AI Orchestration
Coordinate multiple AI agents working in concert. Our orchestrator routes tasks, manages context, and ensures coherent output across complex workflows.
Self-learning AI frameworks that automate workflows, accelerate DevOps, and orchestrate multi-agent systems -- built for teams that ship.
BACON-AI is a collaborative AI framework company building the infrastructure for autonomous, self-improving systems. We believe the future of software development is agentic -- where AI agents don't just assist, they orchestrate.
Our frameworks combine multi-agent orchestration, progressive validation, and self-annealing methodologies to deliver production-grade automation that gets smarter over time.
From orchestration to deployment, our framework handles the complexity so your team can focus on what matters.
Coordinate multiple AI agents working in concert. Our orchestrator routes tasks, manages context, and ensures coherent output across complex workflows.
ADDT is our methodology where AI agents drive the entire development and testing lifecycle -- from architecture decisions to automated quality gates.
Systems that accumulate knowledge from every interaction. Lessons learned are captured, indexed, and applied automatically to accelerate future work.
Infrastructure as code, CI/CD pipelines, deployment orchestration, and monitoring -- all managed by intelligent agents that learn your stack.
A rigorous, model-agnostic coding methodology with self-annealing that ensures progressive validation at every step from planning to production.
Spawn specialized agent teams -- orchestrators, architects, builders, testers -- each with full context propagation and voice-enabled status reporting.
Three stages from idea to autonomous production system.
Describe your problem space. Our orchestrator analyzes complexity, selects optimal agent configurations, and builds a phased execution plan.
Specialized agents execute in parallel with progressive validation gates. Every decision is documented, every output is tested automatically.
The framework captures lessons from every interaction, self-anneals its methodology, and becomes more effective with each project cycle.
A systematic, model-agnostic approach with built-in self-annealing that ensures quality at every step.
Initialize session with full project context, constraints, and objectives.
Score task complexity using weighted criteria to determine approach.
Design solution architecture with component boundaries and interfaces.
Create detailed execution plan with validation checkpoints.
Implement in incremental stages with continuous verification.
Test individual components against requirements and edge cases.
Verify component interactions and end-to-end workflows.
Methodology adjusts based on outcomes, optimizing for quality.
Automated checkpoints ensure standards before progression.
Generate comprehensive records of decisions, patterns, and outcomes.
Extract lessons learned and integrate into the knowledge base.
Ship to production with monitoring and continuous improvement.
The people and AI agents behind the framework.

Building the future of agentic development from the intersection of DevOps, AI, and systems engineering. Colin leads the BACON-AI framework design, agent orchestration patterns, and the self-annealing methodology.
Whether you're exploring AI orchestration for your team, interested in the BACON-AI framework, or want to collaborate -- we'd love to hear from you.