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.
Learn the 9 things your stack needs for an AI-Ready Data Platform in 2026: retrieval, lineage, contracts, observability, governance, and the operating model.
Learn Data Observability in practice in 2026: a case study showing how the right observability cut incident response time 70%, with the playbook to follow.
Learn Change Data Capture in 2026: why CDC is the under-rated piece of a modern data stack, patterns that work, and the operating model behind reliable CDC.
Learn the data pipeline patterns enterprise teams are standardizing on in 2026: medallion, lakehouse ELT, streaming-first, and the operating model behind each.
Pitch decks describe AI engineering capability. Code reviews reveal it. Six engineering markers separate partners who ship from partners who promise. Here is what to look for in the artifacts, not…
Aggregate AI cloud spend hides the unit economics that matter for product decisions. Five inputs determine cost per request. Knowing the calculation gives product, finance, and engineering a…
Most enterprise AI value lives in existing products that nobody wants to rewrite. Four integration surfaces let teams add AI without rebuilds. Here is the pattern reference with the operational…
Multi-agent AI in financial services has regulatory and operational implications that other industries do not face. Four control layers govern production deployments. Here is the architecture with…
Most enterprises run LLM evaluation as ceremony, not engineering. A real eval harness has five components and runs in CI. Here is the buildout reference with the operational details vendors omit.
Small language models have closed enough of the capability gap that for specific workloads they outperform frontier LLMs on the metrics that matter. Four conditions define the sweet spot. Here is…
Production AI models do not stay still. Three decay modes account for most quality loss over time. Each one needs a specific monitoring approach. Here is the reference and the corresponding…
Human-in-the-loop is required by EU AI Act for high-risk systems and important for almost every production agent. Three architectural patterns dominate. Picking the right pattern shapes both…
Most AI readiness assessments are too long to act on. Ten specific signals separate organizations ready to scale AI from organizations that will struggle. Here is the diagnostic and what each…
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.
Board questions about AI have shifted from "are we doing it" to "what could go wrong and what is our response." Five specific questions now appear in roughly every board meeting. Here are the…
The model is roughly 10% of what it takes to run an LLM in production. The other 90% is the operational stack. Here are the five capabilities a CTO needs to fund alongside any serious LLM commitment.
Most agentic AI portfolios spread investment thin and produce modest results. Three workflow profiles consistently pay off first. Picking from these profiles is the difference between a productive…
ISG's 2024 report shows 47% of AI engagements renew at lower scope after year one. Twelve specific diagnostic questions surface the partner-fit issues that standard RFPs miss. Use them before…
Most enterprise AI value lives one integration away from legacy systems. The integration patterns that work fall into five modes. Here is the field guide with the practical tradeoffs each mode…
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.
The gap between demo and production has predictable causes. NIST identifies three specific reasons demos lie. Knowing them before launch is cheaper than learning them from customer complaints.
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.
