The 1980s Solved Your Agent Orchestration Problem
Contract Net, blackboards, BDI, and coordination theory expose the design work hidden behind handoffs, shared state, and workflow graphs.
Blog
Technical insights on AI engineering, custom software development, and bringing ML to production.
On-Device LLMs on Android in 2026: ExecuTorch, llama.cpp, and MNN Compared
Native Android on-device LLMs without React Native. ExecuTorch JNI, llama.cpp-android, and MNN side by side — benchmarks, Kotlin integration patterns, and which framework to pick for your use case.
On-Device AI Inference Trends in 2026: What's Actually Shipping
Five trends making on-device AI the default in 2026: NPU stability on Snapdragon 8 Elite and Dimensity 9400, sub-1B LLMs at 12–15 tok/s, vision-camera pipelines, on-device RAG, and framework convergence. What's already in production.
Computer Vision in React Native: A Practical Guide with ExecuTorch v0.8.0
Classification, detection, segmentation, OCR, and vision-language models — all running on-device in your React Native app. A complete guide to CV with react-native-executorch v0.8.0.
Best On-Device LLMs for Android in 2026: React Native ExecuTorch Guide
Run local language models on Android in 2026 — benchmarks, model recommendations, and production-ready code examples using React Native ExecuTorch.
Real-Time AI Agents: Beyond Chatbots
AI agents are evolving from chatbots to real-time video systems. Technical requirements, use cases, and architecture for latency-sensitive AI agents.
How Agentic Engineering Eliminates the Build vs Buy Friction
Agentic engineering tools let teams prototype in hours, but vibe coding to production requires a new discipline: the Vibe-to-Production Maturity Model.
On-Device AI Inference in 2026: Sub-20ms on Android, Real Benchmarks, and When to Go Edge
Sub-20ms AI inference on a $400 Android — measured on 2025 chipsets. ExecuTorch vs ONNX Runtime benchmarks for real-time production deployments, plus a 5-factor decision matrix for when on-device beats cloud.
The True Cost of Custom SaaS Development in 2026
Custom SaaS costs in 2026: from $50k MVPs to $250k enterprise platforms, plus hidden SaaS sprawl costs and a build vs buy decision framework.
Want to work with us?
We help companies build production AI systems. Let's discuss your project.
Get in Touch