https://neatguycoding.com/tags/weaviate-podcast/Recent content in Weaviate-Podcast on Neat Guy CodingHugo -- gohugo.ioen© 2026 NeatGuyCodingMon, 18 May 2026 00:00:00 +0000https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-patronus-ai-with-anand-kannappan-weaviate-podcast-122/Mon, 18 May 2026 00:00:00 +0000https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-patronus-ai-with-anand-kannappan-weaviate-podcast-122/Agent oversight stack: from static evaluation to trajectory-level observability—evaluation, observability, and supervision for multi-agent systems, with Percival, Lynx, and Glider, and evidence boundaries called out.https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-agentic-rag-with-erika-cardenas-weaviate-podcast-109/Mon, 18 May 2026 00:00:00 +0000https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-agentic-rag-with-erika-cardenas-weaviate-podcast-109/Agentic RAG: When retrieval pipelines add LLM plan–act–observe loops, tool calling, and multi-step validation—separating verified docs from interview speculation for production teams.https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-agentic-topic-modeling-with-maarten-grootendorst-weaviate-podcast-126/Mon, 18 May 2026 00:00:00 +0000https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-agentic-topic-modeling-with-maarten-grootendorst-weaviate-podcast-126/Agentic topic modeling: modular embedding pipelines, LLM-maintained topic tables, and human-in-the-loop granularity—engineering trade-offs between BERTopic, TopicGPT, and retrieval-scale deployment.https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-optimizing-retrieval-agents-with-shirley-wu-weaviate-podcast-115/Mon, 18 May 2026 00:00:00 +0000https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-optimizing-retrieval-agents-with-shirley-wu-weaviate-podcast-115/Stanford’s STaRK benchmark and AvaTaR contrastive optimization for retrieval agents on semi-structured knowledge bases—metrics, multi-vector limits, when agents lose to dense retrievers, and what to ship in production.https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-doug-turnbull-and-trey-grainger-on-ai-powered-search-weaviate-podcast-13/Mon, 18 May 2026 00:00:00 +0000https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-doug-turnbull-and-trey-grainger-on-ai-powered-search-weaviate-podcast-13/AI-Powered Search: When RAG, agents, and classic IR get rewired—retrieval quality vs. agent loops, long context vs. searchable history, leaderboard embeddings vs. domain corpora, with Doug Turnbull and Trey Grainger on what ships.https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-cartesia-ai-with-karan-goel-weaviate-podcast-113/Mon, 18 May 2026 00:00:00 +0000https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-cartesia-ai-with-karan-goel-weaviate-podcast-113/Architectural tension in the voice-agent era: SSMs, low-latency TTS, and whether end-to-end models will displace compound orchestration chains.https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-compound-ai-systems-with-philip-kiely-weaviate-podcast-105/Mon, 18 May 2026 00:00:00 +0000https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-compound-ai-systems-with-philip-kiely-weaviate-podcast-105/Compound AI: When a single LLM call is not enough—multiple model calls, retrievers, tools, and business logic as a graph; structured output, specialist pipelines, inference stacks, and deployment granularity from a Weaviate podcast with Baseten’s Philip Kiely.https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-data-agents-with-shreya-shankar-weaviate-podcast-135/Mon, 18 May 2026 00:00:00 +0000https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-data-agents-with-shreya-shankar-weaviate-podcast-135/Data agents across Snowflake, MySQL, Mongo, and Salesforce—DAB benchmarks, DocETL, tribal knowledge, and agent-first databases, with verifiable claims separated from speaker opinion.https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-arctic-embed-with-luke-merrick-puxuan-yu-and-charles-pierse-weaviate-pod/Mon, 18 May 2026 00:00:00 +0000https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-arctic-embed-with-luke-merrick-puxuan-yu-and-charles-pierse-weaviate-pod/Engineering trade-offs in retrieval embeddings: how to read leaderboards, what contrastive pre-training and fine-tuning each solve, how Matryoshka representation learning scales to billion-vector indexes, and the gap between multilingual benchmarks and proprietary distributions—grounded in Snowflake Arctic Embed and the Weaviate podcast.https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-box-ai-with-ben-kus-and-bob-van-luijt-weaviate-podcast-120/Mon, 18 May 2026 00:00:00 +0000https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-box-ai-with-ben-kus-and-bob-van-luijt-weaviate-podcast-120/Enterprise AI on exabyte-scale unstructured content: permissions, layered retrieval, and agent boundaries—engineering lessons from Box × Weaviate on ACL-aware RAG, embedding economics, and production agents.https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-contextual-ai-with-amanpreet-singh-weaviate-podcast-114/Mon, 18 May 2026 00:00:00 +0000https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-contextual-ai-with-amanpreet-singh-weaviate-podcast-114/Enterprise