Long-form essays from the engineers shipping AI inside payers, hospitals, energy operators and proptech platforms. Written for technology leaders who care more about what runs in production than what trended last week.
EU AI Act enforcement begins August 2026 with specific obligations for healthcare AI systems. Five compliance areas matter most. Here is the practitioner guide for organizations that have not yet…
AI scribes have moved from pilot to production at scale. The operational realities differ from the marketing in specific ways. Eighteen months of production experience reveals five patterns that…
Healthcare cloud architectures spanning regions face data residency, latency, and failover questions that single-region architectures do not. Four patterns handle the realistic complexity. Here is…
AWS HealthLake handles FHIR workloads at enterprise scale with specific operational characteristics. Three workload patterns fit, three do not, and three production realities affect deployment…
Pharmacovigilance signal detection has moved from periodic batch review to continuous pipeline analysis. The pipeline patterns that produce reliable signals share recognizable structure. Here is…
Risk stratification models can be accurate in development and clinically wrong in production. The gap usually traces to calibration and drift issues. Here are the patterns that catch the issues…
FHIR gets the attention. The reality is healthcare data still flows through HL7v2, X12, custom formats, and PDFs. Engineering teams that handle the real mix produce more reliable platforms than…
Population health AI work that produces results follows a recognizable path from cohort definition through intervention delivery. The patterns that work share four characteristics. Here is the…
Commercial real estate AI has emerged as distinct from residential AI through 2024 and 2025. Four use case categories cover most production deployments. Here is the practitioner reference for…
Predictive maintenance in commercial buildings has moved from pilots to production deployments. Three sensor patterns, three model patterns, and three operational patterns produce reliable…
Real estate platforms integrate three primary data sources with very different update patterns and data shapes. The unification work has specific patterns that most platform teams underestimate.…
AI workloads on AWS have settled into a recognizable five-layer reference. Most enterprise teams get one or two layers wrong on first deployment. Here is the reference and the specific mistakes…
Mid-market and enterprise AWS migrations succeed when scoped as three waves rather than as one big-bang program. Each wave has different goals and different success criteria. Here is the playbook…
AWS native observability tools each cover a portion of what production systems need. Three gaps remain where third-party or custom tooling is required. Here is the reference with the gaps explicit.
Production-grade RAG on AWS has five stages from ingest to response. Each stage has AWS-native services that fit and ones that do not. Here is the reference architecture with the specific service…
One-time AWS cost audits produce one-time savings. Continuous FinOps loops produce sustained reduction. A weekly cycle with five steps converts one-time savings into compound improvement. Here is…
AWS Step Functions is one of the better orchestration choices for agentic AI workloads, and not the right choice for some others. Three patterns describe when it fits. Here is the operating reference.
Most AI implementation problems trace to data infrastructure that was not ready when AI was added. Five readiness conditions determine whether your stack can support LLMs. Check them before adding…
Learn what Data Engineering means in 2026: pipelines, contracts, observability, and the operating model behind every modern data platform.
Amazon Prime Video cut 90% off infrastructure cost going from microservices back to a monolith. 42% of orgs are doing similar. Here's the decision framework.
AI adoption hit 90% of engineering teams. But senior engineers see 5x the productivity gain juniors do. The culture gap is now the biggest org problem CTOs face.
75% of VC deal reviews are now AI-informed. By the time investors find your AI issues in due diligence, it's too late to fix the cap table consequences. Here's the audit you run first.
AI inference spend hit $37B in 2025, up 3.2x in a year. The CFO is about to ask why. Here's the per-request framework that produces the answer they want.
75% of VC deals are AI-informed. 90% of VCs use AI tools to screen. Here are the 12 technical questions you'll be asked, with the answers that close faster valuations.
One long-form essay every other Wednesday. Written by the engineers shipping production AI for our clients, not by a content team. No promotional emails. Unsubscribe in one click.
