Insights
The SDLC in the Age of Agents: When Everything Happens at Once
How has the software development lifecycle changed in the age of AI agents? Read on to find out
How to Capture, Scale and Deploy Human Expertise with AI Agents
AI augments human skills - but in reality, we’re in an age of huge skills gaps and societal hiring difficulties. How do you use AI to optimise the time of your most valuable, skilled employees? Read on.
The Context Switching Tax: Here's How To Avoid The Tax Using AI
Enterprise businesses often have fragmented systems with disparate information, and rely on highly skilled engineers to be information repositories. No more - read on to learn about how Model Context Protocol enables context switching at scale.
Why (and why not) train a language model from scratch
Learn about why (and why not to) train a language model from scratch - plus, what would be required to implement in practice
Why Small Language Models Are the Key to Agent Independence
Open source small language models offer organisations a strategic path to building AI agents that avoid vendor lock-in, enable explainability for regulated industries and provide operational independence from the three dominant LLM providers.
How MCP Transforms Your Software Delivery Lifecycle
Gain insight into how Model Context Protocol (MCP) transforms the software delivery lifecycle, letting AI agents work across your system and integrate seamlessly with your data.
Why Your Organisation Needs Agent Lifecycle Management
Explore why organisations should adopt full lifecycle management for AI agents for monitoring, governing, versioning and maintaining in business systems.
Webinar Replay: Unlocking the True Power of Enterprise AI
Watch our webinar recording, where we demonstrate how Model Context Protocol (MCP) and AI agents convert conversational AI into business tools.
What Metrics Matter for AI Agent Reliability and Performance
What are the key metrics and measurement strategies that organisations should monitor to ensure their AI agents behave reliably, safely, and usefully?
Why Prefect is A Perfect Pick for AI Agent Monitoring
Exploring how Prefect (a workflow orchestration tool) fits naturally into AI agent monitoring and enables tracing, alerting and observability of agent operations.
Delivering Differentiated AI-Enabled Products: Practical Field Lessons for the Enterprise
From field experience, WeBuild-AI shares lessons on how enterprises can build AI‑enabled products that are truly differentiated and scalable.
Will MCP Make RAG Obsolete?
We examine the relationship between Model Context Protocol (MCP) and Retrieval-Augmented Generation (RAG), asking if MCP’s capabilities will remove the role or shift the relevance of RAG in enterprise systems.
Our Principles for Building Enterprise Grade Generative AI
The foundational principles WeBuild‑AI used for building our Pathway platform, from AI‑native design to guardrails, ethics and automation as code.
Establishing Gen-AI Muscle Memory in The Enterprise
Learn how enterprises can build GenAI capabilities into daily workflows through continuous practice, experimentation and organisational learning.
The Technical Blueprint for Enterprise Scale Generative AI
Explore the architecture, tools and processes needed to scale generative AI across enterprise environments efficiently and securely.