My work on Neuron started with the legal domain: building modular pipelines to help process messy, unstructured evidence (text, screenshots, audio, video) in cases where context fragmentation and memory limitations weren’t just inconvenient — they were a risk.
Neuron's architecture came out of that need: composable agents, memory layers, and reasoning strategies that could be tracked, validated, and extended.
Where I see Neuron in a year isn't as a product in a leaderboard of agents, but as a framework that underpins domain-specific reasoning systems: legal recovery tools, healthcare data evaluators, adaptive QA engines. It's not about shipping one perfect agent — it's about giving others a structure to build resilient ones.
It's still evolving. But it already shows that reasoning doesn't have to be abstract, and cognition doesn't have to be opaque.
Reflections on Saturation, Structure, and Survivability
Right now, nearly everyone is building agents. From startups raising on pitch decks to solo developers gluing APIs together, the field is saturated with frameworks, SDKs, wrappers, and orchestration tools. The phrase "AI agent" has come to mean almost anything: a chatbot with memory, a prompt chain with logging, or a UI layered over function calls.
This saturation won't last. Most systems built today will either consolidate, disappear, or evolve beyond recognition.
Much of what's labeled as "agentic" is just a shallow layer over existing APIs:
┌─────────────┐ ┌─────────────┐ ┌─────────────┐
│ Prompt │───▶│ Function │───▶│ UI Response │
│ Template │ │ Call │ │ Display │
└─────────────┘ └─────────────┘ └─────────────┘
These pipelines often collapse in production environments:
These tools will likely be absorbed by larger infrastructure providers or quietly phased out.