News & guides
Tool 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.
· 8 min read
Tool 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.
· 8 min read
Top-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.
· 8 min read
Tracing 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.
· 9 min read
Transformer 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.
· 9 min read
Trial 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.
· 9 min read
Unicode 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.
· 9 min readUsage 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.
· 12 min read
Using 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.
· 9 min read
Using 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.
· 9 min read
Using 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.
· 9 min read
Vendor Lock-In Costs: Measure It Instead of Fearing It
The HTTP call is trivially portable. Prompt tuning, tool-call formats, evaluation baselines and caching semantics are not. How to measure and contain the expensive parts.
· 9 min readReady to try it?
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