What works, what doesn't, and what it actually feels like when you carry both customer accountability and real agent infrastructure.
A personal agent that reaches the CRM through one shared account shows a rep every region's pipeline and leaves no record of whose question it was. Per-person token exchange fixes both, and shows a gap in agent identity.
What logprobs and Decisions scores mean, how they can route answers to human review, and what a 64-call classification test found.
Parallel sells web search, typed decisions, research, discovery, and monitoring to AI agents through APIs, MCP servers, a CLI, and agent-harness plugins.
A 660-case OWASP Benchmark Java test at maximum reasoning effort across four models on Amazon Bedrock, with accuracy, missed flaws, false alarms, token use, and cost per correct answer.
Executives are asking how autonomous their AI should become before defining the outcome, workflow, authority, evidence, and recovery model. Autonomy belongs to workflows, not enterprises.
A tested OpenCode configuration for running Claude, OpenAI GPT, xAI Grok, and Moonshot Kimi through their native Amazon Bedrock Runtime APIs.
TypeSafe's Jev returns a typed answer and a probability, not a paragraph. That is worth putting first on a clean enum, and worth nothing on a dirty one.
The sticker price on a model card is not what you pay. Measuring cache-hit ratios from months of real usage across Sonnet 5, Opus 5, and GPT-5.6 puts the effective cost per million tokens 70-95% below list price.
HTTP success proves transport. A credible agent-search evaluation separately tests the contract, evidence, tool calls, lifecycle cleanup, and cost.
Agent search works as a five-stage pipeline: discovery, extraction, verification, synthesis, and monitoring. Treating it as one tool hides the failures that matter.