Locus
Providing the structural affordances of large organizations to small teams and solo builders.
Creator, designer, and systems architect · 2024–Present · Solo, with AI as a consistent collaborator
An operating model that gives solo builders the structure a real team provides — so multiple products can ship and stay coherent as they scale. It supports a mix of product types (database-driven tools, conversational workflows, APIs, and this portfolio) and stays durable via two patent-pending drift-check systems.
In this project: An operating model that gives solo builders team structure · Built-in checks for drift
What if a solo builder had the same structural advantages of a full team?
One operator plus AI shipped multiple real products — database-driven tools, conversational workflows, APIs, and this portfolio — under a single operating model.
Great teams don't just run on talent — they run on the "between work": clear roles, visible decisions, quality bars, and lightweight rituals that keep many threads aligned.
Solo builders and small teams often move fast early, then lose coherence as projects stack up — decisions disappear, standards drift, and rework grows.
Locus turns that connective tissue into an operating model: separated work areas, persisted reasoning, decision + reflection logs, and explicit rules for how AI can contribute without silently shifting the work.
Built-in checks for drift
Instead of relying on discipline, Locus uses built-in checks that surface drift and set clear boundaries for AI — so the model still works when things get busy.
When a process depends on memory, the "check" is exactly what gets skipped under pressure.
Two patent-pending systems make the operating model self-checking:
- Health Check Engine: periodically scans operational signals and writes findings back into the workflow.
- Governance Runtime: makes AI authority explicit (what it can do, and when) before actions are taken.
The Result
decisions stay discoverable and standards stay consistent as projects scale.
Operating Model
three pillars, one loop
Work
what gets done
Domains
Functions
Artifacts
Governance
how it's checked
Reviews
Checkpoints
Standards
Memory
how it's remembered
Work Log
Decision Log
Methodology Log
reviewed at checkpoints
decisions captured
informs next work
Flow & Relationships
how the pillars connect
Work
What gets done
Domains · Functions · Artifacts
reviewed at checkpoints
Governance
How it’s checked
Checkpoints · Panels
overlay across every function
Collaboration
Who does what
5 questions × every function
each verdict produces a record
Decision
The through-line
Minimum Decision Record
written to persistent memory
Memory
How it persists
Work · Decision · Methodology
standing rules feed back into governance
What I'd do differently
- Visualize the system sooner. Early versions lived mostly in text, which made it harder to spot what was missing or confusing. Made it harder to get feedback from peers, and for me to spot continuity errors.
- Simplify earlier instead of patching. When a part of the model wasn't pulling its weight, it took too long to replace it with a cleaner version.
- Productize the repeatable parts earlier. Two pieces started as "habits" to keep the system on track; they should have been treated as buildable, reusable tools sooner.
Deeper case study available on request.
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