KNOWLEDGE & ENGINEERING HUB

AI workforce guides, architectures, and benchmarks.

Explore research and implementation standards for deploying autonomous AI agents with deterministic evaluation and Model Context Protocol (MCP).

Featured Standard /llms.txt compatible

The 2026 Agent-Readable Web Architecture Specification

How to design web applications, navigation trees, and content models that are simultaneously engaging for human users and structurally understandable for autonomous AI agents.

📄 View Raw /llms.txt Spec → Model Context Protocol Guide

Architecture Standard 7 min read

The 2026 Agent-Readable Web Architecture Guide

How to design web applications and APIs that are equally intuitive for human visitors and autonomous AI agents through semantic HTML, JSON-LD, and llms.txt.

Key Takeaways

● Why dual-layer Human + Agent web design is the defining pattern of 2026
● Structuring machine-readable product metadata without bloating client bundles
● Using Model Context Protocol (MCP) as the universal tool connector
● Designing agent-actionable UI with explicit semantic triggers

By Antigravity Research Team

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Engineering Guide 9 min read

Deterministic Evaluation for Autonomous AI Fleets

A practical framework for benchmarking AI employees with golden datasets, semantic diffing, and automated LLM judge scoring before pushing to production.

Key Takeaways

● Building robust golden test suites for multi-step agent trajectories
● Quantifying tool-calling precision vs hallucination rates
● Integrating agent evaluation into GitHub Actions CI/CD pipelines
● Setting up automated rollback triggers on quality score degradation

By Elena Rostova

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Governance & Security 6 min read

Human-in-the-Loop Governance: Balancing Autonomy and Safety

Designing approval workflows, risk classification tiers, and audit trails so your enterprise can deploy autonomous agents with absolute peace of mind.

Key Takeaways

● Categorizing agent actions into Read-Only, Draft, and Write tiers
● Designing frictionless Slack and Dashboard 1-click approval cards
● Maintaining immutable cryptographic audit logs for compliance
● Handling agent timeout and escalation policies gracefully

By Marcus Vance

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Case Study 5 min read

How Rampify Scaled Outbound Pipeline by 3.8x with AI SDR Employees

Learn how a high-growth fintech company automated 12,000+ monthly prospecting workflows while increasing AE demo conversion rates by 42%.

Key Takeaways

● Challenge: AEs bogged down by 15 hours/week of manual research and CRM data entry
● Solution: Deployed OllaSuper Sales and Research Employees integrated with Salesforce
● Outcome: 3.8x outbound pipeline growth, $3.4M new ARR in first 6 months

By OllaSuper Customer Success

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Developer Reference 12 min read

Connecting Custom Enterprise Tools via Model Context Protocol (MCP)

Complete technical reference for implementing, securing, and testing custom MCP tool servers for your OllaSuper AI employee fleet.

Key Takeaways

● Understanding the MCP Server/Client JSON-RPC 2.0 lifecycle
● Implementing tool schemas, resources, and prompt templates
● Securing internal endpoints with mTLS and ephemeral capability tokens
● Local testing with the OllaSuper MCP inspector CLI

By OllaSuper Platform Core

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