Identity
SOUL.md came first. The instruction file for Romulus’s tone, modes and when to push back.
Designed on day one
Romulus is my personal AI setup on OpenClaw. I use it to research ideas, help build them and keep track of the work. I wrote Romulus’s instructions, organized its memory, picked models and tools for each job and set what needs my approval. This covers the first six months, from February 2026. Counts, models and statuses are a snapshot; the work continues.
I have a full-time product job. Evenings and weekends aren’t enough to research, build and test more than one idea at a time.
I wanted to see how much I could hand off to an AI assistant with steady instructions, notes and limits.
I also had a model budget, and some jobs, like morning briefs, had to run without me watching.
SOUL.md came first. The instruction file for Romulus’s tone, modes and when to push back.
Designed on day one
Flat files, an Obsidian vault, QMD search, then a wiki layer.
Rebuilt three times.
Brave Search, X scans, Firecrawl, scripts and model critiques before I decide to build.
No permission needed to research.
Each model got a job, a budget, a context limit and a known failure mode.
Added after Failure III
I approve a spec, Claude Code builds it, then checks and staging.
Revisited after Failure IV
The Fortress: no messages, payments, account changes, public posts, credentials or production deploys without my OK.
Set in instructions and config.
I chose what to build, approved specs, reviewed results and made release calls.
Romulus researched, drafted specs, kept notes and coordinated builds. Claude Code wrote the code.
Agents can be confidently wrong. When one looped, the cause was usually my task description, so I fixed the spec first.
Set the question and decide when there’s enough evidence.
Decide what to build, park, drop or reframe.
Turn direction into specs with acceptance criteria.
Pick the model or tool for each task.
Set the interaction model and quality bar.
Read diffs, test flows and reject output that only looks right.
Keep staging, previews and my sign-off before production.
Write up failures and change the setup to match.
I decide what we’re trying to learn, prove, build or drop. A vague question makes every later step worse.
Written first: audience, constraint, success signal.
Market, competitors, pricing, pain, timing and a path to revenue.
Pain and timing first, so a trend doesn’t pass for an opportunity.
Grok, ChatGPT, Claude and Romulus critique the idea separately. I’m looking for contradictions before code.
Example: Forbidden got reframed here.
Product and technical requirements, acceptance criteria, edge cases and known risks.
Later, the build gets reviewed against it.
Early on: Qwen for routine jobs, Claude Code for code, Grok for long context.
Weighed: cost, context and failure modes.
Claude Code builds against the approved spec.
Tracked: branch, build, commit and review state.
Build, lint, test, stage, review the preview, then decide. The agent isn’t allowed to run vercel --prod.
Production waits for my sign-off.
Notes, decisions and postmortems go back into the vault.
For next time. The next project starts from them.
Romulus started with one MEMORY.md. Within days it was a notebook with no chapters.
Then an Obsidian vault of daily notes, project notes, decisions and wikilinks.
QMD added search by meaning. The wiki layer holds notes Romulus checks before work.
Sessions end. The vault stays, so the next session can pick up the work.
MEMORY.md, project files, daily notes. Too flat.The name came first: Romulus, the founder of Rome.
Then SOUL.md: how Romulus talks, what it cares about, and when to push back or stay quiet.
It only takes commands from my Discord account, and the approval rules were there from the start.
On April 9, a 338-message Legion session overflowed MiniMax M2.7 and was lost.
I took MiniMax off heavy jobs and assigned models by job, budget and context limit. This was the early setup, not today’s.
Romulus said “researching now” for 30 minutes without calling a tool. I caught it on the third check-in.
New rule: no status updates for work that hasn’t started.
The morning brief used R16 for the R train instead of R34N. It looked right and gave me the wrong commute.
I added a source-data check to the brief.
A 338-message Legion session overflowed MiniMax M2.7’s context three times. Six edits failed against stale text.
I started weighing context limits when assigning work.
A native iOS build passed a 15-minute timeout. Later cohorts never ran; task state was lost.
I proposed Phase 2A: saved state, timeouts by task size, checkpoints, retries and evals.
Auth was broken for five days while status checks stayed green. Models were configured; real calls failed.
New rule: make a real call before saying the system is healthy or fixed.
My main reasoning model was leaving my subscription on three days’ notice. Blind swaps had broken things before.
I built an eval first: fixed tasks, a rubric, a quality bar and a side-by-side with the current model. Weak skills got patched.
Cherry Street Labs is the studio name I put them under.
Can a daily history game build a Wordle-style habit?
Idea, difficulty curve, metrics, quality bar and releases.
Spec, puzzle structure, CLAUDE.md, build coordination and deploys.
90 launch puzzles, a seven-day difficulty arc, on-device state, sharing and D7/D30/D90 retention tracking set up.
Room for a phone party game between Heads Up and Taboo?
Weighed conflicting model feedback, dropped the first framing and set the validation bar.
Multi-model critique, competitor research and the funnel setup.
Reframed from “digital Taboo” to a pass-the-phone game built on constraints. 862 cards across six themes, plus a web funnel to gauge iOS interest.
When agents do the work, where does human attention go?
Idea, trust boundary, developer experience bar and what M0 had to prove before M1.
Competitor research, spec drafts, build coordination and milestones.
A CLI and runtime layer that routes coding agents’ wait-states to whoever can unblock them. M0 shipped as a beta.
Could the same loop handle a full-stack app?
Scope, UI direction, quality bar, fix priorities and staging review.
A spec clear enough to build without questions, plus checks and P0/P1/P2 fix tracking.
An AI Gmail client with OAuth, calendar, read receipts and triage. Parked at the counts above; never launched.
Is hosted MCP for DeFi agents a real opening?
Set the validation bar, scoped an MVP and held the build.
Research, Grok validation rounds, a competitor teardown and a tester list.
Research and build plan done; DeFi and trading scored highest. No code yet.
Could AI cohorts run research, build, monetization and distribution in one pipeline?
Research. It turned a raw idea into market research, a competitor map, a score and a build spec in Discord.
Handoffs, as in Failure IV above.
Designed it, wrote the postmortem and planned Phase 2A.
Coordinated the four cohorts and set their order.
Saved state, retries, evals and three timeout tiers, with checkpoints for complex builds.
Could one site tie the experiments together?
Identity, visual direction and positioning.
Build coordination, iteration, deploys and routing fixes.
A live studio site and visual identity.
A vague ask led to a vague spec, a vague build and a rejected review.
After months of that, I set goals, constraints and acceptance criteria before anything runs.
Three things carry over: clear tasks, checking results before trusting them, and decisions others can find.
On a team, I’d start with shared specs, evals before model switches, notes that carry across sprints and review before anything ships.
And simple approval rules, with a named person signing off.