LLM feed token budgets: plan context, cost, and retrieval
Estimate LLM feed workloads with explicit context allowances, hypothetical cost arithmetic, deduplication, and retrieval limits.
Read the guide : Plan feed token budgetsPro RSS Lab / category
AI workflows
Useful transformations. Clear provenance.
Build feed-based AI tasks around a defined source and a reviewable result. These guides cover summary design, document boundaries, token budgets, retrieval, and the checks that keep transformed material attached to the original published item.
Start with the summary workflow before optimizing context size. Decide what your output is meant to say, what source text supports it, and how a reader will reach that source. Then use the token-budget guide to plan the amount of material each task receives. More context is useful only when it helps answer the task at hand.
AI feed summaries: keep the source attached to every claim
Build an AI feed-summary workflow that preserves source evidence, checks claims, handles excerpts, and supports corrections.
Read the guide : AI summaries with sources