Most agent systems degrade in production. We engineer the ones that don't.
Evaluation harnesses, adaptive memory systems, and production infrastructure for agents. Our work ranks #1 on TermBench. Small practice, deep work, real engineering.
Agent Performance
Most agent demos work. Most agent systems in production don't. The gap is evaluation, not prompting.
We build evaluation frameworks that quantify output quality across defined criteria. Prompt architecture, context engineering, retrieval optimization, tool design, and multi-agent coordination — all measured against benchmarks, not vibes.
If you can't measure it, you can't improve it. We start with the measurement.
Production Infrastructure
An agent without observability is a liability. An agent without scoped permissions is a security incident waiting to happen.
We build orchestration for multi-agent workflows, tracing through every decision path, safety constraints with scoped permissions, and deployment pipelines with versioning and rollback. Agents integrate into your existing services without introducing fragility.
Production readiness is a design constraint from day one, not a phase you bolt on later.
How We Work
We embed with your engineering team for a defined engagement. Scope depends on where you are and what's blocking progress.
Assess
We benchmark your agent systems against TermBench-grade criteria — not vibes, not demos. Architecture, evaluation coverage, production readiness. This takes days, not weeks.
Build
Evaluation frameworks, orchestration layers, memory architecture, integration patterns. We write production code, not recommendation decks.
Transfer
You get a working system, evaluation frameworks, and the context your team needs to maintain and extend it independently. We leave infrastructure, not dependencies.
Research
Our client work is informed by a deeper question: what are the structural primitives required for general intelligence, and how far are current systems from having them? We build the tools to answer that.
Intelligence Primitives
We work from both ends. What are the true primitives of intelligence — the irreducible building blocks required for AGI at scale? And what do today’s systems actually have? We define those primitives, map them to engineering constructs, and measure the gap between what exists and what’s needed.
TermBench #1
That research needs measurement infrastructure. We built the top-ranked agent evaluation harness on TermBench — not as a side project, but as the instrument for testing our thesis. We evaluate where current systems are sustainable over long contexts and where they break down.
Adaptive Memory
Memory is the first primitive we’re solving. Context bloat degrades agent intelligence over time. Our persistent memory architecture reduces that degradation by 200%, maintaining reasoning quality across extended interactions — a prerequisite for every other capability that matters.
Writing
We write about the engineering problems we encounter.
Building evaluation frameworks for agent systems
Automated scoring, LLM-as-judge, and human review in a single framework. Evaluation is the highest-leverage investment in any agent project.
Get in Touch
If you're building agent systems and the engineering problems are real, we'd like to hear about them.
Or email us directly at hello@reactorjet.com