All articles
AI features break in ways traditional testing can't catch. This is the case for evaluation-first engineering, the discipline that prevents silent regressions and keeps LLM-powered products reliable at scale.
By Rob Teegarden
10 min read
As AI generates more of the codebase, code review as we know it is becoming a bottleneck. The fix isn't faster review. It's review happening earlier, at the level of intent.
By Ayman Shoukry
12 min read
How Engineering Leaders Can Structure the PdM-PjM Partnership to reduce thrash and improve delivery predictability
By Renata Matos
11 min read
The real architectural shift isn't single-cloud to multi-cloud. It's cloud-agnostic to cloud-sovereign.
By Chris Haire
7 min read
Most AI pilots stall before production. Learn how to sort use cases by capability pattern, integration risk, and time to proof.
By Daniel Avila
11 min read
Machine Learning vs. Artificial Intelligence: What you’re Actually Building and When to Buy vs Build
Stop debating labels. Learn the production tradeoffs, governance risks, and hidden costs that determine whether to build in-house or buy AI capabilities.
By Agustín Achille
13 min read
See how engineering leaders reduce Kubernetes costs through visibility, team accountability, and safe autoscaling without sacrificing reliability or velocity.
By Jimmy E. Bonilla
11 min read
Most enterprises are running AI pilots that never reach production. Two seasoned technology executives break down what it actually takes to restructure an organization around AI.
By Bob Leibholz
7 min read
See how large Java teams can use governed multithreading to improve performance, reduce incident risk, and keep critical services predictable.
By Fernando Ugarte
11 min read
As software shifts from code-first to intent-first, engineering leaders must rethink how systems are built and delivered. In the process, value moves upstream into context, constraints, and provable outcomes.
By Ayman Shoukry
11 min read
Systems-level overview of large language models for engineering leaders: how they work, where they fit, and the risks you need to plan for.
By Alejandro Cordova
13 min read
A practical guide to scaling software engineering teams: pod design, onboarding, quality guardrails, and metrics that reveal what’s really happening.
By Gilberto de Denghy
11 min read
As AI matures inside software teams, women gain career autonomy, accountability sits with individuals, and validation emerges as the defining skill separating acceleration from sustainable engineering practice.
By Rodrigo Outumuro
7 min read
Your AI ambitions are moving faster than your data. This article shows how to scale enterprise AI pragmatically, using a proven maturity model and execution strategies before competitive advantage slips away.
By Charles Boyle
9 min read
Decide when to use off-the-shelf LLMs, when RAG on your data is enough, and when fine-tuning or full training is worth the cost, risk, and overhead.
By Alejandro Cordova
12 min read