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.
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.
MIT found 91% of production AI models drift within a year. 67% fail silently. AWS DevOps Agent now detects regressions in 4 minutes. Here is what reliability means when your software thinks.
GitHub research shows AI now writes 46 percent of code in adopted teams. The SDLC has reshaped around review, evals, and the 11-week ramp. Here is the new shape and what breaks if you ignore it.
GenAI spend hit $37B globally in 2024 and inference now dominates AI cost lines. Five FinOps levers that actually cut the bill: caching, tier routing, batch shifting, prompt economics, and…
DORA dropped the elite/high/medium/low buckets in 2025. Top teams now track AI-attribution metrics, developer experience, and business outcome alignment alongside DORA. Here's the new picture.
Morgan Stanley logged 280,000 developer hours on legacy migration before AI cut it in half. Here is what legacy risk actually costs a CTO in 2026 and how to price it.
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.
