Insights
Life at WeBuild-AI: meet Linda Joseph, fuelled by cups of tea to tackle designing data governance, LLMs, generative AI and more
Linda Joseph, Lead Data & AI Consultant, shares more about her current projects, career journey, technical prowess and why she thrives in the WeBuild-AI team.
Rethinking Engineer Interviews: Why We Don't Do Take-Home Tasks
WeBuild-AI interviews for engineers don’t include any steps with take-home tasks - find out why we approach job interviews differently, from in-house Talent Partner, Rachel O’Keeffe.
Life at WeBuild-AI: meet Vincent Farah, Lead Consultant - from love letters to Python, to coffee as a debugging tool
Meet Vincent Farah, Lead Consultant at WeBuild-AI, to learn about switching hats between AI consulting and software engineering, and his journey from teenage coder to clean architecture aficionado.
Why most AI projects fail (and it’s not about the technology)
Innovation versus governance doesn’t have to be a trade-off, and can lead to greater advantages. Read on to learn how CTOs, CSOs and CIOs balance both.
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
The WeBuild-AI Perspective on Context Engineering
Context Engineering promises dramatically better AI outcomes, yet the reality involves substantial trade-offs in token economics, latency, and MCP infrastructure investment that determine what's actually feasible at enterprise scale.
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.
Life at WeBuild-AI: meet Pranav Patel, Lead Consultant
Meet Pranav, Lead Consultant at WeBuild-AI, as he shares some insight into his role, day-to-day tasks and favourite parts of WeBuild-AI.
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.
How We Harness AI to 10X our Software Engineering Teams
How does WeBuild‑AI integrate AI deeply into development processes, freeing engineers from repetitive work and accelerating delivery while preserving code quality?
Joining the 5% Inner Circle: Moving Beyond the AI Failure Narrative
Discussing what organisations must do to join the small group that succeeds in AI adoption - only 5%, according to MIT research from 2025.
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.