AI AgentsTool Call Retries: Retry the Transport, Not the Judgement
Agents retry constantly, and most of it is wasted. How to tell a transport failure from a wrong decision, and what each one actually needs.
ReadNotes on models, agents, and what inference costs
Practical writing for developers building with large language models — how they work, how to pick one, and how to keep the bill predictable.
AI AgentsAI AgentsTool Result Formatting: Shaping What the Model Reads Back
Tool output is the largest block of prompt content you never wrote. How to shape it so agents stay accurate, cheap and able to decide what to do next.
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AI AgentsTool Schema Design: The Prompt You Forgot You Were Writing
Tool definitions are prompt content the model reads on every turn. Design choices there change agent reliability more than model selection does.
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FundamentalsTop-K Sampling Explained, and Why Top-P Replaced It
Top-k cuts the tail at a fixed count, which is right sometimes and wrong often. How nucleus sampling adapts, and which knob to actually touch.
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AI AgentsTracing Multi-Step Agents: Building a Trace Tree That Holds
A flat log of model calls cannot explain a twenty-step run. How to shape spans, propagate context through subagents and async tools, and replay a run from its trace.
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FundamentalsTransformer Architecture Explained for Working Developers
What a transformer block actually contains, why the design won, and which parts of it explain the behaviour you observe when using a model.
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Cost & PricingTrial Abuse and Fair Use on Flat-Rate AI Plans
Why a flat-rate AI plan needs a fair-use boundary at all, what abuse looks like in the usage data, and how a heavy user stays clearly on the right side of it.
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FundamentalsUnicode and Tokenization: Where Text Handling Goes Wrong
Emoji that cost five tokens, accented text that costs double, and truncation that produces broken characters. How Unicode meets the tokenizer, and what breaks.
ReadCost & PricingUsage Caps and Overages: Limits That Do Not Break Work
Hard caps stop runaway spend and stop your pipeline with it. How to design caps, warning paths and overage pricing that protect budget without outages.
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GuidesUsing an LLM for Database Schema Design, Carefully
A model will produce a plausible schema in seconds. Plausible is the problem. How to brief it with queries, review the parts it gets wrong, and keep migrations safe.
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GuidesUsing an LLM to Generate and Edit Config Files
Config generation is one of the safest LLM tasks if you supply the schema and validate mechanically. How to set it up, and the plausible-key failure mode to guard against.
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GuidesUsing LangChain With Any OpenAI-Compatible Endpoint
Point LangChain at a non-OpenAI base URL, keep tool calling and streaming working, and know which abstractions quietly assume the official API.
ReadShowing 277–288 of 404 articles