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Babar Hayat

As seen in: Nature, MDPI, Blasting News, ESPN Cricinfo, DEV Community, The Cureus Journal of Medical Science, Eversheds Sutherland, Professional Adviser, Estates Gazette
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Articles

The Hidden Math: Why "Cheapest Model" Doesn't Mean Cheapest Execution

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By Babar Hayat
| DEV Community
You're building an AI agent. Smart cost strategy: route to GPT-4o when you need reasoning, Haiku for simple classification, Groq when it's available and fast. In your head, the math is simple: pick the cheapest model per task. In practice, you ship code and never really know if it worked. Here's the gap: cheapest model ≠ cheapest execution. A single agent run might span multiple model calls. One task uses Anthropic's Sonnet ($3 / 1M input, $15 / 1M output).
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Your Agent Returned 200 and Did Nothing: Detecting Silent Failures with Token Counts

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By Babar Hayat
| DEV Community
Your agent returned HTTP 200, zero errors in the logs, and then did nothing. The failure wasn't loud — it was silent. This happens more than you'd think. An agent invokes a model, gets back a response, processes it, returns success. But somewhere in that flow the actual output — the thing that was supposed to happen — vanished. No exception. No timeout. Just an empty response where a decision or action should have been.
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Delegation Masking: Why Your LangChain Callbacks Lie About Sub-Agent Failures

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By Babar Hayat
| DEV Community
You delegate a task from Agent A to Agent B in LangChain. Agent B fails. Agent A's callback chain fires 'success' anyway. This is the observability blind spot most builders miss in agentic workflows: delegation masking. A sub-agent fails silently, but the parent agent's callback layer never knows because it only watches the delegation call itself, not what the delegated agent actually did. Let's walk the mechanism.
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