task packet template, verification checklist, and memory structure template you can adapt to your own stack.
Implementation notes
Recommended rollout order, common traps, and where to keep things lean instead of building a cathedral for imaginary future-you.
Copy the operating logic, not the cosplay.
Söze
Orchestrator, owner of the relationship, final synthesiser.
Gump
Cheap local grunt work, transforms, first-pass output.
007
Tactical implementation and bug-hunt lane.
Drax
High-judgement reviewer for bounded risk-heavy passes.
Codex
Heavier autonomous coding lane for substantial implementation work.
Stitch
Design control room for turning UI intent into buildable system shape.
This is for you if…
- you already use AI for real work
- you are technical enough to configure tools and files
- you want leverage rather than prompt-porn
- you know one giant chatbot is not the whole answer
Not the best fit if…
- you want one-click magic
- you hate tinkering
- you want generic prompts instead of system design
- you need enterprise procurement theatre on day one
One simple offer. No silly ladder.
Whole pack
Ultimate OpenClaw Coding Machine Pack
£15
- full guide PDF
- Markdown guide source
- starter template pack
- routing rules
- memory and verification model
- delivery by email within a few hours
This is intentionally priced like an easy yes, not an overcaffeinated info-product pyramid.
Questions a sensible buyer would ask.
Is this for beginners?
Not really. It is for technical operators and builders who can tolerate configuring tools, files, and a bit of system plumbing.
What happens after purchase?
You’ll receive the whole pack by email within a few hours of purchase: guide PDF, Markdown source, starter templates, and the support docs that make it usable.
Are the names the point?
No. The names are flavour. The value is in routing, memory, verification, boundaries, and handoffs.
Is this another AI hype product?
Quite the opposite. The whole thesis is that most AI workflow content is too vague, too theatrical, or too detached from real operating discipline.
You do not need one magical AI.
You need a system where each lane has a job, context survives, and the work actually gets finished.