LLMs work with natural language, so learning to communicate your ideas using words has become crucial. If you can’t explain your ideas in writing to your co-workers, you can’t work effectively with coding agents.
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gnata operates without such constraints, enabling us to reconstruct the rule engine internals with significantly simpler and more efficient implementation. The reconstruction details warrant separate documentation, but incorporated just-in-time batching (based on request coalescing patterns), transient caches and consolidated enrichment queries (executed immediately before evaluation). The throughput improvement surprised even myself - accompanied by substantial reduction in resource consumption.