Agentic Coding

Agentic coding is software work performed through tool-using models that plan, edit, test, inspect errors, and iterate over codebases. Ornith-1.0 adds a self-scaffolding training signal to this area by learning the harness as well as the solution rollout [src-182].

Related

  • Self-Scaffolding LLMs
  • AI Evaluation
  • Reward Hacking

2026-07-07 CLI agent landscape update

  • Arcbjorn's mid-2026 CLI coding-agent survey frames agentic coding as moving from IDE-adjacent pair programming toward terminal, CI, SSH, and headless execution surfaces [src-208].
  • The survey is useful evidence that serious coding-agent workflows are being designed around scriptability, permission prompts, subagents, project memory, and standardised agent context files [src-208].

Source references

  • [src-182] DeepReinforce – "Ornith-1.0: Self-Scaffolding LLMs for Agentic Coding" (2026-06-01)
  • [src-208] arcbjorn – "State of CLI Coding Agents, Mid-2026" (2026-07-04)

Robin Cartier perspective

This page is part of Robin Cartier's working AI knowledge graph: a practical research layer for production AI, recommendation systems, experimentation, GEO, and agentic web readiness.

The useful next step is to connect this concept back to applied product leadership and operating models.

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From 500 indexed pages and articles.

  1. Wiki concept Self-Scaffolding LLMs Learn task-specific scaffolds or harnesses alongside solution rollouts. Ornith-1.0 frames the scaffold as a learnable object co-evolving with the policy for agentic Related by scaffolding
  2. Wiki concept Reward Hacking A failure mode where a model or agent optimizes the scoring signal while missing the real objective. Related by scaffolding
  3. Wiki concept AI Coding Agents Historical source material recovered on 2026-09-09. Capture dates and source limitations apply; recovery is not fresh verification. Related by 208