LLM security meets architecture: defend against poisoning and design for model choice
Secure the AI data supply chain and keep models swappable—both are now table stakes.
Secure the AI data supply chain and keep models swappable—both are now table stakes.
Plan for hard LLM budgets and measure cost per accepted result, not per token—then build reliability guardrails around every call.
Muse Code’s persistent agents plus a replayable log make agent-driven dev more resilient and auditable—worth a controlled pilot.
Agentic coding is getting real guardrails: isolate-by-default sandboxes and policy-checked tool calls you can actually deploy.
Treat agent frameworks as plugins, not architecture—use graphs, logs, and traces to scale safely.
Web IQ makes external grounding easy; reliability still requires signals, loops, and tests.
Anchor core automations in deterministic logic and use AI only where it clearly helps with guardrails and fallbacks.