RAG and agents: from stitched-together pipelines to an end-to-end optimizable system—RAG 2.0, active retrieval, preference learning (KTO/APO), and LMUnit-style evaluation, with evidence boundaries called out.https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-saurabh-mishra-and-bob-van-luijt-on-weaviate-and-sas-weaviate-podcast-12/Mon, 18 May 2026 00:00:00 +0000https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-saurabh-mishra-and-bob-van-luijt-on-weaviate-and-sas-weaviate-podcast-12/Enterprise RAG and agents when vector databases meet four decades of analytics software—engineering tensions in regulated industries, SAS RAM, Weaviate integration, and production boundaries.https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-morningstar-intelligence-engine-with-aravind-kesiraju-weaviate-podcast-1/Mon, 18 May 2026 00:00:00 +0000https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-morningstar-intelligence-engine-with-aravind-kesiraju-weaviate-podcast-1/Enterprise RAG on financial research corpora: engineering trade-offs across vector stores, agents, and eval—ingestion throughput, retrieval granularity, entitlements, and agent latency.https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-search-agents-with-nandan-thakur-weaviate-podcast-137/Mon, 18 May 2026 00:00:00 +0000https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-search-agents-with-nandan-thakur-weaviate-podcast-137/From RAG to search agents: BEIR co-author Nandan Thakur on BrowseComp-Plus, synthetic data pipelines, GRPO economics, and why retrieval benchmarks, training cost, and harness design pull in different directions.https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-haize-labs-with-leonard-tang-weaviate-podcast-121/Mon, 18 May 2026 00:00:00 +0000https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-haize-labs-with-leonard-tang-weaviate-podcast-121/Judge-time compute: stacking structured, composable weak-model calls at evaluation time instead of assuming one expensive judge pass is enough—Verdict, agreement metrics, and production guardrails, with evidence boundaries called out.https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-mipro-and-dspy-with-krista-opsahl-ong-weaviate-podcast-103/Mon, 18 May 2026 00:00:00 +0000https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-mipro-and-dspy-with-krista-opsahl-ong-weaviate-podcast-103/Multi-stage language programs and automatic prompt optimization: from DSPy to MIPRO—proposal, bootstrapping, and combinatorial search; credit assignment; meta-proposers; and how they relate to RAG, agents, and fine-tuning.https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-multi-vector-search-with-ame-lie-chatelain-and-antoine-chaffin-weaviate/Mon, 18 May 2026 00:00:00 +0000https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-multi-vector-search-with-ame-lie-chatelain-and-antoine-chaffin-weaviate/Multi-vector search: how to choose among single-vector bi-encoders, late interaction (ColBERT-family), and cascaded reranking—grounded in the Weaviate podcast with LightOn’s Amélie Chatelain and Antoine Chaffin.https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-weaviate-s-query-agent-with-charles-pierse-weaviate-podcast-128/Mon, 18 May 2026 00:00:00 +0000https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-weaviate-s-query-agent-with-charles-pierse-weaviate-podcast-128/Query Agent on a vector database: auditable retrieval, Ask vs Search modes, schema introspection, multi-collection routing, and what is verified in docs versus speaker claims.https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-refrag-with-xiaoqiang-lin-weaviate-podcast-130/Mon, 18 May 2026 00:00:00 +0000https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-refrag-with-xiaoqiang-lin-weaviate-podcast-130/REFRAG compresses retrieved passages into chunk-level decoder positions, then uses RL to selectively expand high-entropy spans—mechanisms, training pipeline, and how to read TTFT and RAG benchmarks without over-generalizing paper numbers.https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-pyversity-with-thomas-van-dongen-weaviate-podcast-132/Mon, 18 May 2026 00:00:00 +0000https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-pyversity-with-thomas-van-dongen-weaviate-podcast-132/Retrieval list diversification: geometric post-processing, evaluation gaps, and RAG context budgets—MMR, MSD, DPP, Cover, and SSD as NumPy reranking after any Python retrieval stack.https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-scaling-pandas-with-devin-petersohn-weaviate-podcast-101/Mon, 18 May 2026 00:00:00 +0000https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-scaling-pandas-with-devin-petersohn-weaviate-podcast-101/Scaling DataFrames: when notebook habits meet distributed execution—pandas semantics, Modin’s compiler stack, Snowflake ordering, Parquet pushdown, quote-aware CSV, Ray data movement, and what is verified vs. speaker opinion.https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-semantic-query-engines-with-matthew-russo-weaviate-podcast-131/Mon, 18 May 2026 00:00:00 +0000https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-semantic-query-engines-with-matthew-russo-weaviate-podcast-131/Semantic query engines treat foundation-model