Sep 09, 2026

Your agents lack context: Here's how to fix "You're absolutely right!" — Brandon Waselnuk, Unblocked

Brandon Waselnuk of Unblocked discusses the critical need for robust context engines in AI-driven software development. He explains how AI agents' lack of company-specific understanding leads to compounding costs like wasted tokens and rework. Waselnuk outlines common pitfalls in providing context and details six essential characteristics of an effective context engine, demonstrating its impact with a 50% token reduction and significant time savings. He also introduces three open-source tools from Unblocked, including a workshop to build a relational context engine, emphasizing that "access to information is not understanding" and that context, not intelligence, is the current bottleneck for AI effectiveness.

Aug 21, 2026

Building Agents Is Trivial Now, Context Is the Next Frontier — Jeff Ng, Unblocked

Building AI agents is now easier than ever, but they frequently make confident yet incorrect decisions. This is because agents often lack critical context that humans provide, such as historical discussions, postmortems, and tribal knowledge. The solution proposed is a 'context engine' that synthesizes and grounds information from across an organization's documents, code, tickets, and conversations, providing agents with a holistic and reconciled view, thus bridging the 'context gap' that current LLMs often miss.