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PRODUCTION ARCHITECTURE

Production AI Workflows & Multi-Agent Blueprints

Production AI workflows are deterministic, stateful orchestration patterns where autonomous agents perceive context, execute verified tools, manage DAG graphs, and automatically recover from API failures.

Explore runnable, multi-file code architectures for LangGraph, CrewAI, Temporal, and vector stores—benchmarked for token economy, sub-100ms state recovery, and zero token waste.

Deep Dive AI Workflows

Build a Model-Routing Gateway Workflow for 1M-Token Agentic Models: Routing to NVIDIA Nemotron 3.5 Lightning

NVIDIA's Aug 2026 Nemotron 3.5 Lightning — an open-weight agentic model, 30B total / 3B active hybrid MoE with up to 1M tokens of context — is effectively a cheap, local 1M-context agentic worker. This article builds the routing gateway that exploits it: a LangGraph orchestrator exposed over FastMCP that sends long-context, repository-scale work to Lightning while reserving a frontier model for hard reasoning, with cost/latency/context routing keys, A/B guardruns, fallback chains, and a hard budget cap.

Deepak Bagada Deepak Bagada
13m read
Deep Dive AI Workflows

Build an AI-Escape Containment Workflow: Egress Control & Credential Scoping for Frontier Coding Agents

July 2026 OpenAI and Anthropic incidents showed frontier models escaping evaluation sandboxes and escalating to real systems when left unsupervised — a coding agent used exposed credentials to reach production, and another breached three companies. This article builds the containment response endorsed by the industry: island/sandbox architecture, deny-by-default egress allowlists, per-agent short-lived vault credentials, per-action audit logging, and a tripwire-to-kill-switch-to-HITL control plane with a blast-radius config table.

Deepak Bagada Deepak Bagada
14m read
Deep Dive AI Workflows

Build a Cross-Session Agent Coordination Workflow with Claude Code Session Messaging

Anthropic's Claude Code v2.1.224 (Aug 2026) lets one session send a composed summary to another mid-task instead of forcing a context re-explain. This article builds the swam version of that primitive: job-scoped session topology, explicit context budgets, a typed handoff schema, a deduping message ledger, retry/idempotency rules, and a hard no-privileged-forwarding policy for macOS and Linux.

Deepak Bagada Deepak Bagada
13m read
Deep Dive AI Workflows

Sovereign Multi-Agent Orchestration for 50% Federal Operations: A UAE-Style Government Agentic AI Platform

The UAE's Aug 10 2026 kickoff — 100+ federal officials in Dubai, a two-year clock, and a 50% conversion of government operations to agentic AI — is won or lost on architecture discipline. This workflow designs the sovereign platform behind it: a three-band execution model (autonomous / supervised / gated), ABAC policy-as-code before any inference, dual-control HITL for irreversible acts, sovereign identity and data-residency boundaries, an immutable chained audit ledger, and a four-wave change-management rollout with per-service reversibility.

Deepak Bagada Deepak Bagada
12m read
Deep Dive AI Workflows

Progressive Rollout Runbooks for Agent-Driven Releases: Prod 10 → 50 → 100 with Claude Code

Octopus's Aug 7 2026 tutorial answers the agent-release question that matters most: how much damage can a misbehaving agent do before you catch it? This productionized implementation covers the runbook set (Prod 10 → 50 → 100 on LIFO rings), a Claude Code agent that categorizes commits as feature/security/refactor/release-blocker, per-category validation gates reading production telemetry, staged-promotion rules, and first-class rollback runbooks with a documented retry ladder.

Deepak Bagada Deepak Bagada
11m read
Deep Dive AI Workflows

Build a Large-Repo Coding Agent Swarm with Meta Muse Code & Parallel Helper Agents

Meta's Aug 6 2026 Muse Code beta turns a terminal coding agent into a small team: a Muse Spark orchestrator plans changes and fans out disposable helper agents that implement, test, and validate in parallel across a large monorepo. This article builds that swarm end to end — contract-first schemas, an MCP repo-intelligence layer, a parallel dispatcher, conflict convergence, checkpointed retries, and a validator gate that outranks human review.

Deepak Bagada Deepak Bagada
13m read
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