You have probably seen this with Claude Code or any long agent run: – it repeats work
– it forgets a decision
– it argues with stale instructions
– it misses the exact file you mentioned earlier
– the API bill keeps climbing That is not random.
LLMS
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Systematic failures in long agent runs: repetition, forgetting, high API bill
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General-Purpose AI Agent Surpasses Karpathy’s Auto-Researcher by Self-Improvement
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A GENERAL-PURPOSE AGENT SURPASSED KARPATHY'S AUTORESEARCHER It wasn't designed for research. It simply improved itself until it achieved it The framework behind it is called SIA by Hexo Labs and it's open source → The agent updates its own logic
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Agent Context Expansion Shifts AI Token Pricing Economics
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As agents use more context, input tokens have become the majority of price-equivalent token costs.
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Cost Per Accepted Line of Code Across Model Families
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The cost per accepted line of code varies by roughly 7x across model families.
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MS Office now powered by Perplexity Computer
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MS Office is now powered by Perplexity Computer https://t.co/fIcY5TZ7lT
— Aravind Srinivas (@AravSrinivas) 28 mai 2026MS Office is now powered by Perplexity Computer
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Claude Opus 4.8 spotted in source code, might drop today.
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ANTHROPIC : Claude Opus 4.8 has been spotted in the source code. Would it drop today?
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Managed Deep Agents: Features for Agent Creation and Workflow Support
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Managed Deep Agents lets you create a managed Deep Agent without standing up a custom agent server. Our runtime supports: Durable threads Streaming runs Checkpointing Human-in-the-loop workflows
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Why Inference Latency Matters Over Training Throughput
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Why does this matter for AI inference specifically? Training = throughput problem. Inference = latency problem. When a user talks to an AI assistant, tokens have to return fast. Latency, memory access, bandwidth, and interconnect all matter, not just raw compute. In large AI
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Improving a Prompt: The Constraint Architect
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Challenge 2: The Constraint Architect Hand them this prompt and ask them to improve it before running it: "Write a blog post about marketing." Then count. How many constraints do they add? Audience. Word count. Tone. Structure. Examples. Output format. Point of view. What to
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Cold Start Prompting Test for AI Assistants
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Challenge 1: The Cold Start Test Give them this brief and nothing else: "Write me a landing page for my product." No context, audience, tone. Not even constraints. Now watch. Do they paste it straight into Claude or do they ask you 3-5 clarifying questions first? A skilled