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Droptops/README.md

Manny Villegas

Enterprise sales operator building open-source tooling around AI agents, authority, evaluation, and infrastructure economics.

Building in public

  • FAAR Runtime — authority and execution controls for tool-using agents, with explicit fail-closed boundaries around high-consequence actions.
  • Agent Honesty Harness — mechanical evaluation of whether an agent's claims match what its tools actually did.
  • Constraint Enumeration Eval — research and evaluation work on authority routing, work primitives, and agent failure modes.
  • Token Yield — analytical model for API-vs-self-hosted inference economics and local AI ownership.
  • CCA Prep — interactive study resource for the Claude Certified Architect Foundations exam.

Background

Enterprise sales and financial-services experience spanning communications infrastructure, fintech, private banking, and business development. Interested in the intersection of agent systems, infrastructure economics, and real-world deployment constraints.

Connect

LinkedIn

Popular repositories Loading

  1. agent-honesty-harness agent-honesty-harness Public

    Mechanically scores whether an AI agent's final claim matches what its tools actually did. Pre-registered, calibrated, adversarially reviewed.

    Python 1

  2. pcf pcf Public

    Portable Context Format: cache-aware prompt compilation for OpenAI and Anthropic

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  3. cca-prep cca-prep Public

    Interactive prep course for the Claude Certified Architect – Foundations exam. Single-file React app, progress tracking, all 5 domains.

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  4. Droptops Droptops Public

  5. constraint-enumeration-eval constraint-enumeration-eval Public

    Constraint-enumeration prompting skill + HOB-pattern eval. Tests whether forcing explicit conjunction-checking improves LLM accuracy on multi-constraint real-world decision tasks.

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  6. openai-cookbook openai-cookbook Public

    Forked from openai/openai-cookbook

    Examples and guides for using the OpenAI API

    Jupyter Notebook