Skip to main content

Documentation Index

Fetch the complete documentation index at: https://lab.pollack.ai/llms.txt

Use this file to discover all available pages before exploring further.

Pollack AI Lab
Agent Infrastructure · Experiments
Helping you build agents that demonstrably work. A growing ecosystem of projects — usable together or individually — for composing, evaluating, and understanding agent behavior. Experiments that prove the approach works, with published data and reproducible results. By Mark Pollack, creator of Spring AI.

Core Projects

Agent Workflow

Multi-step agentic pipelines with typed context, quality gates, and portable runtimes

Agent Judge

Evaluation with deterministic, command, and LLM judges

Loopy

Interactive coding agent CLI for Java developers

Agent Client

Claude, Gemini, Codex, Amazon Q as unified Spring services

Agent Journal

Behavioral trace capture for analysis and observability

Agent Bench

Benchmarking on real enterprise Java tasks

Latest Experiments

Code Coverage v2 — Skills vs Knowledge Bases
Do structured skills outperform flat file injection? 7 variants, N=3
Mar 2026 · In Progress · Details →
Code Coverage v1 — Knowledge Injection Baseline
9 variants testing progressive knowledge injection on Spring Boot test generation
Feb 2026 · Complete · Details →