A production-grade framework for AI-first software engineering. Scale individual developers through rigorous orchestration, security-first architecture, and adversarial audit loops.
Modern AI agents can generate thousands of lines of code in minutes. But speed without structure creates chaos.
SOLO transforms sloppy AI outputs into production-grade software through structured workflows that demand rigor at every stage.
Implementation is forbidden until the design survives the critique loop. C4 modeling by default.
Typed contracts are the canonical source of truth. Schema synchronization is non-negotiable.
Auth and RBAC are designed before feature code. Zero-Trust authorization is the foundation.
AI orchestrates; Human validates. Mandatory approval gates between every engineering phase.
Production code is a liability without tests. TDD is the default mode for all critical business logic.
Session memory preserves architectural "gotchas" across weeks of non-contiguous development.
Adversarial design refinement to eliminate drift before the first line of code.
Because optimistic engineering is a liability. The default state of software is 'broken until proven robust'.
It views your code as a potential liability, hunting for complexity, gold-plating, and fragile abstractions. It does not optimize; it scrutinizes everything that is not essential.
Every 'TODO' is a blocker. Every caught exception must have a recovery strategy. If the implementation_plan is vague, it halts the loop immediately.
"Complexity is a liability. Simplify ruthlessly."
Resilient implementation with mandatory human validation gates.
Systematic Root Cause Analysis (RCA) when verification fails.
Because adopting a persona intentionally unrelated to software development acts as a cognitive power up.
It forces the model to abandon its training to apply "standard fixes" and instead unlocks a relentless, deductive mode of reasoning that standard engineering prompts cannot reach.
When the investigation hits a dead end, he suspects every variable, refuses to guess, and enlists Watson's help (the User) when standard deductive processes yield no answers.
"It is a capital mistake to theorize before one has data."
Switch between tasks, days, or AI models without context decay. The protocol is the project's long-term memory.
Because relying on "automatic memory compaction" is fragile. We must explicitly persist the project state to survive the session boundary.
It treats the session as a finite unit of work. We start with a clean state for new features to ensure previous sessions don't pollute current results.
Before signing off, the context is compacted into a structured handoff
(SESSION_MEMORY.md). On return, the agent re-hydrates
strictly from this source of truth.
"Context is currency. We control what is retained."
Create distinctive, production-grade frontend interfaces with high design quality. Generates creative, polished code and UI design that avoids generic AI aesthetics.
Adversarial analysis to identify gaps, risks, and brittleness.
Principal Technical Project Manager for sprint planning and ticket decomposition.
High-fidelity Coding Agent for resilient, production-grade implementation.
High-fidelity refactoring with reference-first safety and legacy preservation.
Code Review Agent for rigorous logic verification and technical debt audits.
Implementation & Remediation Agent for production-grade refactoring and hardening.
This document describes a structured workflow for AI-assisted software development using Cursor IDE with custom slash commands. The workflow emphasizes planning before coding, iterative critique, and quality gates before deployment. It was refined over multiple iterations of a full-stack application migration.
Never jump directly into implementation. Every significant piece of work goes through a planning phase that includes analysis, explicit design decisions, and self-critique.
The AI agent does the heavy lifting, but the human maintains control through explicit approval gates, structured reviews, and quality checks before commits.
Sessions can span days or weeks. Context preservation is critical: session memory files capture state, and the AI can resume work without re-explaining the project.
The API contract is the source of truth. Before implementation begins, define all endpoints and
schemas. The .API/ folder contains the canonical contract enabling independent
technology choices.
Production code is a liability without tests. Quality is a prerequisite. Write tests before implementation—they define "done". No code ships without passing the full test suite.
Security is not a feature; it is an architectural constraint. Auth and RBAC are designed before feature code. Zero-Trust is default. Security Audits are mandatory gates.
Custom slash commands in .cursor/commands/ define specialized agent personas. Each
command transforms the AI into a domain expert. Click a card to view the protocol specification.
Command: /resume
Start every session by loading context from the session memory file. The AI reads
.tmp/SESSION_MEMORY.md and orients itself to project state, critical knowledge, and
user preferences.
Command: /architect
For significant work, generate a technical specification before implementation. The architect persona produces structured documents including diagrams, API contracts, and security considerations. Outputs a comprehensive plan answering "what" and "why".
Command: /design
When UI is impacted, invoke the UX Oracle. Produces an "Experience Manifesto" utilizing JTBD Deep-Dives, Shadow Data Extraction, and Cognitive Load Mapping.
Command: /critique
Turns the AI against its own plan. Hunts for gaps, brittle design, code smells, and security concerns. Flags anti-patterns like "Gold-Plating," "Abstractions for One," and "Locked File Modification."
Command: /revise
Address every critique item. Does NOT write implementation code. Specifies patterns and trade-offs. Iterates with Critique until the plan is ready.
Command: /tickets
Convert the approved plan into prioritized, actionable tickets. Each ticket is self-contained, vertically sliced, prioritized, and testable.
Command: /code
With an approved plan, implementation begins following strict TDD discipline. All failure modes must be handled with zero-bug tolerance and mandatory test coverage. No production code without unit, integration, or E2E tests.
Command: /code++
For complex refactoring, use the Reference-First workflow. Create a complete source of truth before applying changes incrementally with full verification at each step.
Standalone Test Verification: /test ensures all tests are "green and
clean."
Command: /review
After implementation, conduct a formal code review. Produces a structured report with a Summary of Findings and a Health Score.
Command: /fix
Remediate all issues from the review systematically by severity. Runs full test suite after fixes.
Commit with conventional messages, tag the release, save context with /memory, and
deploy.
Command: /sherlock
Even with rigorous orchestration, runtime issues occur. The Debug Loop provides a systematic protocol for Root Cause Analysis (RCA) when verification fails.
/sherlock to trace
logs, state, and dependencies.
┌→ [Minor] → /critique → /revise → /fix → /test
/sherlock ──┤
└→ [Major] → /architect → /critique → /revise → ...
Key Rule: Never apply a "blind fix". If /sherlock cannot explain
why it broke, do not run /fix.
.tmp/SESSION_MEMORY.md allows multi-session resiliency.
Smaller Tasks:
/resume → /code → /review → /fix → commit
Backend-Only: Skip
/design.
UI-Heavy: Include
/design after architect.
Exploratory: iterate with
/architect → /critique → /revise.
Debugging:
/sherlock → /fix → /review
The .lockedfiles mechanism prevents agents from modifying stable code.
Agents check this file before writing. If matched, they must pause and request a "Manual Override".
This workflow treats AI as a highly capable but supervised team member. The human provides strategic direction and approval; the AI provides deep analysis, consistent quality, and structured documentation. The result is production-grade code with a clear audit trail.