BaselineResources
Guides and comparisons to help you evaluate, monitor, and improve your AI.
Guides
LLM evaluation your whole team can actually run
LLM evaluation is how teams check whether their AI is good enough to ship, and keep it that way. Baseline turns evaluation into rubrics, scheduled runs, and automated optimization, with no data-science team required.
ReadLLM-as-a-judge, made consistent and reviewable
LLM-as-a-judge uses one AI model to grade another's outputs at scale. Baseline makes that judgment consistent and readable, graded against a rubric your whole team agrees on instead of a black box.
ReadPrompt optimization without the guesswork
Prompt optimization means systematically finding prompts that score higher, instead of tweaking by hand and hoping. Baseline runs the search for you and proves the lift against your rubric.
ReadRubric-based evaluation: one definition of good
Rubric-based evaluation turns a fuzzy sense of "good output" into explicit, weighted criteria your whole team agrees on. Baseline makes the rubric the shared, reusable definition every eval and optimization runs against.
ReadReduce AI hallucinations before they reach customers
Hallucinations are confident, wrong answers. Baseline helps you measure how often your AI makes things up, catch new ones on a schedule, and drive the rate down with rubrics built for accuracy.
ReadAI agent testing that keeps up with a moving target
AI agents are hard to test because they act, not just answer. Baseline connects to your agent, scores its real outputs against a rubric, and re-runs the check on a schedule so regressions surface fast.
ReadSimple Mode: prompt optimization with fewer decisions
Simple Mode improves a pasted prompt by trying scored rewrites and keeping the best. Learn when to choose it over Reflective Mode, what every run option does, and how a run is billed.
ReadEval Points, explained
Eval Points are the unit Baseline's evaluation work is priced in. Learn the exact per-run arithmetic, what happens when a run fails, each plan's monthly allowance, and how overage stays under a cap you set.
ReadOptimize a prompt by hand, one honest round at a time
Manual prompt optimization means freezing a test set, scoring against fixed criteria, and running an AI assistant through one focused revision at a time. Get the full loop, the copy-paste prompt that runs it, and when it's worth automating with Baseline.
ReadComparisons
Baseline vs Braintrust
How Baseline and Braintrust compare for evaluating AI outputs: rubric-based scoring, scheduled eval runs, and automated prompt optimization. Verified, dated, and sourced.
CompareBaseline vs LangSmith
How Baseline and LangSmith compare for evaluating AI outputs: rubric-based scoring, scheduled eval runs, and automated prompt optimization. Verified, dated, and sourced.
CompareBaseline vs Humanloop
How Baseline and Humanloop compare for evaluating AI outputs: rubric-based scoring, scheduled eval runs, and automated prompt optimization. Verified, dated, and sourced.
CompareBaseline vs Langfuse
How Baseline and Langfuse compare for evaluating AI outputs: rubric-based scoring, scheduled eval runs, and automated prompt optimization. Verified, dated, and sourced.
CompareBaseline vs Arize AI
How Baseline and Arize AI compare for evaluating AI outputs: rubric-based scoring, scheduled eval runs, and automated prompt optimization. Verified, dated, and sourced.
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