Why? Self-interest has made everyone blind to open corruption.

The worst part is reality hits 3-4 years later, and the big guy is already out and about. Already with his billions, partying in the Caymans.

Welcome to democratic oligarchy!!

I also have a self-evolving architecture on it, but you have to be careful, especially if you're using multiple models (still WIP).

Multi-agent / org (core/agent_radio/, core/fleet_orchestration/): - Stanford Virtual Biotech — bioRxiv 2026.02.23.707551, Zou Lab — https://www.biorxiv.org/content/10.64898/2026.02.23.707551v1 — 37k agents, CSO->scientists->reviewer->re-delegation, Merck external validation of B7-H3 design. Basis for VFS + hierarchy. - Debate or Vote (Choi & Li) — NeurIPS 2025 — https://arxiv.org/abs/2508.17536 — MAD gains = majority vote, not debate (why we didn't build debate)

Sandbox / eval: - DABstep — arXiv:2506.23719 — https://arxiv.org/abs/2506.23719 — 450 real Adyen tasks, justifies code-interpreter + sandbox isolation - Spotlighting — Microsoft Research — https://arxiv.org/abs/2403.14720 — provenance delimiters cut injection ASR 50% -> <2%

Governance: - OWASP Top 10 for Agentic Applications 2026 — globally peer-reviewed by 100+ experts, Dec 2025 — https://genai.owasp.org/resource/owasp-top-10-for-agentic-ap... — HIGH. Atom maps 1:1 (Goal Hijack -> match-confidence + oracle, Tool Misuse -> sandbox whitelist/caps, Privilege Abuse -> capability bindings, Memory Poisoning -> verified-episode graduation, etc.) docs/marketing/RESEARCH_NOTES.md:130 - NIST AI Agent Standards Initiative — Feb 17 2026, NIST CAISI — https://www.nist.gov/artificial-intelligence/ai-agent-standa... + RFI summary May 2026 https://www.nist.gov/publications/summary-analysis-responses... — HIGH (US gov standard). Defines the 4 enterprise minimums Atom implements: identification, authorization, access delegation, logging. - Stanford Virtual Biotech — bioRxiv 2026.02.23.707551 — https://www.biorxiv.org/content/10.64898/2026.02.23.707551v1 — CSO -> 4 divisions -> 8 scientists -> reviewer -> re-delegation, no debate, no SFT — HIGH (Stanford Zou lab + Merck external validation). Basis for Atom's fleet hierarchy core/agent_radio/ and why maturity is routing not security. - Spotlighting — Microsoft Research — https://arxiv.org/abs/2403.14720 — HIGH — provenance delimiters cut indirect injection ASR 50% -> <2%, used in core/provenance.py:10 - IntentGuard — https://arxiv.org/abs/2512.00966 + OpenReview — HIGH — intent tracing ASR 100% -> 8.5% on AgentDojo/Mind2Web, basis for sandbox egress allowlist + core/sandbox_tripwire.py

1. Guardrails - deterministic, social intelligence, team alignment & accountability 2. Learn by doing 3. make it stupid easy for the agent to research and access data 4. DRY

Research supports this. Try picking up some ideas from my harness: https://github.com/rush86999/atom

Now with OpenCode Go integration. I'm rapidly fixing as many bugs as I can, and with the same subscription. Thank you, DeepSeek!

That's a pretty good benchmark

I also developed something similar for my agent harness. It's based on model predictors and an exponential moving average:

https://github.com/rush86999/atom/blob/main/docs/architectur...

One missing point: careers that require communication, especially person-to-person, won't be replaced by AI. Why? Because people don't like to speak with AI when they have a hard pain point to solve. It's not about intelligence; it's about trust and relationships that AI cannot replace.

Everyone is trying to figure out how to achieve this prerequisite. I'm thinking of agent harnesses. That's what everyone is trying to do at this point.

That's the same problem I'm trying to solve: https://github.com/rush86999/atom

https://github.com/rush86999/atom/blob/main/backend/core/off...