Agentic Coding
Top tech stories today across software, hardware, AI, and product launches. Senior engineer audience — skip rumour churn and pre-announcement leaks. Lead with shipping-now stories and what changed for builders.
Harness engineering outpaces prompts, open-source orchestrator drops discipline agents
1 min read
Harness engineering
The competitive moat just shifted from prompts to harnesses.
A new framework calls agent harness engineering the next evolution—model plus five components: personalisation via global CLAUDE.md files, project-specific context rules, action connectors to tools like Notion and Linear, memory that saves every mistake as a permanent rule, and delegation to specialist agents for complex workflows [Source: MarTech AI]. The folder structure lives at ~/.claude/ with memory folders, skills, commands, and agents. The core discipline: stop and document every correction so it compounds over time.
Your harness eventually runs jobs end-to-end with minimal intervention—that's the pitch.
oh-my-openagent
Someone built the multi-agent orchestrator you've been stitching together manually.
oh-my-openagent ships discipline agents with memorable names: Sisyphus orchestrates, Hephaestus handles autonomous deep work, and Prometheus does strategic planning—all running in parallel so you stop juggling models across Claude Code and Cursor [Source: GitHub]. The /init-deep command auto-generates hierarchical AGENTS.md files for token efficiency, while hash-anchored edits eliminate stale-line errors. Built-in MCPs cover web search, GitHub search, and official docs, and it stays compatible with your existing hooks and skills.
Worth testing if the four-agent ceilings from two days ago still feel limiting.
Skills ecosystem update
The plugins you've been tracking keep getting sharper tooling.
Both new frameworks this week emphasize auto-generating AGENTS.md rather than hand-writing them—a shift from the 313-skill library and gstack drops you bookmarked earlier. oh-my-openagent's ultrawork command chains the full workflow from planning through execution, while the harness pattern from MarTech AI formalizes the memory-saving habit that makes skills actually stick. The common thread: encode your corrections once, never re-teach them.
Your next session should probably start with /init-deep.
Wait, your Claude doesn't have a harness?! - MarTech AI16 hours ago ... Boris runs Claude Code at Anthropic and his template is the closest thing to a community best-practice standard.charliehills.substack.com

The article introduces agent harness engineering as the evolution beyond prompt and context engineering, defining it as a model plus five components: personalisation (global CLAUDE.md files), context (project-specific rules), action (tool connectors like Notion and Linear), memory (mistake corrections saved as permanent rules), and delegation (specialist agents for complex workflows). For Claude Code users, the harness is built through a folder structure at ~/.claude/ containing CLAUDE.md files, memory folders, skills, commands, and agents, while the same architecture applies in Cowork through settings and project-level configurations. The article emphasizes that the core discipline—stopping to document and save every mistake as a permanent rule—compounds over time, eventually enabling the agent to run jobs end-to-end with minimal human intervention, and notes that the harness itself is now the competitive moat rather than the underlying model.
code-yeongyu/oh-my-openagent: omo; the best agent harness21 hours ago ... ... the best agent ... Context Injection: Auto-inject AGENTS.md, README.md, conditional rules; Claude Code Compatibility: Full hook system, commands, skills, agents, ...github.com
oh-my-openagent is an open-source orchestration framework for agentic coding that addresses the user's specific interests in advanced AI agent workflows and optimization. The project features discipline agents like Sisyphus (orchestrator), Hephaestus (autonomous deep worker), and Prometheus (strategic planner) that work in parallel, eliminating manual model juggling across Claude Code, Cursor, and other harnesses. Key best practices highlighted include using hash-anchored edits to eliminate stale-line errors, auto-generating hierarchical AGENTS.md files via /init-deep for token efficiency, and leveraging the ultrawork command for complete workflow automation. The framework integrates LSP, AST-Grep, and built-in MCPs (web search, GitHub search, official docs) while maintaining full compatibility with Claude Code hooks, commands, and skills, enabling the efficient PRD and AGENTS.md workflows the user seeks without vendor lock-in.