If something is costing your team time, slowing down growth, or simply doesn't have a good off-the-shelf solution, I figure out what should be built — and build it.
From revenue workflows and internal tools to AI systems, backend infrastructure, and custom software.
Problem → system → production → measurable impact.
Built with teams behind products people actually use.
Sometimes the problem starts as:
“Our sales team is wasting hours doing this manually.”
Sometimes:
“We have the data, but none of our systems talk to each other.”
Sometimes:
“We know AI could help here, but we don't know what should actually be automated.”
And sometimes:
“The software we need simply doesn't exist.”
That's where I do my best work.
I understand the problem, decide what software should solve, build the system, and stay with it until people are actually using it.
What I do
More revenue. Less work between the cracks.
Same work, every week.
Off-the-shelf software doesn't fit.
AI should do useful work — not just generate impressive demos.
More revenue. Less work between the cracks.
When sales or growth teams are spending too much time finding information, qualifying opportunities, moving data around, or following up manually, I build the systems underneath that work.
More opportunities through the same team.
Same work, every week.
If people are repeatedly researching, copying, checking, reporting, or moving information between tools, I look for the part software can reliably handle.
People stay involved where judgment matters.
Less repetitive work. More capacity.
Off-the-shelf software doesn't fit.
Some problems don't need another SaaS subscription.
They need software built around how the business actually works.
I build:
Your process, turned into working software.
AI should do useful work — not just generate impressive demos.
I build AI systems around real company data, tools, and constraints.
That means deciding:
Because in production, “usually works” isn’t enough.
Production, not prototypes
No toy demos. I've spent more than six years building systems used by real businesses, products, teams, and customers.
“Sam has been crushing it on an automated reply bot.”
15,000+
GitHub stars on the elizaOS runtime. Billing, credits, API keys, quotas, and usage infrastructure for thousands of hosted agents at Eliza Labs.
60%
Faster data-layer responses after five social APIs became one schema. Creators resolved across TikTok, YouTube, Twitter, Instagram, and Spotify. Shipped for Camp Network.
What I have built
At Eliza Labs, I built the credits, API-key, usage-metering, quota, and billing infrastructure used by thousands of hosted AI agents.
At Camp, I reverse-engineered external APIs and built the data layer that resolved creators across TikTok, YouTube, Twitter, Instagram, and Spotify into one model.
At Shield, I built the product backend through frontend as the engineer on the build and shipped against live customer feedback.
I built a complete revenue-data system that discovered companies from live signals, verified them at the source, resolved contacts, enriched records, and prepared them for outreach.
Every record carried evidence instead of asking the operator to trust an AI guess.
Case studies
Usage tracking, API keys, credits, accounting, quota enforcement, and production infrastructure for long-running agents.
Thousands of agents · production billing · plugin setup −70%
Read case study →02Reverse-engineered APIs, entity resolution, a unified data model, and infrastructure used by a live creator-analytics product.
5 platforms → 1 schema · response times −60%
Read case study →03Built the signal, verification, enrichment, sequencing, and human-review layers behind a complete revenue workflow.
351 companies · 456 contacts · source-verified
Read case study →04A zero-to-one build spanning backend, APIs, data model, and frontend, iterated against real customer feedback.
Shipped in four months
Read case study →A little about me
I've spent more than six years building software across early-stage companies, client projects, AI products, data systems, and infrastructure.
Over time I became increasingly interested in the part that happens before someone writes the code:
That led me deeper into customers, sales, growth, operations, and AI.
I still like building.
I just want the thing I build to matter.
2024–2026
Senior Software Engineer · AI infrastructure
2023–2024
Early engineer · data + AI
2023
Zero-to-one full-stack engineer
2022
CTO · customer discovery · B2B API
2021–2022
Founder · engineering services · 15+ international clients
2020 onward
Software engineering across startups and distributed teams
I'm especially interested in working with teams building ambitious AI and software products where the engineer is expected to understand the customer, think through the business problem, and own the solution through production.
I'm also open to selected projects where there is a real problem to solve and a clear outcome behind it.
