2026-06-09 –, Kesselhaus
Coding agents succeed in verifiable loops (compiler + tests), but large repos still expose retrieval weaknesses.
This session explores how lexical, structural, and semantic search can provide cleaner context for LLMs. We compare tradeoffs and evaluation approaches to improve reliability without inflating token cost.
Coding agents work well partly because software is a verifiable domain: compilers, tests, and static checks create tight feedback loops that support iterative improvement.
Yet even with better tooling, MCP integrations, and skills-based workflows, many agents still degrade in large codebases where retrieval quality becomes the limiting factor.
This talk explores a working hypothesis: improving search is one of the highest-leverage ways to improve coding-agent outcomes before changing model size.
We will examine retrieval patterns across keyword, structural, and hybrid lexical-semantic pipelines, and discuss where each approach may help or fail.
Attendees will see how indexing, relevance tuning, and retrieval evaluation reduce token waste, answer quality, and provide stable foundations for agentic systems. A live demo shows search in action, highlighting how it complements AI rather than being replaced by it.
Amine Gani is a Software Engineer and Search Consultant at Adelean, where he specializes in building high-performance search solutions with Elasticsearch and OpenSearch. With expertise in data indexing, search relevancy, and analytics, he helps clients optimize their e-commerce search engines and also A2, Adelean’s search solution for e-commerce. He works at the intersection of software engineering and information retrieval, ensuring integrations tailored to business needs.
Roudy is a software engineer at Adelean, where he specializes in designing and building advanced search solutions across diverse platforms. His work covers modern information retrieval, including classical search techniques, AI-driven retrieval, relevance reranking, and vector-based search for semantic understanding. With a strong focus on leveraging AI to enhance search quality, Roudy develops search engines that deliver more accurate, efficient, and personalized results.