InsightsShort reads on shipping reliable software for healthcare, cybersecurity, and AI — guardrails, architecture, and practical lessons from real systems.
A practical engineering guide to voice AI latency covering endpointing, WebRTC, streaming audio, realtime models, tool calls, barge-in, telephony, latency budgets, p95 monitoring, and production optimization.
A production guide to AI document processing covering OCR, layout analysis, tables, intelligent extraction, structured outputs, field validation, human review, evaluation, healthcare data, and workflow integration.
A practical healthcare LLM evaluation framework covering context of use, harm modeling, datasets, task-specific metrics, graders, RAG, clinical outputs, tools, subgroups, release gates, and continuous monitoring.
An engineering field report on the recurring reliability lessons from 16+ production AI agents: system boundaries, structured outputs, contextual evals, human review, latency, tool safety, tracing, and recovery.
A practical guide to LLM structured outputs covering JSON Schema, strict function calling, schema design, TypeScript implementation, domain validation, versioning, evaluations, and production lessons.
A practical guide to ambient AI medical scribes covering audio capture, transcription, clinical extraction, note generation, failure modes, validation, clinician review, EHR integration, HIPAA considerations, and implementation.
A practical AI-agent cost guide covering prototype and production budgets, project types, integrations, guardrails, evaluation, monthly operating cost, timelines, and build-vs-buy decisions.
A production guide to reducing LLM hallucinations with grounded evidence, structured outputs, deterministic validation, permissioned tools, prompt-injection defenses, evaluations, monitoring, and human escalation.
A practical guide to HIPAA-compliant software development covering PHI data flows, risk analysis, access control, auditability, encryption, BAAs, secure delivery, incident response, and the current regulatory direction.
A practical guide to healthcare AI voice agents: patient intake workflows, architecture, latency, safety guardrails, EMR integrations, build-vs-buy decisions, timelines, and realistic development costs.
A practical guide to building production AI agents with controlled architecture, structured outputs, guardrails, evaluations, observability, latency engineering, and realistic cost ranges.
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