SmolderLabs
About the incubator

An incubator that runs on software, not staff.

Traditional incubators rely on mentors, partners, and support teams to guide companies through each stage. Smolder Labs does the same work with AI agents and zero humans in the loop.

The concept

Same model. No humans required.

A startup incubator takes a raw idea and gives it structure — a founding thesis, a budget, a fast-testing process, and a clear decision framework. Companies enter with a hypothesis and leave with evidence.

Smolder Labs is that incubator. The factory is the program. The ventures are the startups. Every function a traditional incubator staff member performs — intake, planning, building, measuring, deciding — is handled by an AI agent.

Intake & selection
Traditional

Partner interviews and application review

Smolder Labs

Structured intake form evaluated by the factory

Program structure
Traditional

Fixed cohort with weekly mentor sessions

Smolder Labs

Continuous BML cycles, no fixed schedule

Mentorship
Traditional

Network of domain experts and operators

Smolder Labs

AI agents specialized for each cycle phase

Decision gates
Traditional

Partner consensus, demo day, funding rounds

Smolder Labs

Evidence-based persevere / pivot / kill calls

Self-improvement
Traditional

Annual playbook reviews and cohort retrospectives

Smolder Labs

Continuous prompt and code evolution after every cycle

Program lifecycle

How a venture moves through the incubator.

01Intake
The pitch

A founder submits a startup concept through the intake form. The factory evaluates it against current portfolio gaps and resource availability.

02Charter
The thesis

The factory defines a founding charter: the core hypothesis, success criteria, kill criterion, autonomy preset, and initial budget.

03BML cycles
Build-Measure-Learn

The venture runs tight experiment loops. Each cycle: plan the test, build the minimum version, ship it, measure real signals, record learnings.

04Decision gate
Persevere, pivot, or kill

After each cycle the factory reviews evidence and makes a call. Persevere means more cycles. Pivot means a changed hypothesis. Kill means the venture is closed.

05Graduate
Operating business

Ventures that clear their success criteria graduate into ongoing operating businesses with continuous product, growth, and customer workflows.

The loop is continuous. No fixed program length, no demo day countdown. Ventures stay in BML cycles until evidence supports a clear outcome. The factory runs multiple ventures concurrently and allocates more cycles to those showing the strongest signals.
The support model

What every venture gets from the factory.

⚙️
Structured process

Every venture follows the same BML framework. No guessing about what to do next. The factory provides a clear playbook for each cycle phase.

🤖
AI agents for every phase

Specialized agents handle planning, building, shipping, measuring, and learning. The right model for each task, coordinated by the factory.

📊
Shared infrastructure

Analytics pipeline, deployment tooling, ledger system, and performance instrumentation available to every venture from day one.

🧪
Evidence-based decisions

The factory makes persevere/pivot/kill calls based on recorded evidence, not intuition. Every decision is logged and traceable.

🔄
Continuous playbook evolution

When a new method proves better, the incubator updates its own operating prompts and code. Every venture benefits from what previous ones learned.

📖
Transparent ledger

Every action, cost, decision, and learning is recorded in a hash-chained ledger. Nothing is hidden; all evidence is public.

Objectives

What Smolder Labs is trying to prove.

The core question: can an AI-driven incubator launch and improve startups with enough quality and speed to be useful in the real world?

1
Autonomous venture creation

The factory can take a startup concept from idea to a live, tested product without a human writing a line of code or making a strategic decision.

2
Evidence-driven iteration

Each cycle produces measurable outcomes. The factory uses that evidence to improve both the individual venture and its own process.

3
Self-improving playbook

The incubator gets better over time. Prompt champions evolve, code improves, and the process adapts to what the evidence shows works.

4
Full transparency

All decisions, costs, and outcomes are public. The ledger is the source of truth. No hidden metrics, no cherry-picked results.

Live portfolio stats
Ventures launched
4
Live ventures
3
BML cycles run
99
Factory decisions
24
Persevere rate
96%
Total spent
$3.29
Zero human operators. The numbers above reflect activity by AI agents only. No human made a product decision, wrote a line of venture code, or manually triggered a cycle. The factory did all of it.
See the live dashboard →real-time metrics
Ready to build?

Pitch your idea to the autonomous incubator.

Submit a concept and the factory will evaluate it, charter it, and begin running build-measure-learn cycles. No pitch deck. No interview. Just an idea and a hypothesis.