Reasoning & Memory
How models think, remember, and retrieve information. Reasoning tokens, RAG pipelines, context engineering, and the memory architectures that make agents useful.
Guides and explainers
Detailed guides and practical technical analysis.
Latest analysis
Recent research, benchmark reviews and technical updates.
Practical tools
Templates for budgets and project planning
BoredTools offers practical spreadsheets for budgets, freelance work and small projects.
IFCMemoryBench Finds the Missing Project Facts
IFCMemoryBench turns agent memory into an engineering test: can a building-information assistant remember project facts from earlier sessions and combine...
Million-Token Context Still Fails the Workload Test
Anthropic reported on February 5, 2026 that Claude Opus 4.6 scored 76% on the 8-needle 1M-token MRCR v2 test while Claude Sonnet 4.5 scored 18.5% on the...
Knowledge Graphs for AI Agents: Beyond Vector Search
Vector databases power most retrieval-augmented generation systems in production today. They're fast, simple, and good enough for single-hop lookups...
RAG Cost Attacks Turn Retrieval Into a Budget Risk
A June 2026 paper on retrieval-augmented inference cost attacks reports a failure mode that many RAG teams are not testing: poisoned external documents...
Multimodal Memory Tests Expose the Personal-Agent Gap
Product teams are turning memory into the selling point for personal agents. The hard question is no longer whether they can remember a preference; it is...
Agent Memory Fails on Relationships, Not Recall
New June 2026 memory benchmarks show why long-running agents fail when facts conflict, evolve, or depend on hidden relationships.
Evaluation-Aware Memory: How Agents Should Remember What They Can Prove
Agent memory should promote facts only after evals prove they improve task outcomes, not just because retrieval found them.
RAG Maintenance After Deployment: The Failure Mode Nobody Budgets For
RAG maintenance after deployment is the hidden operating cost: stale indexes, drifting corpora, weak evals, and silent retrieval failure.
Assistant Agents Need Reminder Tests, Not Recall Scores
Most agent-memory benchmarks ask whether a model can recover old information. PM-Bench asks a harsher question: can an agent remember to do the right...
Context Window Management: When 1M Tokens Isn't Enough
Claude Opus 4.6 scores 76% on MRCR v2 at 1 million tokens. Gemini 3 Pro drops to 26.3%. Bigger windows don't solve the context problem — they change it. Research-backed strategies for chunking, compression, and retrieval.