Welcome to the blog

2026-07-28T00:00:00-07:00

This is the first post on my blog. I’ll use this space for working notes and essays on the things I spend my days thinking about: agentic reasoning, inference-time compute, and large-scale neuroevolution as a path toward AGI.

This post doubles as a template — it shows every kind of content the blog supports, so future posts are copy-paste-and-edit.

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The thesis in one line: pre-training scaling is hitting diminishing returns, and the next leg comes from recursive self-improvement at inference time — gradient descent inside, evolutionary search outside.

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Neuroevolution as an outer-loop substrate: gradient descent trains each network, evolution searches over architectures.

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Code

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def evolve(population, generations):
    for _ in range(generations):
        for net in population:
            net.train()            # inner loop: gradient descent
        population = select(population)  # outer loop: evolution
        population += mutate(population)
    return best(population)

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