THE ML LIFECYCLE,
AS A SKILL.
Your AI already codes. Gaslamp teaches it to build, deploy, and report on production ML — natively inside Claude Code and Gemini CLI.
Who Is Gaslamp For?
AI agents can chat about models. Gaslamp makes them actually build, deploy, and report on them.
The First Hire
Junior MLE or the first AI researcher on a small team. You need a companion who guides you through best practices — not just generates code.
→ Ship your first production model with confidence.
The Evaluator
Technical PM exploring whether ML can enhance a product feature. You don't have a data science team yet, but you need a proof-of-concept fast.
→ Validate an ML idea for under $10.
The Accelerator
Senior MLE who wants to focus on novel architecture — not wrestle with CUDA paths, Python envs, and deployment boilerplate.
→ Automate the 80% that isn't research.
The Roadbook
Every Gaslamp project produces a gaslamp.md — a Living Architectural Decision Record that captures why every choice was made.
Every Decision, Documented
You don't have to trust the AI blindly. gaslamp.md is your permanent trail of every fork in the road and why you turned left instead of right — auditable, explainable, reproducible.
A learning journal. Understand the reasoning behind every architectural choice as you build.
The artifact you bring to the leadership review. Auditable decisions, not black-box magic.
A reproducibility guarantee. Pick up any project months later and understand it instantly.
## Decision 1: Model Architecture
- Chose: Random Forest
- Rejected: Fine-tuned LLM
- Rationale: Tabular data, latency <50ms required.
LLM adds cost without predictive benefit.
## Decision 2: Feature Strategy
- Used: recency, frequency, monetary (RFM)
- Rationale: Classic e-commerce signal.
Adding session-based features for v2.
## Status
- Phase: Deployed ✓
- Cost: $0.12 total training
- Next: Stakeholder demo generated
The Frictionless Platform (1/6)
Get Started
Gaslamp works for both humans and AI agents. Pick your path.
Install in Your CLI
Add Gaslamp as a skill to your favorite AI coding assistant. Then just describe what you want to build — Gaslamp handles the rest.
claude mcp add gaslamp
Then: "Use gaslamp to build a churn prediction model."
gemini use gaslamp
Then: "I need to predict seasonal sales for headphones."
Download the skill and add it to your agent's context window. Gaslamp is a markdown skill — it works anywhere.
1. Describe your problem in plain English.
2. Gaslamp interviews you to define success metrics.
3. It creates a unified workspace with all artifacts.
4. Trains, evaluates, and deploys the model.
5. Generates a demo site and executive report.
Every decision is logged to gaslamp.md.
You own the full audit trail.
In Practice
Real-world stories from teams using Gaslamp to ship ML products.
From Toy to Tool
The design philosophy behind Gaslamp — why we built an ecosystem layer on top of the AI agent primitive, and what it means for ML engineering.
Read the manifesto →Customer StoryThe 4-Hour ML PM
How a technical PM with no ML background went from a vague product idea to a working time-series forecasting model in a single afternoon.
Read the story →Customer StoryThe $10 PoC
A midsize company proved ML feasibility and secured budget for their first MLE hire — all for less than a lunch.
Read the story →