Tool-based agent memory: why 2026 benchmarks favor it
Tool-based agent memory exposes store, retrieve, and navigate as callable MCP tools. 2026 benchmarks from Mem0, Memanto, and Wire show why the pattern wins.
Further reading
Articles about Structured Context
10 articles from the Wire blog, sorted newest first. Return to the Structured Context definition for context.
Why AI customer support replies sound generic
AI support replies sound generic because teams treat brand voice as a prompt problem. Context engineering fixes it by selecting the right exemplars.
TOON vs JSON: why smaller doesn't mean cheaper for LLMs
TOON looks more compact than JSON, but a 9,649-test study found it cost LLMs 38% more tokens. The reason: model training distribution beats format size.
Provenance is a context engineering primitive, not a trust score
Retrieval provenance for AI agents isn't an audit log or a trust verdict. It's structural metadata (source, position, time, edges) agents use to plan.
How context engineering reduces AI hallucinations
Most AI inaccuracies in production are context quality failures, not model fabrications. Here's the research on what context engineering actually changes.
Why Customer Support AI Gives Wrong Answers
AI customer service fails at 4x the rate of other AI tasks. Support bots need five types of context most teams never provide. The model isn't the problem.
Why Product Management AI Gives Wrong Priorities
84% of product teams doubt their products will succeed despite AI adoption. The problem: PM tools see feature requests but not the context behind what to build.
Why Sales AI Fails Without Deal Context
87% of enterprises missed revenue targets despite AI investment. Sales AI needs five types of deal context most teams never provide. The model isn't the issue.
7 context engineering techniques for production
Seven context engineering techniques used in production AI systems, with implementation patterns, research backing, and guidance on when each one works.
Structured Context vs Raw Text for AI
ETH Zurich found AI-generated context files hurt agent performance by 3%. Format choice alone swings LLM accuracy by 40%. Here's what the research says.
Put context into practice
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