Blog Archive
Validating Tool Outputs with Pydantic Contracts
Learn how to enforce rigorous Pydantic schema validation on external tool outputs in AI agent pipelines, preventing downstream corruption and silent failures.
The Complete Guide to ADK-Rust v2: High-Performance Enterprise AI Agents in Rust
A comprehensive deep-dive into ADK-Rust v2, covering core runtime concepts, workflow agent patterns, tools & protocols (MCP/ACP), realtime multimodal audio, and production deployment case studies.
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.