filter, join, classify, map, and rank as first-class operators—logical and physical plans, cost–quality tradeoffs, SemBench workloads, and how they differ from script-style RAG and vector search alone.https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-swe-bench-with-john-yang-and-carlos-e-jimenez-weaviate-podcast-107/Mon, 18 May 2026 00:00:00 +0000https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-swe-bench-with-john-yang-and-carlos-e-jimenez-weaviate-podcast-107/Software engineering agents on real repositories: SWE-Bench benchmarks GitHub issue → patch → tests green, while SWE-agent pushes the debate onto Agent-Computer Interface design—separating verified docs from speaker opinion.https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-letta-ai-with-sarah-wooders-weaviate-podcast-117/Mon, 18 May 2026 00:00:00 +0000https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-letta-ai-with-sarah-wooders-weaviate-podcast-117/Stateful agents and context compilation: how Letta (from MemGPT) treats the context window as a compiled runtime view—memory tiers, agentic RAG, tool-call unification, multi-agent blocks, and observability—with evidence boundaries called out.https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-structured-outputs-with-will-kurt-and-cameron-pfiffer-weaviate-podcast-1/Mon, 18 May 2026 00:00:00 +0000https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-structured-outputs-with-will-kurt-and-cameron-pfiffer-weaviate-podcast-1/Structured outputs: from parseable JSON to logit-level constrained generation—why RAG pipelines and agents need generation-time constraints, how FSMs and coalescence work, and how to choose between API guarantees and self-hosted logits masking.https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-sufficient-context-with-hailey-joren-weaviate-podcast-125/Mon, 18 May 2026 00:00:00 +0000https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-sufficient-context-with-hailey-joren-weaviate-podcast-125/Sufficient context asks whether retrieved chunks let a model answer the question—not just whether they look relevant. A Weaviate Podcast #125 walkthrough of Joren et al. (ICLR 2025) on RAG evaluation, abstention, and selective generation.https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-synthetic-data-with-david-berenstein-and-ben-burtenshaw-weaviate-podcast/Mon, 18 May 2026 00:00:00 +0000https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-synthetic-data-with-david-berenstein-and-ben-burtenshaw-weaviate-podcast/Synthetic data for RAG, agents, and offline evaluation—when to augment, how to trust the distribution, and pipelines from distilabel and Persona Hub to Hub SQL and quality filters.https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-vertex-ai-rag-engine-with-lewis-liu-and-bob-van-luijt-weaviate-podcast-1/Mon, 18 May 2026 00:00:00 +0000https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-vertex-ai-rag-engine-with-lewis-liu-and-bob-van-luijt-weaviate-podcast-1/The boundaries of enterprise RAG: managed pipelines, vector stores, and write-back retrieval—engineering lessons from Vertex AI RAG Engine × Weaviate on parsing leverage, multi-corpus routing, and generative feedback loops.https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-muvera-with-rajesh-jayaram-and-roberto-esposito-weaviate-podcast-123/Mon, 18 May 2026 00:00:00 +0000https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-muvera-with-rajesh-jayaram-and-roberto-esposito-weaviate-podcast-123/Models like ColBERT and ColPali represent documents as token-level vector sets and pay for finer alignment with late interaction (MaxSim/Chamfer)—but index entries explode from one per document to hundreds. Google Research’s MUVERA compresses each set into a single fixed-dimensional encoding for one ANN pass, then reranks with true Chamfer; this article separates paper facts from podcast opinion for engineers shipping multi-vector search.https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-let-me-speak-freely-with-zhi-rui-tam-weaviate-podcast-108/Mon, 18 May 2026 00:00:00 +0000https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-let-me-speak-freely-with-zhi-rui-tam-weaviate-podcast-108/When format constraints hurt LLMs: the same structured-output techniques often lower scores on reasoning tasks and raise them on discrete classification—from agent pipelines to benchmark evaluation.https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-rag-benchmarks-with-nandan-thakur-weaviate-podcast-124/Mon, 18 May 2026 00:00:00 +0000https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-rag-benchmarks-with-nandan-thakur-weaviate-podcast-124/Production RAG no longer matches short-query IR leaderboards—BEIR co-author Nandan Thakur on why search benchmarks and long-context, nugget-level RAG evaluation are diverging axes.https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-gepa-with-lakshya-a-agrawal-weaviate-podcast-127/Mon, 18 May 2026 00:00:00 +0000https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-gepa-with-lakshya-a-agrawal-weaviate-podcast-127/When scalar reward isn’t enough: GEPA’s reflective prompt evolution and per-instance Pareto retention for compound AI language programs—natural-language feedback, LangProBe benchmarks, and how it compares to GRPO and MIPROv2.