Author Archives: Allen Rodriguez
Savings Plans and EC2 Reserved Instances both exchange flexibility for lower compute pricing, but they bind that commitment in different ways. Savings Plans commit to a consistent amount of eligible usage measured in dollars per hour. Reserved Instances commit more directly to an EC2 configuration and, depending on scope, can also provide capacity reservation. The […]
AWS Transit Gateway route tables can be used as routing domains that segment groups of VPC, VPN, Direct Connect, peering, and other supported attachments. The useful mental model is similar to virtual routing and forwarding: an attachment sends traffic into one associated transit gateway route table, and that table determines which destination attachment receives the […]
“Vertex AI Model Armor” is a useful search term, but the current Google Cloud product is Model Armor, a separate security and safety service that can protect generative-AI traffic, including Gemini requests on Google’s current Gemini Enterprise Agent Platform. Google renamed much of the Vertex AI generative-AI surface in April 2026, so architects now need […]
Microsoft AI-103: Foundry Evaluation Datasets Microsoft Foundry evaluation datasets provide a reusable test asset for measuring model or agent quality across prompt, model, and agent versions. Current Foundry guidance describes JSONL as the common reusable format and supports turn-level and conversation-level evaluation, uploaded/versioned datasets, inline data, synthetic generation, trace-derived datasets, and evaluation directly from stored […]
Microsoft AI-103: Foundry Model Benchmarks Microsoft Foundry model leaderboards help teams compare models across quality, safety, throughput, estimated cost, and scenario-specific benchmarks, but current Microsoft documentation labels the leaderboard feature as preview and warns against treating preview capabilities as production guarantees. For Microsoft AI agents, the leaderboard is best used to narrow candidates and understand […]
Microsoft AI-103: Foundry Model Catalog The Microsoft Foundry model catalog is a discovery surface for Microsoft, partner, and open-source models with model cards, task and modality information, benchmark data, licensing details, and deployment options. Current Foundry guidance also distinguishes serverless API and managed-compute deployment paths, with some models supporting instant access. For Microsoft AI agents, […]
Microsoft AI-103: Foundry Tool Connections Microsoft Foundry tool connections are where an agent’s reasoning meets external authority. A model can decide that it needs customer data, a search result, a calculation, or an operational action, but the connection determines how that tool is reached and which identity is allowed to use it. Foundry Agent Service […]
Amazon AWS AIP-C01: DynamoDB for Agent State DynamoDB is a strong fit for some kinds of agent state because agent workflows often need a durable, low-latency record of facts that must survive process restarts: current workflow step, tool-call result, idempotency key, task status, user-to-session mapping, or a checkpoint that lets an execution resume safely. The […]
Amazon AWS AIP-C01: ECS vs EKS for AI Services Amazon ECS and Amazon EKS can both run containerized AI services, but the important choice is not “which service supports AI?” Both do. The decision is which orchestration model best fits the platform team’s existing skills, portability requirements, operational controls, workload shape, and need for the […]
Amazon AWS AIP-C01: Embeddings with Amazon Titan Amazon Titan Text Embeddings V2 turns text into vectors that can be compared for semantic similarity in retrieval, search, clustering, classification, and related workflows. The model is simple to call, but embedding quality depends on more than the model endpoint. Chunk boundaries, dimensions, normalization, source language, vector-store configuration, […]
Amazon AWS AIP-C01: Event-Driven AI Workflows Generative AI systems become operationally interesting when inference is only one step in a larger process. A document arrives, a customer record changes, a security finding is created, a batch completes, or a human approves a request; that event can trigger retrieval, classification, generation, tool calls, validation, and downstream […]
Planning Copilot Studio Generative Orchestration Generative orchestration in Microsoft Copilot Studio changes the agent from a collection of manually routed topics into a planner that can select multiple tools, topics, knowledge sources, and other agents to satisfy a request. Current Microsoft guidance describes this as the standard harness: an LLM-driven layer interprets intent, fills inputs […]
Measuring GitHub Copilot Adoption and Impact GitHub Copilot usage analytics now show more than the number of licensed seats: teams can distinguish activation, engaged usage, and meaningful engineering activity. Current GitHub documentation describes dashboards and APIs for adoption, engagement, code generation, agent use, model use, pull-request lifecycle signals, and per-user or repository reports. For engineering […]
Claude structured outputs make JSON reliability an interface-design problem instead of a prompt-formatting gamble. Anthropic supports schema-constrained JSON through `output_config.format` and strict tool inputs through `strict: true`; these validate completed, non-refusal outputs against a supported JSON Schema subset. A refusal or a response stopped by a token limit can still interrupt the requested JSON contract, […]
Claude API cost control is an architecture discipline, not a single billing setting. A request can become expensive because the chosen model is larger than the task requires, the input history grows without context management, outputs are unconstrained, cache reuse is poor, retries multiply work, or traffic ramps into rate limits. Cost-aware Claude engineering measures […]
