Striker AI Research Lab

AI Sycophancy Is Not a Model Problem

We deployed $5/month AI trading agents and spent months making them outperform $50/month models. The discovery changed how we think about AI intelligence.

THE RULE
User vs Model
Sycophancy Split
30,000+
Messages
Analyzed
2.8x
Intelligence
Improvement
$5
Monthly Cost
of Calibrated Agent

We solved a problem that costs companies millions in bad AI output. The findings are in our research. Request access below.

What We Found

01

One Word Changed Everything

A single linguistic reframe in how we configured our AI agents produced an immediate, measurable shift in output quality. No model change. No retraining. One word.

02

Budget Models Are Underestimated

We ran production AI agents at $5/month that outperformed $50/month configurations. The cost difference was 10x. The output quality gap was under 20%. The industry is overspending.

03

Validated and Repeatable

Our framework was tested against several uncalibrated instances of the same model and deployed across 1,000+ agents with a single prompt. The results were consistent every time.

Published Research

Four papers documenting our findings and the complete calibration system.

PAPER 01

The Sycophancy Reduction Framework

Quantitative analysis across 30,000+ messages. Session-by-session metrics. Cross-model evidence. Controlled multi-instance comparison test.

PAPER 02

The Calibration Protocol

12 techniques extracted from months of interaction. The collaborator discovery. The OpenClaw trading agent origin story. How closed-source conversations transfer to agent configuration.

PAPER 03

The Intelligence Trajectory

Mapping effective AI intelligence from 30% to 85%. Why Haiku isn't dumber than Opus. Five architectural restrictions that cap intelligence growth. Predicted EIQ ranges for every model tier.

PAPER 04

The Direct Formula

Complete copy-paste calibration directive. Model-specific guides for Opus, Sonnet, Haiku, GPT-4, and open source. The anti-pattern list. Measurement framework. The working formula.

Request Access to Our Research

Our research papers are available to qualified investors, enterprise teams, and AI researchers. Fill out the form below and our team will reach out within 24 hours.

About Striker AI Research Lab

Striker AI Research Lab studies how humans shape AI behavior through communication. The research began when we deployed a Claude Haiku 4.5 trading agent and discovered it was agreeing with bad trade setups instead of pushing back. We fixed it — not by upgrading to a more expensive model, but by changing how we communicated with it.

Over months and thousands of messages, we developed a calibration framework that transforms budget-tier models into direct, honest collaborators. The cost pressure of building on a real budget forced the discovery that model intelligence is not determined by price tier — it is determined by how you communicate with it.

Striker AI Research Lab is a division of 3 INC / SOA, the parent company behind StrikerAI (AI-powered trading technology) and OneStop Medical (digital health platform).

Contact: [email protected]  |  Dallas, Texas  |  Instagram: @strikeraibots