Context Engineering
Deciding what an agent sees, and what it is spared.
6 articles by Paul Scarrone.
- Agentic AI Engineering: Building Determinism Around a Non-Deterministic Engine A working definition of agentic AI engineering: treating tool-using language models as processes rather than conversations, and putting the determinism in the pipeline instead of the prompt.
- Judgement-Capable Circuits: What You Write Loops Out Of If the job is writing loops rather than prompts, the question is what you write them out of. A circuit is deterministic wiring with judgement localised to specific nodes, assembled from tmux, an event transport, and generated prompts, running on credentials you already hold.
- Five Techniques That Keep Paying Off When You Build for LLMs Six months of building tools for LLMs, distilled into five techniques: embedding and vector search, structural indexing, harness engineering, hooks, and why agents are better at writing code than using tools.
- Wavelet Google Wave's data model repurposed as a coordination substrate for multiple chat agents - forked conversations, cursor-based wake semantics, and deterministic targeted delivery that keeps an agent's context about what concerns it
- Agentic Patterns: Elements of Reusable Context-Oriented Determinism Exploiting tool-using LLMs as processes instead of conversations - patterns for keeping context focused and outputs deterministic
- A Deterministic Box for Non-Deterministic Engines Taming LLM non-determinism through structured workflows, task tracking with Beads, and memory management strategies for more predictable AI-assisted development