limerIQ turns your prompts into reliable workflows that orchestrate Claude Code, Codex, and Gemini CLI. Independent agents plan, code, test, and review changes so you keep the leverage and lose the chaos.
A short story from prompt -> workflow -> guarded execution -> merge. Built for developers who expect tests, git discipline, and repeatability.
In VS Code: "Add a /projects endpoint with validation and tests using our existing helpers."
No new AI subscription required. limerIQ orchestrates the models you already have.
Claude API Key
ChatGPT Plus or Pro
Or OpenAI API key
Gemini Plus, Pro, or Ultra
Or Google API key
Kimi Code Moderato, Allegretto, Vivace
Or Kimi Code API key
One orchestrator. Four frontier model families. Your choice.
Request closed beta accessBecause limerIQ treats AI like part of your SDLC, not a magic autocomplete box.
Tasks spiral when there's no structure. limerIQ breaks work into discrete steps with explicit gates—agents stay on-task because the workflow won't let them wander.
"Sure, I'll write tests" → no tests. Compliance guards enforce deliverables at each step. No output, no proceed.
Deterministic code steps (lint, test, build) create checkpoints AI can't fake. If it compiles and passes, it's real.
One model, one opinion, one blind spot. Multi-agent consensus and LLM-as-judge patterns pit models against each other so the best answer wins.
Build and share limerIQ workflows with the community. Here are a few workflows that are popular right now.
Transforms vague user intent into a comprehensive, testable product plan through structured discovery, competitive parallel drafting (Opus + GPT-5.2), and multi-phase review. Produces PRD, user stories, acceptance tests, architecture docs, and a handoff prompt—ready for builder execution. Ideal for greenfield products, feature additions to existing codebases, or any initiative requiring thorough upfront planning before implementation.
An iterative product development workflow that orchestrates parallel planning and review phases using multiple frontier AI models (GPT-5.2 and Claude Opus). Features branch-based iteration loops with user checkpoints, built-in observability profiling, automated PR generation, and anomaly detection. Ideal for building new products from scratch, enhancing existing codebases, or continuing paused projects with full documentation scaffolding and creative backlog management.
Demonstrates limerIQ's unique git worktree isolation capability for true parallel feature development. Three independent features develop simultaneously in isolated workspaces with zero merge conflicts because each builds against a stable foundation. Perfect for teams that need concurrent feature development without stepping on each other's toes.
A meta-workflow that demonstrates limerIQ's revolutionary self-improving capability by using AI to intelligently gather requirements, automatically generate production-ready orchestration workflows, validate them, and present them for human review. This showcases the power of AI designing AI systems for maximum automation potential.
A comprehensive workflow demonstrating all limerIQ step types and visual editor capabilities, from project discovery through sprinted execution. Perfect for learning the platform's full potential and understanding how to orchestrate complex, multi-phase AI workflows with human checkpoints, parallel branches, and quality gates.
A sophisticated multi-stage code review workflow that demonstrates limerIQ's fresh context management capabilities. Each review stage—discovery, security, performance, and synthesis—operates with a clean context window, receiving only targeted variables and documentation scaffolding. Sub-agents handle deep dives without polluting main context, resulting in cleaner reasoning, less hallucination, and efficient token usage.
