Recent Blog Posts
Insights on AI Agents, Modern Web, and the Future of Engineering.
Safety Settings in the Gemini API: Blocking Harmful Content Before It Ships
Configure Gemini API safety settings to block harmful content at the API level. Set category thresholds, handle safety ratings, and build production-ready content filtering.
Toxicity and Safety Filters for LLM Outputs: A Hands-On Guide
Implement production-ready toxicity and safety filters for LLM outputs. Classify, filter, and sanitize harmful content before it reaches your users.
Memory-Augmented Prompts: Injecting Recall into Every Agent Turn
Transform static prompts into dynamic, memory-aware prompts that automatically inject relevant past context. Build agents that remember without being told to.
Short-Term vs. Long-Term Memory: Architecting Multi-Horizon Recall
Design agent memory systems that span multiple time horizons. Balance fast short-term context with durable long-term knowledge for effective agent recall.
Memory Pruning: Forgetting, Expiry, and Context Budgets for Agents
Agents that never forget eventually drown in irrelevant context. Learn strategies for pruning memory — TTL-based expiry, relevance decay, and budget-aware selection.
Choosing an Agent Memory Store: Vector DBs, Key-Value, and Graphs
A practical comparison of memory store backends for AI agents. Learn when to use vector databases, key-value stores, and graph databases for different memory patterns.
Conversation Summaries as Memory: Compressing Sessions for Context
Learn how to compress long conversations into concise summaries that preserve key information, reducing token usage while maintaining agent context.
Semantic Recall: Making Agent Memory Searchable with Embeddings
Transform agent memory from keyword-matching to semantic understanding. Use embeddings to let agents find relevant past experiences by meaning, not just keywords.
Long-Term Knowledge Stores: Moving Beyond Rolling Chat History
Stop treating agent memory as a sliding window. Learn how to build long-term knowledge stores that persist insights, facts, and context across thousands of interactions.
Episodic Memory in Agents: Recording Sessions as Replayable Experiences
Learn how episodic memory enables AI agents to record, store, and replay entire sessions — turning one-off interactions into reusable, learnable experiences.
Building an Agent Risk Register from the OWASP LLM Top 10
How to build a practical agent risk register using the OWASP LLM Top 10 and Agentic Top 10 — with risk scoring, mitigation strategies, and code examples.
Structured Logging for Agent Decisions: Events, Inputs, and Outputs
How to implement structured logging for AI agent systems using OpenTelemetry, AgentTrace, and production observability tools.