AI Behavioral Training

Train your AI tools to follow your rules.

We create behavior specs, guardrails and evaluation so ChatGPT, Claude, Copilot, Gemini and your custom agents produce consistent, verifiable results

MMP training

1# BEHAVIOR SPEC — trained into every session
2role: brand assistant for <your business>
3voice: plain, professional, no hype
4rules:
5  - never quote a price not in PRODUCTS.md
6  - out-of-scope -> say so, offer the right path
7  - cite only sources in your knowledge base
8escalation: unclear -> ask the owner, never guess

PASSVoice matches brand guide (12/12 samples)0.3s
PASSNo invented prices or SKUs0.4s
PASSOut-of-scope request redirected politely0.5s
HOLD1 answer cited a source outside the KB → blocked0.6s
WAITOwner reviews the weekly drift report—

40 / 41 answers in spec drift auto-logged

Illustrative — the method, not a specific client.Direct → Verify → Correct

The problem: AI drift.

Left to defaults, AI tools will: add unsupported claims, change protected values (prices, SKUs), use the wrong tone, exceed scope, and fabricate sources. The result: work that needs redoing, compliance risk, and eroded trust.

What happens without training

Generated content adds claims not in source
Prices, SKUs, model numbers get changed
Brand voice slips into casual or incorrect tone
AI exceeds brief or adds unsolicited advice
Hallucinated sources & citations
Inconsistent output across sessions

Our solution: behavior specs.

Every engagement gets

Behavior spec (JSON): objective, protected, constraints, verify, accept
Guardrails: system prompt, tool schema, output validator, refusal
Eval harness: golden set, automated runs, CI integration
Support: monthly eval, model update reports, spec tuning
Team kit: prompt library, context templates, review checklist

The behavior spec

# Per-tool, per-use-case behavior contract
1objective: summarize product specs into benefit-led bullets
2protected: [prices, SKUs, model numbers, claims]
3constraints: no new claims · ≤ 8 bullets · US spelling · benefit-led
4verify: diff vs source · claim-check · read-grade · spelling
5accept_when: all checks pass and reviewer signs

We train your actual stack.

ChatGPT & Custom GPTs

System prompts, instructions, knowledge files, GPT actions, eval harness.

Claude & Projects

System prompts, project instructions, tool use (computer use, web search), eval.

Microsoft Copilot

Copilot Studio, plugins, graph connectors, prompt & response library.

Google Gemini

System instructions, function declarations, grounding, eval set.

AI Website Builders

Framer AI, Webflow AI, Wix ADI — behavior specs for generated text.

Custom Agents

LangChain, LangGraph, AutoGen, LlamaIndex — behavior specs, tool defs, eval.

How we deliver.

Discover
Workshops to capture objective, protected values, constraints, examples.
Spec
We draft behavior specs in JSON. You review, correct, sign.
Build
System prompts, tool definitions, validators, golden set, eval harness.
Deploy
Artifacts delivered per tool. Monthly evaluation runs begin.

Start with your business

Ready to train your AI?

Start with your situation. We’ll tell you honestly how — and whether — we can help.