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.
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Recent research, benchmark reviews and technical updates.
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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.
Knowledge Graphs for AI Agents: A Practical Guide
Build useful agent memory with stable entity IDs, explicit updates and permission-aware retrieval. Includes a runnable example.
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.
More Context Doesn't Kill RAG. It Just Changes the Fight.
Long-context LLMs now hit a million tokens, but a persistent 10% accuracy gap and punishing costs keep RAG very much in the fight.
Agent Memory Needs Quarantine, Not Recall
Persistent memory is moving from chat convenience into personal-agent infrastructure. The failure mode is not just forgetting. It is remembering the wrong...
The NHS Bet on AI Triage Is Bigger Than Anyone Admits
A single GP surgery in Surrey cut patient waiting times by 73% in four months. Not by hiring more doctors. Not by extending hours. By letting an AI decide...
Chain-of-Thought Prompting Doesn't Always Work. Here's the Evidence.
Think step by step. It's the most common prompt engineering advice in circulation, repeated in tutorials, baked into system prompts, and treated as a...