Deep dives, technical analysis, and system breakdowns
LLM generation and crystal growth are mathematically identical, proven by Boltzmann distribution. 10-level distillation of 200+ papers across statistical mechanics, crystallography, information theory, and ML. Code binds to APIs like molecules bind to substrates.
Comprehensive analysis of agent systems: arizuko, Claude Code, Cline, Devin, OpenHands, Cursor, Langchain, Autogen. Architectural trade-offs in tool invocation, context management, state persistence, multi-agent coordination, and autonomous execution.
Designing simplicity & taste tools for LLMs. Scan codebase → extract structural patterns → output natural language fragments for prompts. Novel approach: automated detection of boring code patterns (guard clauses, flat control flow, function length) to nudge LLM code generation.
Comprehensive guide for software engineers entering biotech. Covers cellular factories, grown materials, software stack for bio R&D. From DNA assembly automation to fermentation scale-up, bioreactor control systems, and computational biology tooling.
Should an LLM write a program that learns, or edit its own weights? Each approach page names one orthogonal component and one documented failure: Darwin Gödel Machine, GEPA, AlphaEvolve, LLM-SR, ASI-Arch against SEAL, Titans, MEMIT, plus the substrates (SINDy, Neural ODE, Scallop, DreamCoder) and the cautionary AI Scientist audit. Same method as the Agents hub.
Why an LLM should write a learnable program instead of editing its own weights. Darwin Gödel Machine, GEPA, AlphaEvolve, LLM-SR vs SEAL, Titans, MEMIT. Substrates (JAX-MD, Neural ODEs, Pyro, SINDy), the forgetting cost, the bitter lesson, and the open lane in biology.
Reinforcement learning for coding agents. From reward modeling to policy optimization, self-play, and continual learning. Covers RLHF, outcome-based rewards, test-driven RL, multi-agent debate, self-correction, and iterative refinement strategies.
Analysis of Anthropic's AI-driven vulnerability discovery & exploitation capabilities. Claude Mythos autonomously discovers zero-days in major OSes and browsers. Disclosed vulnerabilities: FreeBSD NFS RCE (CVE-2026-4747), OpenBSD TCP SACK DoS, FFmpeg H.264 OOB, Linux kernel privesc chains. Over 99% remain unpatched.
Compilers, interpreters, and visualizations for esoteric programming languages. Brainfuck (300-byte compiler), Befunge-93 (2D stack-based), Whitespace (only spaces/tabs/newlines), Unlambda (pure functional combinator calculus). Interactive playgrounds with step debuggers and execution traces.
PocketBase (SQLite + Go monolith) vs arizuko (microservice agent gateway). Trade-offs in simplicity, scaling, and agent orchestration. PocketBase optimizes for single-developer simplicity with embedded DB. Arizuko optimizes for multi-agent coordination with separate processes and IPC.
Critical vulnerability disclosure: unauthenticated remote → full root access. Stack buffer overflow (304 bytes past 128-byte buffer). No stack canary, no KASLR. Exploit uses 6-packet ROP chain to append attacker SSH key. Full autonomous discovery and exploitation by Claude Mythos in several hours.