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.
The common infrastructure as code pitfalls: drift from manual changes, no state discipline, copy-paste sprawl, and no testing, and how to avoid each.
Invest in CI/CD pipeline design or keep your current deployment process? A VP Engineering decision guide on when the investment pays off and when it is premature.
How energy and utilities teams add pipeline monitoring without disruption: instrument running data pipelines incrementally, starting where failures hit operations.
How to approach semantic layer design in real estate: get the organization to agree on one definition per metric (NOI, occupancy, cap rate) and govern it, then build.
The 2026 trends shaping change data capture in healthcare: real-time, reliable sync of clinical data with the PHI handling and auditability healthcare demands.
Rightsizing cloud spend explained: the concepts behind matching resources to real usage, the benefits of doing it, and the trade-offs against reliability headroom.
A practical roadmap to cloud security posture: gain visibility, prioritize by risk, remediate, and prevent with guardrails, so posture improves continuously instead of via one-time scans.
The common AI model risk management pitfalls: policy without controls, pre-deployment-only validation, no intervention path, and uniform governance, and how to avoid each.
How Logiciel delivers Kubernetes at scale for real estate: the engagement, the foundations, and what you get when many services run reliably on orchestration.
A framework for Kubernetes cost control in mid-market and enterprise teams: make spend visible, right-size, and assign accountability, in that order.
A DevOps lead's checklist for implementing container orchestration: get the foundations (networking, storage, security, observability) right, not just a running cluster.
How Logiciel delivers data lineage for the enterprise: the engagement, the work, and what you get when data flow becomes automatically captured, current, and navigable.
How to measure and prove real-time data ingestion ROI: quantify the value of fresh data for decisions, against the higher cost and complexity versus batch.
How Logiciel delivers feature stores for real estate: the engagement, the work, and what you get when ML features become consistent, reusable, and governed.
How to build a business case for high-availability systems in healthcare: justify the cost on the clinical and operational impact of downtime, not just uptime numbers.
Best practices for MLOps at enterprise scale: standardize the model lifecycle, automate the path to production, and monitor models, so many models ship reliably.
Choosing an AIaaS adoption partner: the questions a VP of Engineering should ask to find one who helps draw the consume-versus-build line, not just wire up APIs.
Taking AI model risk management from strategy to production with an engineering partner: the gap between a risk policy and operational controls on real models.
Container orchestration or your current deployment approach? A VP Engineering decision guide on when orchestration's complexity pays off and when it is premature.
How to measure and prove data unification ROI: quantify the cost of fragmented data, the value of a unified view, and weigh it against the integration effort.
A practical roadmap to multi-cloud strategy: adopt multi-cloud for a real reason, deliberately, because accidental multi-cloud multiplies cost and complexity for nothing.
A decision framework for internal developer platforms in mid-market and enterprise teams: when an IDP is worth building, what to build first, and when it is premature.
How to build a business case for LLM evaluation and testing in energy and utilities: justify it on the operational risk of deploying an unevaluated LLM near the grid.
Self-service analytics explained: the concepts behind letting people answer their own data questions, the benefits when governed, and the trade-offs when it is not.
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.
