# SignalSDR: Autonomous Sales-Signal Agent

> A sales-development agent that finds buying signals and drafts the outreach, daily.

**Status:** Proof of concept

## Problem

SDRs manually check careers pages and news for each target: slow, inconsistent, and easy to miss the moment.

## What it does

An automated sales-intelligence agent that monitors a set of target accounts every day for two kinds of buying signal: hiring signals (scraping careers pages for roles that indicate demand for our services) and prospect intelligence (scanning business news via the Brave Search API across categories like product launches, electrification, regulatory events, and AI/ML adoption). For each signal it generates a personalized cold-outreach email draft with an LLM, tied to specific products, with false-positive filtering built into the prompts, then delivers a daily digest for human review before anything is sent. All signal-detection, prospecting, drafting, and state logic is custom, built on the open-source nanobot agent framework; it runs unattended on a daily schedule.

## Measured results

- **25 accounts** monitored daily — Across hiring plus four prospect-signal categories.
- **~10 min** full daily pipeline — Human reviews the drafts before any outreach is sent.

## Stack

Python, nanobot (agent framework), Brave Search API, LLM drafting (litellm), BeautifulSoup, launchd scheduling

## Topics

AI, Agents, LLM

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Part of the proof-of-work portfolio of Michael Wahl — VP, Software Engineering & AI Enablement.

- Canonical project page: https://connect.michaelwahl.org/project/signalsdr
- Full professional profile: https://connect.michaelwahl.org/
- Machine-readable context: https://connect.michaelwahl.org/llms.txt