Why agent harnesses need fast decisions
Latency compounds inside agent loops; fast decision layers make routing and gating affordable.
TenthMatrix Insights
Articles, reproducible benchmark methodology, architecture diagrams and model-selection guidance for engineers, architects and technical leaders. Not a product announcement blog — an independent editorial lab.
The Jev series
Ten chapters that investigate specialised decision models, agent harnesses, routing, safety and the changing economics of inference — without treating vendor headlines as independent facts.
Hands-on surfaces that stay versioned as models change.
Long-form
5,000+ word engineering deep dive with architecture, citations and limitations.
Lab
Compare systems by metric with source kind filters.
Guide
Map workloads to candidate model types and key metrics.
Timeline
From LLMs to composable AI systems with dated sources.
Every article in the publication, newest first.
Latency compounds inside agent loops; fast decision layers make routing and gating affordable.
Put allow / deny / escalate in front of shell, deploy, delete and data-mutating tools — and measure false negatives like production incidents.
A living TenthMatrix guide to the shift from monolithic LLMs toward tools, reasoning, agents, routers and specialised decision models.
An evergreen TenthMatrix manual for selecting models by workload — intelligence, latency, cost, tools, calibration and risk — without fake “best model” rankings.
TenthMatrix’s reference architecture for planners, fast decision layers, routers, tool gates and evaluators — inspired by public LangChain patterns, implemented as our own design.
What happens when decision intelligence gets dramatically cheaper — and which engineering disciplines become mandatory.
How TenthMatrix structures suites, source kinds, reproducibility packs and non-claims.
An independent TenthMatrix series on System One models, agent harnesses, routing, safety and inference economics — with citations, not cheerleading.
A TenthMatrix long-form investigation of System One models, harnesses, routing, safety, RAG judgement, benchmarks and model selection — with strict attribution.
How to build and measure routers that send simple work to cheap models and hard work to expensive ones — without assuming the router helps.
Complementary roles for generative models and decision models in production AI systems.
A TenthMatrix field guide to TypeSafe’s System One model: structured decisions, probabilities, confidence gates, and the boundaries engineers should respect.
A technical publication spanning the stack builders actually ship.
Read the research, then jump into agents, apps and jobs.