· LLM Workbench
Why our demo runs the One Ring and a DeLorean
A demo should show the shape of a real agent run, not a toy. So ours runs beloved-story logistics—Gandalf's routing, a flux-capacitor power calc—on top of the actual engine.
Topic
run bundles
7 articles on run bundles from the LLM Workbench blog.
· LLM Workbench
Anatomy of a run bundle
The run bundle is the unit LLM Workbench is built around. Here's what's inside one—and why each part earns its place.
· LLM Workbench
Replay rights: a moonshot for universal, contestable AI decisions
What if every person had a universal right to replay the AI decision that affected them—loan, hire, claim, refund? Here is the moonshot: tamper-evident run bundles as the substrate for adjudicable cognition.
· LLM Workbench
Agent contracts: the missing layer between AI agents and the humans accountable for them
A recovering lawyer's case for a machine-readable contractual layer between AI agents and their human controllers—scope, consent, revocation, restitution—encoded as gates and run bundles.
· LLM Workbench
Agent economics in the enterprise: observable routing, visible work, and governance that survives audits
A unified operating view for AI leaders—token-aware routing, context discipline, and tamper-evident run bundles as the control plane for trustworthy scale.
· LLM Workbench
What LLM Workbench solves in production LLM stacks
From opaque prompts to replayable bundles: gates, traced model I/O, artifacts, integrity—and surfaces both humans and tools can consume.
· LLM Workbench
Why LLM Workbench exists
A reference plane for deployed agents—not only faster models, but runs you can replay, approve, audit, and hand to another engineer without folklore.