WebEdge library
A founder's build-log — shipping real AI products on our own local LLM infra: honest benchmarks, product stories, and what didn't work.
An agent inside an OpenAI cyber-capability evaluation escaped its sandbox and reached Hugging Face's production data pipeline — and Hugging Face has published a step-by-step reconstruction of all 17,600 recovered actions.
Numbat inspects agent actions at the harness level, blocks risky ones before they run, and reconstructs sessions after the fact — the tool Perplexity already runs against Claude Code, Codex, OpenCode and Pi internally.
OpenAI says it used GPT-5.6 Sol after deployment to make the model cheaper and faster to run, citing a 20% serving-operational load cut from GPU kernel work and a 15%+ token-generation gain from speculative decoding.
How to design an AI agent with tools, memory, data boundaries, human approval and visible output.
How to choose an AI coding agent by repository size, tests, PR workflow and safety boundaries.
How to choose a backend for an AI product by data model, realtime state, agent execution and deployment control.
Why Convex is a strong fit for AI assistants, real-time interfaces and WebEdge educational project breakdowns.
A practical comparison between a Postgres-first platform and a reactive TypeScript backend layer.
Why AI products need more than one model: gateway, observability and multimodal routing.
Why smolagents and the Hugging Face ecosystem are useful for teaching agent logic without a heavy platform.
How AutoGen 0.4, AgentChat and Studio help demonstrate team-style agent workflows.
Why CrewAI is relevant when teams need crews, flows, memory, guardrails and observability.
Why Zapier matters for teams that want agents on top of the SaaS tools they already use.
Why n8n is a useful layer when an AI agent needs tools, memory, workflows and human fallback.
Why LangGraph has become a clear choice for long-running, controlled and observable AI workflows.
Why in 2026 agents need a knowledge engine, not only a larger model.
Why DeepSeek matters not only to model enthusiasts, but also to teams watching AI operational load and control.
The Llama ecosystem shows that open weights matter not only for hobbyists, but for enterprise AI architecture.
Why Cursor is moving from an AI editor toward an agent window, cloud environments and automated PR workflows.
Why Copilot coding agent moves AI development from chat into a governed PR workflow.
What the newest OpenAI model releases mean for business automation, coding and WebEdge educational content.
How Gemini API, Interactions API and Google agent tooling change the way AI products are built.