Five complementary disciplines the founder brings together to build, protect and evolve platforms teams can operate.
Choose an expertise area based on the technical decision you face. These pages explain capabilities and trade-offs; service pages describe a specific engagement and its deliverables.
FIVE AREAS
Design governed, connected Cloud foundations that can evolve without turning every new project into an exception.
Explore this expertiseMake spending understandable and manageable without sacrificing performance or availability.
Explore this expertiseProtect applications without blocking legitimate journeys or leaving teams with invisible exceptions.
Explore this expertiseIndustrialize delivery without passing pipeline and access complexity on to product teams.
Explore this expertiseDesign measurable, governed LLM workflows without confusing a prototype with production operations.
Explore this expertiseCROSS-DISCIPLINARY APPROACH
Architecture, security, costs, automation and AI meet on the same platforms. A networking decision affects access and operations; a capacity choice affects spend and performance. I start with your specific constraint to identify the relevant expertise, without turning every question into a company-wide program.
Architecture and security define network boundaries, identities and recovery. Application teams need to understand these decisions and deploy without creating invisible parallel paths.
DevOps and FinOps connect automation, capacity and economic ownership. Standards remain versioned and exceptions justified; a lower bill is not worth lost availability or a shifted burden on teams.
AI fits into an existing architecture with minimized data, quality measures and a fallback mode. A recommendation becomes a sensitive action only after checks and an authorized decision.
CONNECTED CHALLENGES
The Cloud path determines private flows and where requests are inspected. A WAF choice also depends on legitimate journeys and log visibility; migration cannot ignore protection or rollback.
Shared pipelines reduce divergence but change runner and cluster consumption. Isolation, waiting times and deployment permissions must be weighed against the full platform cost instead of sizing capacity from an average.
Before connecting a model to real events, separate inference, deterministic rules and human approval. Quality, latency, confidentiality and cost per use guide the model choice and fallback path.
AKITA / CONTACT
Tell me about the constraint or decision ahead: I'll identify the expertise needed and suggest a useful first step.
