Echo Theory Labs
Applied AI Research & Development
The gap between what AI can do and what companies can ship is not closing. It's widening with every breakthrough.
Over 40% of agentic AI projects will be cancelled by 2027. The failure pattern is consistent: teams ship agent systems fast, then discover they have no evaluation pipeline, no drift detection, no containment model, and no plan for what happens when the system degrades under real load.
The models are capable. The engineering discipline to make them reliable, secure, and production-grade barely exists.
Context Engineering
Instruction architecture, memory systems, and attention budget management for long-running agents.
Evaluation Engineering
Domain-specific eval rubrics, LLM-as-judge pipelines, and production drift detection.
Adversarial Defense
Prompt injection hardening, agent identity governance, and AI supply chain security.
Every tool we recommend to a partner, we've already broken in-house.
Currently exploring: self-evolving agent systems, domain-tuned model portfolios, and spatial reasoning for physical environments.
The discipline is the product.
If this resonates, let's talk.