BrennerBot

What Is BrennerBot?

Sydney Brenner (1927-2019) was one of the most successful experimental biologists in history. He won the Nobel Prize for his work on programmed cell death and helped decode the genetic code. But his method is more valuable than any single discovery.

BrennerBot operationalizes that method for AI-assisted research. It helps you develop hypotheses that can actually be tested, design experiments that discriminate between alternatives, and think rigorously about what you're assuming.

The Two Axioms

Brenner's methodology rests on two foundational beliefs:

Reality has a generative grammar

The world is produced by causal machinery with discoverable rules. Phenomena aren't random — they're generated by underlying mechanisms that we can identify and understand.

To understand is to reconstruct

You haven't explained something until you can build it from primitives. Description isn't explanation — you need to specify the mechanism that produces the phenomenon.

What You'll Produce

By the end of this tutorial, you'll have a research artifact for your own scientific question. Here's what it contains:

Hypothesis Slate

2-5 competing explanations, including a genuine "third alternative"

Discriminative Tests

Tests designed to separate hypotheses, not just confirm your favorite

Assumption Ledger

Explicit load-bearing beliefs that your hypotheses depend on

Adversarial Critique

Attacks on your own framing to strengthen your thinking

Pro Tip

You don't need any AI subscriptions for this tutorial. The Quick Start path works with any AI chat interface — Claude, ChatGPT, Gemini, even free tiers. You'll compose prompts locally and paste them into your preferred AI.

Sample Artifact Preview

Here's a snippet of what a completed research artifact looks like:

my_artifact.md

# Research Artifact: Cell Fate Determination
 
## Hypothesis Slate
 
### H1: Morphogen Gradient Model
Cells determine their fate by reading concentration gradients
of signaling molecules (morphogens) secreted from organizing centers.
- Mechanism: Concentration-dependent transcription factor activation
- Anchors: §58, §78
 
### H2: Timing Model
Cell fate is determined by intrinsic timing mechanisms that
count cell divisions or developmental stages.
- Mechanism: Sequential gene expression programs
- Anchors: §161
 
### H3: Third Alternative (Stochastic + Selection)
Initial fate assignment is stochastic, with selection
mechanisms eliminating "incorrect" outcomes.
- Mechanism: Random differentiation + competitive survival
- Anchors: §203
 
## Discriminative Tests
...

Next up: In Step 2, you'll verify your prerequisites — Git, terminal access, and Bun. It only takes a couple of minutes.