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IluvatarThePious/README.md

Enterprise Sales · Practical AI Workflows · Evidence-Based GTM

Peter Ryther · AI Operator || Philomath || GTM Hunter || Technophile · New York, NY || Naples, FL

LinkedIn salesrobots.com Email


What I Build

I turn enterprise-sales problems into inspectable AI-assisted workflows: customer follow-ups, pilot plans, value models, and account preparation.

My background spans enterprise sales at Orum, Outreach and Ironclad. This portfolio shows how I connect commercial judgment with practical AI tools—making sources, assumptions and human review visible.

I'm interested in Enterprise and Strategic Account Executive opportunities at growing AI and robotics companies. Explore a five-minute work sample or connect on LinkedIn.


Featured GTM & AI Work Samples

Try the GTM Evidence Toolkit →

Three workflows: Call to Commitment, Value Case Lab, and Career Evidence Companion. Start with a fictional call and its reviewed follow-up, or run the transparent Python calculator. Includes evaluation cases and seven calculator tests; live AI-output benchmarking is still planned.

Explore the enterprise GTM & AI workflow portfolio →

Three inspectable examples: a fictional customer-proof story with a source ledger and calculation checks; a pilot-to-expansion playbook; and a reproducible Python service scenario model with six tests. These AI-assisted work samples distinguish evidence, assumptions, and simulated results. They are not presented as customer deployments or measured commercial outcomes.


Current Projects

Project What It Is
salesrobots-gtm Full go-to-market plan: ICP, pricing, outreach sequences, 60-day launch roadmap
cold-email-deliverability-playbook SPF/DKIM/DMARC setup, 21-day warmup schedule, domain health monitoring protocol
ai-outbound-stack The full Apollo → Clay → Instantly → Inbox system, documented and diagrammed
launch-command-center Interactive sprint tracker dashboard — built with vanilla JS, deployed on Vercel

Tool Stack

Apollo Clay Instantly Vercel GitHub Python Make Calendly Perplexity


How I Work

  • Start with a real decision — define the user, the problem and what a useful output must help them do.
  • Make evidence inspectable — separate source facts, assumptions, proposals and measured outcomes.
  • Build with AI, review with judgment — use AI for implementation and drafting, then check calculations, claims and usability.

GitHub Stats

Peter's GitHub Stats

GitHub Streak


Domain Portfolio

I hold ~50 AI-era domains including futurebrain.io, worldmachines.io, vcworld.ai, and others at the intersection of AI, finance, and the next decade of software. Building selectively — salesrobots.com is first.


Working on enterprise sales, value engineering, or practical AI adoption?

Explore the toolkit and share feedback →

Pinned Loading

  1. enterprise-gtm-ai-portfolio enterprise-gtm-ai-portfolio Public

    Enterprise GTM and AI-assisted work samples: customer proof, pilot-to-expansion strategy, and reproducible service scenario modeling.

    Python

  2. gtm-evidence-toolkit gtm-evidence-toolkit Public

    Practical AI workflows for enterprise sellers: source-grounded follow-ups, transparent value modeling, and career evidence. Fictional examples, prompts, and tested Python calculations.

    Python