Technical decisions
Engineering for business decisions
Architecture, legacy and MVP decisions with context: when to intervene, where to reduce risk and how to build without hidden debt.
- strategyST2 min read
Why corporate software initiatives fail before code
Many software initiatives fail because of unclear scope, fragile data, weak adoption and no operational owner before the first delivery.
- strategy
- operations
- risk
- mobileMO2 min read
Native app or web app: product, cost and operations decision
How to choose between a native app and a web app considering usage frequency, distribution, integration, team and cost of evolution.
- mobile
- product
- architecture
- mvpMV2 min read
MVP without hidden debt: what must be right from the first release
How to ship fast without creating a foundation that blocks billing, operations, and evolution right after launch.
- mvp
- product
- architecture
- mlopsML2 min read
Your model works until operations change: why MLOps matters
Production models break because of data, context, versioning and lack of operational routine, not only because of algorithm errors.
- mlops
- ai
- operations
- architectureAR2 min read
Microservices: when architecture makes the problem larger
Microservices can reduce coupling, but they can also multiply deployment, observability, duplicated data and coordination cost.
- architecture
- microservices
- operations
- architectureAR2 min read
When rewriting a legacy system stops being overkill
A pragmatic decision path for choosing between stabilizing, slicing, or rewriting a system that has become operational risk.
- architecture
- legacy
- risk
- legacyLE2 min read
Legacy modernization without rewriting everything
How to evolve critical systems in stages, reducing operational risk without betting on a complete rewrite.
- legacy
- modernization
- architecture
- uxUX2 min read
A working system nobody wants to use: the operational cost of poor UX
When an internal system works on paper but forces workarounds, spreadsheets and rework, the problem stops being aesthetics and becomes cost.
- ux
- operations
- product
- generative aiGE1 min read
Generative AI in production: leaving the experiment without losing control
What needs to exist to turn a generative AI prototype into a reliable operational workflow.
- generative ai
- architecture
- product
- diagnosisDI2 min read
How to diagnose software bottlenecks before hiring more people
A simple method for separating technical, process, and decision bottlenecks before increasing team size.
- diagnosis
- performance
- operations
- devopsDE2 min read
A pipeline is not DevOps: what changes when operations mature
CI/CD matters, but mature DevOps involves ownership, observability, rollback, incidents and learning cycles.
- devops
- operations
- reliability
- aiAI2 min read
AI observability: what to measure before an agent becomes risk
Logs, metrics and operational signals to know whether an AI automation stays reliable after it reaches production.
- ai
- observability
- risk