Recent Blog Posts
Insights on AI Agents, Modern Web, and the Future of Engineering.
Beyond AI: An Executive Brief for C-Level Leaders
AI changes every month, but the principles of designing work change every ten years. An executive brief on how to manage AI — warning signs, the resource mindset, five strategies, and the role each C-Level leader must own.
Gemini 3 Robotics: Bridging the Gap Between Reasoning and Physical Motion
Reasoning and motion used to live in different worlds. Learn the two-brain robotics pattern: an embodied reasoning model that plans and coordinates, and a vision-language-action model that moves.
Zero-Knowledge Agents: Processing Private Data with Gemini 3's Encrypted Reasoning
When agents touch private data, you need two promises: the provider computes without seeing it, and you can verify the model really ran. Learn ZK proofs, FHE, TEEs, and the collaborative SLM/LLM split.
The "Long-Horizon" Task: Keeping Gemini 3 Focused Over Months-Long Projects
Long-horizon tasks outlast a single context window. Learn to beat context rot with execution-state memory, agent-managed context tools, file-centric state, and proactive memory intervention.
The "Continuous-Learning" Agent: Updating Gemini 3 Knowledge via Live Feeds
An LLMs knowledge freezes at training time. Learn the continuous-learning agent pattern: frozen base + live vector store, temporal scoring, EWC-guarded micro-adaptation, and indexes that learn from validated queries.
Building a Meta-Agent: The Gemini 3 Orchestrator of Orchestrators
A meta-agent is a higher-order agent that operates on other agents. Learn the orchestrator-of-orchestrators pattern: hierarchical planning, sub-agent split, lazy tool discovery, and Git-like execution traces.
Human-Agent Collaboration: Designing UIs for Gemini 3 "Co-Pilot" Modes
A copilot UI is not a chat UI with autonomy bolted on. Learn the seven agent UI patterns, autonomy as a design decision, approval gates that dont train users to click through, and the AG-UI/A2UI protocol stack.
Hyper-Personalized SLMs: Local Fine-Tuning of Gemini 3 Nano Models
A model that runs on-device still has to be trained somewhere. Learn to fine-tune Nano SLMs locally with LoRA, QLoRA, MeSP, and GradCut — without ever shipping user data to the cloud.
Wasm-Powered Agents: Running Secure Gemini 3 Nano Logic in the Browser
Ship an entire AI agent as a single HTML file. Learn the Wasm-powered agent pattern: Pyodide vs WebLLM, sandboxing agent-generated code in WASM kernels, and wiring MCP tools from a browser tab.
Multi-Modal RAG for Video: Using Gemini 3 to Build Searchable 4K Video Knowledge Bases
Transcription-only video search throws away the pixels. Learn to embed video natively with Gemini Embedding 2, chunk with overlap, truncate with Matryoshka, and return trimmed clips on a text match.
The "Browser-as-a-Tool" Pattern: How Gemini 3 Agents Navigate the Visual Web
Most valuable data lives behind a browser, not an API. Learn the browser-as-a-tool pattern: the three-layer architecture, DOM vs screenshot grounding, surface contracts, and sandboxing for Gemini 3 agents.
Agentic SEO: Preparing Content for Gemini 3's Multimodal Search Browsers
Search is becoming an AI operating system. Learn how to make your content discoverable, trustworthy, and actionable for Gemini 3 multimodal search agents.