Software delivery has changed. The teams that move fastest are no longer relying on isolated AI tools, scattered prompts, or one-off experiments. They are building repeatable systems that turn AI into execution.
That is why we built DinoStack.
DinoStack is Space Dinosaurs' agentic engineering framework: a structured system for using AI agents to accelerate planning, development, QA, review, debugging, release workflows, optimization, and analysis.
It gives teams a faster way to move from idea to production without adding chaos to the delivery process.
What DinoStack Does
DinoStack brings agentic AI into the full software delivery lifecycle. It helps teams:
- Break work into clearer technical plans
- Coordinate multi-agent coding workflows
- Improve QA coverage and debugging speed
- Reduce manual review and release friction
- Analyze implementation quality earlier
- Support faster iteration on ecommerce and retail technology initiatives
The goal is simple: higher velocity, cleaner execution, and better outcomes.
DinoStack is built for teams that need to ship with confidence. It helps engineering organizations reduce coordination drag, increase throughput, and create a more predictable path from roadmap to release.
Why We Built It
At Space Dinosaurs, we work with brands where time to market matters. Product teams need to launch faster. Engineering teams need fewer blockers. Leaders need technology investments to translate into measurable performance.
AI can help, but only when it is engineered into a repeatable operating model.
DinoStack turns agentic AI from an experiment into a delivery system. It gives teams structure, guardrails, workflow design, and practical execution patterns that support real production work.
In side-by-side testing, engineers using the framework achieved 84% higher PR throughput, improved code quality, and reduced defects.
That is the kind of performance gain that changes the shape of a roadmap.
Built for the Tools Teams Already Use
DinoStack is designed to travel with your team's workflow.
The same methodology is packaged for multiple coding agents and AI development tools. Teams can start with the tool that matches their current workflow, then extend the framework as their agentic engineering stack evolves.
What Is Included
DinoStack packages the methodology into three core layers: rules, reference protocols, and specialist agents.
Rules
The framework includes three core rule files:
- Agent methodology — delegation, risk classification, task decomposition, and worktree lifecycle
- Code standards — tool discipline, quality gates, package management, and browser verification
- Conventions — writing style, project structure, session context, and git workflow
These rules give agents a shared operating model. They define how work should be planned, executed, checked, and handed off.
Protocols
DinoStack also includes seven detailed protocol specifications that load when relevant:
- Skeptic protocol — adversarial review loop, findings classification, and sign-off format
- Subagent protocol — parallel spawning, worktree isolation, and task decomposition
- Agent team — roles, composed flows, decision rules, and spawn requirements
- Design goals — system design principles and intent
- Multi-developer coordination — parallel sessions, branch hygiene, and worktree hygiene
- Regression test obligation — when a fix requires a regression test and what counts
- Doc-sync obligation — when a reality-asserting change must update intent-layer docs in the same PR
These protocols help teams reduce ambiguity. They make the agent workflow more inspectable, repeatable, and safe.
Specialist Agents
DinoStack includes named specialist roles including:
- Architect
- Engineer
- Skeptic
- Debugger
- Dependency Auditor
- Investigator
- Learning Extractor
- Orchestration Planner
- Performance Analyst
- QA Engineer
- Release Orchestrator
- Security Auditor
These agents give teams a sharper division of labor. Instead of asking one AI assistant to do everything, DinoStack defines roles for planning, implementation, review, testing, security, performance, release coordination, and institutional learning.
You can explore the framework in the DinoStack documentation.
Preparing for Open Source
We are preparing to open-source DinoStack so more teams can use it, test it, improve it, and help push agentic engineering forward.
Before the broader release, we are giving a small group of teams early access.
Early access is best suited for engineering and ecommerce teams that want to explore agentic planning, AI-assisted development workflows, QA acceleration, review discipline, and faster release execution inside a practical framework.
Want Early Access?
DinoStack is still evolving, and we are looking for teams that want to help shape what comes next.
Explore the docs and Contact Space Dinosaurs for early access to DinoStack.
Let's ship faster. With teeth.