236 articles
· 13 read
GraphRAG's indexing bill is real, and the 2026 benchmarks are mixed. Here's the decision table for when a knowledge graph beats vector RAG, and when it just costs more.
· 12 read
MIT NANDA found 95% of generative-AI projects return zero measurable value. This working calculator, ROI formula, and 12-month worked example show how to measure AI integration ROI, find your payback month, and prove the gain to a CFO.
· 14 read
Two of these three are LLM observability tools; MLflow is a 2018 ML platform that grew tracing, and that lineage decides most of these evaluations. Vendor pricing re-read in August 2026 at 100K, 1M and 10M traces, plus a named pick per team profile.
· 16 read
We read the license file and default-branch commit log of eight open-source LLM evaluation frameworks on 2026-08-04, then installed six and ran the same 10 cases through each. One ships under a license the OSI doesn't approve, two haven't shipped a release since 2024, and two relevance metrics scored a confident lie above a correct answer.
· 10 read
Sonar acquired Gitar on May 21, 2026. This review covers what Gitar's CI-validated autofix actually does, the $20 and $40 tiers, where it beats CodeRabbit and Greptile, and the honest reasons to skip it.
· 14 read
Your agent picks the wrong tool because the failure lives in four specific places: selection, arguments, loops, and response size. This guide diagnoses each failure mode first, then maps eight agent tool calling best practices to them, with code, schemas, and an eval loop you can run on every change.
· 14 read
RAG retrieves facts at query time; fine-tuning bakes knowledge into model weights. A 162-citation arXiv study ran both on the same task, and the winner surprises most teams. Here's the decision framework with real cost math on public list prices.
· 14 read
A chatbot can pass every single-turn test and still ask the user for information they gave three turns ago. This guide covers the 5 multi-turn metrics that catch conversational failures, how DeepEval, RAGAS, and Langfuse differ, and the 6-step workflow to gate regressions in CI.
· 14 read
Nine LLM logging best practices from a team running this in production: structured JSON records with 14 named fields, PII redaction before the write, OpenTelemetry GenAI traces, and per-request cost tracking. Includes the Python code, the storage-cost math at 1M requests a day, and the tool comparison.
· 10 read
Offline evals gate your deploys; online evals watch what ships. A 9-dimension comparison, a real CI gate config, a tool-to-mode matrix, and the feedback loop that turns production failures into regression tests.
· 13 read
LLM inference cost ranges from $0.02 to $75 per million tokens depending on model tier. We built 4 workload cost models from July 2026 pricing so you can estimate your monthly bill before committing to a provider.
· 15 read
A tool is a contract between your deterministic code and a non-deterministic model. Seven design principles, the build-vs-buy call, MCP serving, tool-level security, and the eval loop that proves your agent tools work.
