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.
SRE explained for real estate technology leaders: what it is, why it matters for the platforms your business runs on, and what to know without being an engineer.
A practical, phased roadmap to data observability: start where bad data hurts most, instrument the pipelines that matter, and build the practice that catches issues before users do.
A VP Product's introduction to building an enterprise AI roadmap: sequence by value and readiness, not hype, and treat data and trust as the real dependencies.
The common observability strategy pitfalls that produce huge bills and no answers: collecting everything, dashboards nobody uses, alert fatigue, and how to avoid each.
Best practices for cloud cost optimization at scale: make cost visible and owned, fix the structural drivers, and build the practice that keeps spend from creeping back.
How to build a business case for managed AI services in real estate: the real cost comparison, the speed-to-value, and the data and lock-in risks to weigh honestly.
The 2026 trends shaping ELT modernization in healthcare: why providers are moving transformation into the warehouse, and what PHI and compliance change about it.
SRE or your current DevOps status quo? A decision guide for DevOps leads on when SRE's overhead pays off and when your existing approach is already enough.
A CTO's implementation checklist for site reliability engineering: the decisions and foundations to get right so SRE becomes a practice, not a renamed ops team.
How enterprises cross from an AI-ready-data strategy to production data infrastructure with an engineering partner: the gap, the path, and what a partner adds.
How healthcare organizations should approach well-architected reviews: treat them as a recurring risk practice tied to patient safety and compliance, not a one-time checklist.
From strategy to production: how enterprises take MLOps from a slide to running infrastructure with an engineering partner, the gap, the path, and what a partner adds.
How to measure and prove cloud migration ROI: the real baseline, the costs that arrive before the savings, and the business value beyond the bill that justify the move.
How Logiciel delivers SLOs and error budgets for energy and utilities: the engagement, the work, and what you get when reliability targets must reflect grid stakes.
RAG architecture explained: the concepts behind retrieval-augmented generation, the benefits when it fits, and the trade-offs to weigh before building on it.
The state of managed AI services in enterprise for 2026: what enterprises are buying as managed, where they keep control in-house, and how the buy-vs-build line has settled.
How to approach developer experience in enterprise organizations: treat DevEx as a measurable outcome with an owner, not a perk, and improve the friction that slows delivery.
A practical roadmap to GitOps: the phased path from ad hoc operations to a reviewed, self-correcting, auditable system, with what to do at each stage and what to avoid.
How Logiciel delivers securing AI systems for real estate: the engagement, the work, and what gets delivered when AI handles listings, valuations, and tenant data.
The common application modernization pitfalls that stall or sink projects, big-bang rewrites, no definition of done, lost domain knowledge, and how to avoid each.
Embedding AI into existing products explained: the concepts, the benefits when it works, and the trade-offs to weigh before adding AI to a product already in production.
How to measure and prove AI reliability engineering ROI: the cost of unreliable AI, the improvement, and the business value that justify the investment with a number.
Incident management explained for energy and utilities leaders: what it is, why it matters when systems affect the grid, and what to know to make incidents recoverable.
GitOps explained for real estate technology leaders: what it is, why it matters for reliable software delivery, and what to know before adopting 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.
