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Agentic Systems

21 summarised stories about Agentic Systems, each linking back to the original source. Browse all topics →

Friday, 17 July 2026

Digital Ecosystems: Interactive Multi-Agent Neural Cellular Automata

Sakana AI 2 sources

Sakana AI released Digital Ecosystems, a browser-based platform where small neural networks compete on a 2D grid, learning via gradient descent while the simulation runs. The system contains 40+ tunable parameters and runs entirely in the browser without installation. The research found that gradient descent stabilizes the ecosystem by preventing species from overextending or stagnating, enabling exploration of complex emergent behaviors.

Frontline Development in Defense Sector: Sakana AI Software Engineer Interview

Sakana AI 5 sources

Sakana AI launched an Applied Team in early 2025 to implement generative AI technology in sectors like finance and defense. The company is developing command-and-control systems for defense that integrate large volumes of field data from drones and other sources to support rapid situational assessment and decision-making by military personnel. Software engineers at Sakana AI work on mission-critical defense applications using Python, TypeScript/Next.js, and Kotlin, with generative AI serving as an essential tool across implementation, goal-setting, and problem extraction.

The Insights Factory: how we run deep data investigations with LLM agents

TLDR Dev 4 days ago

Photoroom's data team developed the Insights Factory, a system that decomposes complex analytical questions into hundreds of small, auditable SQL queries executed by LLM agents with fresh context for each task. The system stores investigation memory in a markdown file rather than a context window, uses five reusable skills to orchestrate agent work, and costs approximately $5 per investigation while remaining fully auditable. This architecture addresses LLM limitations with long context and multi-step reasoning by giving each agent a single atomic task, maintaining external memory to avoid token re-billing, and ensuring human validation at the start and end of each investigation.

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