With this you are not using a 3rd-party harness anymore, but the 1st-party claude one. I recommend switching to a more friendly model provider tho. There's quite a lot that offer good subs.
LLMS
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Claude -p harness call allowed by Anthropic
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this calls claude -p, which is their 1P harness and allowed.
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OpenAI Preparing Imminent Release of Image Generation Model v2
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OpenAI’s image gen v2 release immanent
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Databricks Releases New Foundation Models and Platform Updates
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Nick Karpov and Holly Smith walk through some of the latest Databricks features – and how they work together under a single architecture. Our R&D teams have been busy. Recent updates include:
– Three new foundation models in Databricks Foundation Model API support
– Stateless -
Everyone’s AI Psychosis Phase: Sydney, 4o, and Opus
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Everyone goes through an AI psychosis phase, for some it is 4o, for others it's Opus. For me it was Sydney.
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From Code Repos to Idea Files: AI Agents Replace Traditional Sharing
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This is the way. Don't share apps, share ideas with AI Agents. Karpathy just introduced a new primitive: "the idea file". Instead of sharing a repo with code to clone, you share a markdown doc with the idea. What to build, not how to build it. Your agent reads it and figures out the rest. I pointed my OpenClaw agent Monica to it. Within one session, they read the idea file, compared it against our existing setup (6 agents already coordinating through markdown files on a Mac Mini), identified what we're already doing and what's missing, and started building the parts we don't have. Turns out we already had the ingestion layer without knowing it. Our intel agent scans sources twice a day and writes structured signals to a daily file. The raw data gets saved, but nobody ever looks at it again. What we were missing: compilation. 60 days of daily signals sitting in files, but no agent turning them into structured knowledge. My agents only see today's intel. They can't say "this is the third local OCR tool this quarter" because that context isn't compiled anywhere. Monica caught that gap on her own from the idea file. You don't need someone else's code. You need their thinking. Your agents handle the rest, and they'll customize it to what you actually need. We are moving from cloning repos to sharing ideas with Agents. Shubham Saboo (@Saboo_Shubham_) x.com/i/article/202179384677… — https://nitter.net/Saboo_Shubham_/status/2022014147450614038#m
→ View original post on X — @saboo_shubham_, 2026-04-04 17:57 UTC
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Managing Long-Running Tasks with Codex Planning
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so typically for long running task you’d want codex to have a to-do md or plan md and have it update it as it continues chugging along and then ask it to respond with a phrase of your choice “__CODEX_DONE__” for example and then you can add an if-else to your hook to exit when
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Human Cognitive Errors vs LLM Hallucinations Explained
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So many people are confused about the relation between human cognitive errors and LLM hallucinations that I wrote this short explainer two years ago. Since many of those confusions persist, I am reposting:
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LLM NPC Implementation with Custom Prompts for Each Agent
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it’s not actually a custom GPTs in the ChatGPT sense but a LLM call w unique prompts for each NPC