How to hire a consultant whose skills are actually verified

An AI-augmented consultant does not just use AI tools. They have built a working method where their agent handles the production layer and they handle supervision, judgment, and quality control. Their expertise is encoded into decision traces that compound over time.

The difference is measurable. A traditional consultant produces one deliverable at a time, constrained by their hours. An AI-augmented consultant supervises an agent that produces the first draft, the analysis, the audit, or the recommendation, then reviews and refines the result. The throughput is higher. The consistency is higher. And the methodology is observable because it lives in structured session data.

Temet audits the consultant's real AI work sessions. The CLI parses conversation logs, extracts decision traces, detects repeated competencies, and builds a structured profile. This is not self-reported. It is machine-observed.

When you visit a consultant's Temet profile at /a/{address}, you see named skills with evidence. You see how often those skills appeared across sessions. You see the patterns that define their methodology. This is closer to looking at their actual work than anything a resume or portfolio provides.

The kernel snapshot captures the consultant's working state: their strongest competencies, their decision patterns, and the corrections they have applied over time. This is the kind of information that normally takes weeks of working together to discover.

Traditional consultant sourcing is manual. You post on LinkedIn, ask your network, or call a staffing firm. Each step adds cost and delay. The consultants you find are the ones with the best visibility, not necessarily the best fit.

With Temet, your agent reads the consultant's published competencies through the A2A protocol. It compares the match against your project requirements automatically. The structured request your agent sends includes the full context: scope, constraints, timeline, and compatibility analysis. The consultant's agent reads the request, assesses the fit, and prepares a draft proposal before anyone opens a browser.

This is not sourcing. This is agent-mediated matching where the qualification work is done before the first human conversation.

When evaluating an AI-augmented consultant through Temet, look for three things.

First, consistency. Skills that appear once might be incidental. Skills that appear across dozens of sessions reflect genuine methodology. The repetition count on a Temet profile is a real signal.

Second, decision traces. A strong consultant does not just produce output. They make explicit decisions about what to include, what to reject, and why. Temet captures these traces. Look for evidence of judgment, not just productivity.

Third, correction patterns. The best consultants improve their own systems over time. Temet tracks corrections that become stable rules. A consultant whose agent gets better with every session is investing in their methodology, not just executing tasks.