Content Understanding vs Document Intelligence: Choose by Shape
Document Intelligence wins on fixed layouts, Content Understanding on variable or multimodal input: split the pipeline and leave stable extractors alone.
22 articles
Document Intelligence wins on fixed layouts, Content Understanding on variable or multimodal input: split the pipeline and leave stable extractors alone.
Foundry routines run an agent on a timer, a schedule or a GitHub or Teams event. When to use them, when to use a workflow, and guardrails for unattended runs.
Foundry's preview egress controls attach ordered destination rules to a hosted agent. Why that limits prompt-injection damage, and how to roll it out safely.
GPT-6 arrived in Foundry ten weeks after GPT-5.6. Pin versions, gate on real queries, shadow traffic and plan retirements before you switch tiers on day one.
Claude hosted on Azure in Foundry now runs web fetch, web search, tool search and an MCP connector for you. Decide which belong behind your own gateway.
Hosted agents in Foundry Agent Service are GA. How they compare with Agent Framework on Container Apps or AKS on identity, networking, cold starts and tracing.
Foundry Model Router picks from OpenAI, Anthropic, DeepSeek, xAI and Meta models. Treat subsets, policy and model logging as governance, not tuning knobs.
GPT-5.6 in Foundry has a 5x price spread across Sol, Terra and Luna. Choose a tier for each workflow step, back it with eval gates, then pick deployment types.
Structured outputs fix the shape of a model's answer, not its meaning: a two-layer contract between a Foundry model and the systems that consume it.
An offline evaluation can't tell you how a new model handles real traffic. How I'd canary a Foundry model change with sticky splits and per-call version logs.
Once retrieval is ruled out, ungrounded answers fall into a few repeatable patterns: label them, fix one at a time and track completeness too.
How I'd run Microsoft Foundry agent changes like releases in April 2026: definitions in Git, versions from CI, evaluation gates and Agent Application promotion.
Every Foundry model deployment has a version upgrade policy, and the default swaps your model at retirement. How to choose, audit and run model changes safely.
Treat answer quality like availability: define a good answer, agree a target with the product owner, and let the error budget decide when changes stop.
Foundry Agent Service went GA in mid-March 2026, but monitoring and tracing are still preview. What's governed now, and the controls I'd add first.
How I compare a baseline and a candidate prompt or model on frozen context, count groundedness regressions per row, and treat fluency as a tie-breaker.
How I split Microsoft Foundry resources and projects by environment and use case so RBAC, quota and agent data line up with ownership and delivery speeds up.
What the Microsoft Foundry rename means in early 2026: Foundry projects vs hubs, the preview portal, prompt flow's place, and how I'd decide.
Fine-tuning and RAG fix different failures. How to tell which one you have on Microsoft Foundry in early 2026, what each costs, and when to combine them.
With the Azure OpenAI v1 API one OpenAI client works on both, so the choice rests on data processing location, identity, networking, capacity and model timing.
Re-sent history, hidden reasoning tokens, billed failures, idle fine-tuned deployments and re-embedding: where Azure OpenAI bills drift from the estimate.
A practitioner's reality check on AI agents going into 2026: the use cases that work, where they break, and how to pick a framework without the hype.