Most enterprise agent projects don't stall because the models aren't smart enough. They stall because the software around them was built for deterministic code: static service accounts, no limits on spend, tests that pass while an agent quietly gets the business logic wrong.
Executing Dynamic Autonomy is the blueprint we wish we'd had. It follows one case study from a brittle legacy estate to governed, observable agents, and covers:
- Architecture and orchestration: design patterns for teams of agents, and how they share state and memory across sessions.
- Knowledge: a two-layer pipeline with graph retrieval, kept current from your systems.
- The tool gateway: one switchboard between agents and every system they touch.
- Identity: agents that act on behalf of a person and never beyond that person's rights.
- Cost, speed and scale: latency, concurrency and budget limits that stop runaway spend.
- Testing and observability: a development lifecycle built for probabilistic software, and traces that explain what an agent did and why.
- Security: adversarial testing and guardrails.
It's written for systems architects, CTOs, heads of engineering and platform engineers who have to run agents against real systems of record and answer for what they do.
Download the free book (PDF, 117 pages, in English).