AI Agents
AI Agents: Evidence ledger
Store each important claim with source identity, observation time and supporting excerpt.
Read article : AI Agents: Evidence ledgerExplore 2246 articles on AI, cybersecurity, networking and IT. 25 detailed practical guides now include concrete inputs, step-by-step procedures, expected results and troubleshooting. The remaining 2221 articles retain their existing content.
Defend against AI-assisted attacks with practical guidance for cybersecurity and network professionals. Ten reading paths contain 20 articles each, with threat scenarios, evidence requirements, control designs and authorized validation plans. The collection includes protection for AI systems used by defenders and businesses. Behavioral evidence is kept separate from claims about an attacker's use of AI.
Build reliable agents and run language models on your own infrastructure. Explore 160 AI Agents techniques and 140 Local LLM techniques across 15 reading paths, with 20 techniques per path. Each guide includes an implementation action, a validation exercise, platform context and official documentation for further reading.
Diagnose stale reports, late logs, slow queries and unreliable alerts. Explore 40 Power BI articles, 40 Splunk articles, 40 SQL Server articles, plus 20 each on PostgreSQL, MySQL, pipeline freshness and data quality, and alerting and observability. Each guide connects a specific symptom to evidence, a focused correction and validation.
Prepare for CCNA 200-301 v1.1 with 100 focused topics, each paired with a recall guide and an original practice exercise. Build understanding through packet tracing, subnet calculations, lab evidence, troubleshooting and spaced review. These are independent study guides; 200 is the collection size, not the number of questions on the exam.
Reviewed 2 November 2026. Check Cisco’s current exam information before booking. Reading paths are study groupings and do not represent official exam weights.
Ten focused reading paths with 20 articles each. Start from routing and fabric behavior, then explore transport, name resolution, security, host performance, storage, availability and incident evidence.
Choose a platform to explore 50 guides, from a first task brief to reusable workflows. Microsoft Copilot guides cover the consumer and Microsoft 365 experiences; in-app features depend on your account and license.
AI Agents
Store each important claim with source identity, observation time and supporting excerpt.
Read article : AI Agents: Evidence ledgerAI Agents
Separate harmless defaults from missing information that changes the target or outcome.
Read article : AI Agents: Ambiguity triageAI Agents
Report completed outcomes and remaining uncertainty at bounded intervals.
Read article : AI Agents: Progress checkpointsAI Agents
Estimate calls, elapsed time and output volume for each major phase.
Read article : AI Agents: Budget-aware planningAI Agents
Define completion, blocked and exhausted states in application code.
Read article : AI Agents: Stop conditionsAI Agents
Measure a single coordinator before introducing multiple interacting workers.
Read article : AI Agents: Single-agent baselineAI Agents
Package the objective, evidence, unresolved questions and artifact pointers for another operator.
Read article : AI Agents: Handoff packetAI Agents
Review the final artifact against original acceptance criteria and current evidence.
Read article : AI Agents: Outcome-based reviewAI Agents
Name tools by action and resource and avoid overlapping descriptions.
Read article : AI Agents: Narrow tool namesAI Agents
Declare required fields, types and allowed values and validate them before dispatch.
Read article : AI Agents: Required argument schemasAI Agents
Validate amounts, dates and resource ownership after syntactic schema checks.
Read article : AI Agents: Business rule validationAI Agents
Assign a unique call identifier and attach the matching result to that identifier.
Read article : AI Agents: Tool call correlationOur original short guides to AI, account protection, and recovery.