We operate where frontier AI meets production reality: agentic architectures, retrieval systems, evaluation science, and AI-augmented software pipelines. Technical jargon welcome — hand-waving is not.
Tool-use agents, multi-agent orchestration, memory architectures, delegation topologies. We probe models empirically before trusting them in any loop.
RAG pipelines, knowledge graphs, citation-grounded generation. Every factual claim traceable to a verifiable source — no synthetic authority.
Benchmark harnesses (MMLU, GSM8K-class), regression suites, red-team probes. If it can't be measured, it doesn't ship.
Agent-driven development workflows: plan → spike → implement → verify. Humans own architecture and gates; agents own velocity.
Anti-hallucination policy as engineering discipline: verify-against-disk, artifact-first reporting, honest blocker escalation over fabricated output.
vLLM serving, quantization (GGUF/GPTQ), edge functions, cost/latency optimization. Research that pays its own inference bill.
Literature review before architecture. Benchmarks before claims. Every engagement ends with evaluated artifacts, reproducible runs, and documentation a stranger could audit.