Custom AI Agents.
Built For Your Stack.
The retainer version of the open-source Origin — a 15-agent extension that produces my own pipeline. Same approach, configured for your business.
Six Agent Categories
Mix and match. Most engagements run 8–25 agents in parallel.
Content & Social Agents
Automated content repurposing pipelines. Turn one blog post into social threads, newsletters, and community posts — running continuously without manual work.
Lead Enrichment Bots
Enrich inbound leads with technographic data, GitHub activity, and Stack Overflow presence. Score and route leads to your sales team in real time.
Developer Advocacy Agents
Monitor community channels, triage GitHub issues, answer developer questions, and surface product feedback — 24/7 without burning out your DevRel team.
Competitive Intelligence
Track competitor launches, pricing changes, and feature updates across the web. Get weekly briefings delivered to Slack with actionable insights.
Email Sequence Agents
Dynamic email sequences that adapt based on user behavior, product usage data, and lifecycle stage. Higher conversion, zero manual segmentation.
Custom Integrations
Connect AI agents to your existing stack — CRM, analytics, helpdesk, community platforms. Every agent is built to fit your workflows, not the other way around.
How The Install Works
Audit Your Workflows
I map your current marketing, sales, and community workflows to identify high-impact automation opportunities — where AI agents will save the most time and drive the most growth.
Build Custom Agents
Each agent is purpose-built for your stack and workflows using LangGraph, Claude API, n8n, and Supabase. No off-the-shelf tools — these are engineered specifically for your business.
Monitor & Optimize
Agents are deployed with observability built in. I monitor performance, tune outputs, and iterate based on real results. You get weekly reports on what each agent accomplished.
What to build first, by stage
The mistake at every stage is building the wrong agent first. Below is the sequencing I recommend after running the install across 20+ DevTools startups — what to ship, what it actually automates, and the failure mode to plan around.
| Decision | Seed | Series A | Series B+ |
|---|---|---|---|
| First agent to build | Content repurposing (one blog → social + newsletter) | Lead enrichment + scoring | Multi-agent DevRel pipeline + competitive intel |
| What it automates | Founder content distribution | Inbound qualification + AE workload | Full-funnel observability + lifecycle ops |
| Time saved / week | 5-8 hours (founder) | 15-25 hours (marketing + AE) | 60+ hours across GTM + RevOps |
| Common failure mode | Over-engineering before PMF is clear | Bad data in CRM → bad enrichment → AEs lose trust | Agent sprawl with no observability or owner |
Time-saved estimates reflect production retainer installs (2023-2026). Seed-stage figure assumes a founder doing GTM work directly.
The Stack
Best-in-class tools, configured for your team — not a black box.
Want to put it to work?
Two ways to engage the agent stack.
Origin Install ($4,500, 7 days) gets the open-source 15-agent pipeline configured for your stack. AI-Powered Growth ($60K audit + $150K–$250K build) is the two-phase project that ships 8–25 custom agents.
See pricing & deliverablesReady when you are.
Discovery calls are 20 minutes. First one's on me.