3.1 The real production tools
You just built a working harness — durability, sandboxing, memory, routing, supervision, and human-in-the-loop — from scratch. The point was never to ship that code. The point was so that when you open the docs for a real framework, nothing is a black box. You’ll recognize every piece, because you built the toy version of it.
Here’s the map from what you built to what the industry ships.
Concept → production tool → when to reach for it
Section titled “Concept → production tool → when to reach for it”| What you built | Industry name | Real tools | Reach for it when… |
|---|---|---|---|
| Event log + checkpoint/resume (2.1) | Durable execution | Temporal, DBOS, Inngest, Restate | Your agent does real, irreversible work and must survive crashes without repeating it |
| Policy gate + isolated runner (2.2) | Sandboxing / code execution | e2b, Firecracker, Cloudflare Sandbox, Daytona | The model writes or runs code, or calls tools that could do damage |
| History / state / context split (2.3) | Context engineering / memory | Vector DBs (Pinecone, pgvector), LangMem, mem0 | Tasks run long enough that “send everything” gets slow, costly, or forgetful |
| Router + typed handoffs (2.4) | Orchestration / routing | LangGraph, Mastra, OpenAI Agents SDK, CrewAI | One agent is juggling too many tools or intents and picking wrong |
| Supervisor + parallel fan-out (2.5) | Multi-agent orchestration | LangGraph, Mastra, CrewAI, AutoGen | A task splits into independent sub-tasks, or you need resilience to partial failure |
| Suspend / resume for approval (2.6) | Human-in-the-loop / durable signals | Temporal signals, Inngest waitForEvent, LangGraph interrupts |
An action needs a person’s sign-off, or the workflow must wait on an external event |
Notice how often the same names recur — Temporal and LangGraph especially. That’s not coincidence: the two hardest problems are durability (surviving time and crashes) and orchestration (coordinating multiple steps and agents), and the big frameworks are organized around one or the other.
Two families, one split
Section titled “Two families, one split”Almost every tool above falls into one of two camps — and it’s the same split this whole guide is built on:
- Execution / durability (Temporal, DBOS, Inngest): they own how a workflow runs — checkpointing, retries, resuming, waiting. They don’t care that there’s an LLM inside.
- Agent orchestration (LangGraph, Mastra, CrewAI): they own how agents coordinate — routing, handoffs, sub-agents, shared state.
The most serious production setups use both: an orchestration framework for the agent logic, running on top of a durable-execution engine for the guarantees. Which is exactly the harness you built — the agent decides, the durable runtime executes.
How to read any agent framework now
Section titled “How to read any agent framework now”Open the docs for anything — LangGraph, Mastra, the OpenAI Agents SDK — and ask five questions. You now know what each one means and why it matters:
- What happens when the process crashes mid-run? (durability — 2.1)
- What can a tool do, and what stops it? (policy + sandbox — 2.2)
- What does it actually send the model each step? (context — 2.3)
- How does work get to the right agent? (routing/handoffs — 2.4)
- Can it run things in parallel and survive one failing? (supervision — 2.5)
- How does it wait for a human or an event? (suspend/resume — 2.6)
A framework’s real quality is in its answers to those six questions — not its demo.