General

API versioning is the practice of managing changes to an API contract so existing clients can continue working as a service evolves. An API may be used by a mobile app, a partner integration, an internal service, or customer-written scripts. A change that seems small to the team maintaining the API can break consumers that […]

The GraphQL vs REST decision affects how an application requests data, how teams design interfaces, and how they manage changes over time. REST organizes APIs around resources and standard HTTP methods. GraphQL lets a client request specific fields through a schema and query language. Either can support a reliable product; the right choice depends on […]

Test driven development (TDD) is a software development practice in which a developer writes a small test before writing the code that makes it pass. The cycle is often called red, green, refactor: create a failing test, implement the simplest change that passes it, then improve the design while keeping the tests green. TDD can […]

Infrastructure as code (IaC) is the practice of defining servers, networks, databases, permissions, and other infrastructure in version-controlled configuration files. Instead of creating each environment by hand, a team describes the desired state and uses a tool to provision or update resources. This makes infrastructure changes easier to review, repeat, and recover. IaC can reduce […]

A CI CD pipeline is an automated path that takes a software change from source control through validation and toward release. Continuous integration (CI) helps teams merge and test changes frequently. Continuous delivery or deployment (CD) automates later steps so a validated change can be released in a controlled way. Together, these practices shorten feedback […]

A data warehouse is a system that brings data from multiple business sources into a structured environment for reporting and analysis. It helps teams examine historical and current information without placing every analytics query on the systems that run daily transactions. A well-designed data warehouse can support dashboards, financial reporting, customer analysis, and operational planning. […]

LLM evaluation is the process of checking whether a large language model or AI application produces outputs that meet defined quality, safety, and business requirements. A response can sound fluent and still be inaccurate, incomplete, unsafe, or expensive to produce. Evaluation gives teams repeatable evidence about how a system behaves across realistic tasks. This guide […]

A vector database stores numerical representations of information, called vectors, and searches for items that are close to a query in meaning or other measurable features. A text search for “change my password” may miss a document titled “reset account credentials.” A vector search can connect those phrases when their embeddings capture similar meaning. Businesses […]

Retrieval augmented generation (RAG) connects a generative AI model to a selected knowledge source at the moment it answers a question. Rather than relying only on information learned during training, the system retrieves relevant documents and includes them as context for the model. Businesses use this approach to answer questions from policies, product manuals, contracts, […]

AI agents are software systems that use an AI model to interpret a goal, choose from available tools, and carry out a sequence of steps. Unlike a chatbot that only replies, an agent can look up a record, draft an update, or hand a task to another system. For a business, the value comes from […]