Multiplayer AI will revolutionize the way we work | OpenClaw Foundation’s Vincent Koc
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This roundup covers multiplayer AI coding setups, harness economics, and PR review bottlenecks. OpenClaw Foundation's Vincent Koc describes OpenClaw 2.0, where teammates and their agents share sessions on shared servers and hand off work overnight. A separate test found a harness of specs and tests took GPT-6 Luna from 3 of 10 passing runs to 10 of 10, while GPT-6 Sol passed all ten regardless but cost seven times more with the harness. LinearB's 2026 report found agentic AI pull requests wait 5.25 times longer for review, and only 32.7% merge versus 84.4% for human-written ones. Other items cover a 'Glass Town' auditable AI coding factory and AI-driven game decompilation reaching native 1440p at 165 FPS.
Table of contents
2. Glass Town keeps the receipts3. An agent that checks the review queue first4. What your software factory is doing to your engineers5. AI took the status updates, not the job6. You can reverse engineer and customize basically anything now7. This week! Come find us at ObservabilityCon and AGNTCon + MCPConQuestions this post answers
Does adding a test harness to an AI coding agent actually improve results, or just add cost?
It depends on the model's baseline capability. In one test, a weaker model (GPT-6 Luna) improved from passing 3 of 10 acceptance-test runs to 10 of 10 when given a harness of specs, examples and deterministic tests, and still cost about a third less than an unharnessed stronger model (GPT-6 Sol). But Sol passed all 10 runs with or without the harness, meaning the harness only added about 7 times the cost with no benefit for that model. Weigh harness costs against model capability before deciding on daily.dev when agent workflows are worth the overhead.
How much longer do AI-generated pull requests take to get reviewed compared to human-written ones?
Agentic AI pull requests wait 5.25 times longer for pickup than unassisted, human-written PRs. Additionally, only 32.7% of AI-generated PRs end up merging, compared to 84.4% of human-written PRs, according to LinearB's 2026 Software Engineering Benchmarks Report based on more than 8.1 million pull requests. Teams scaling AI-generated code track review bottlenecks like these on daily.dev before they bite.
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