OpenCode 2.0: Background Service, Code Mode and What Breaks When You Upgrade

You are helping me turn one specific YouTube video into real, durable learning.

Source video:
- Title: OpenCode 2.0: Background Service, Code Mode and What Breaks When You Upgrade
- URL: https://www.youtube.com/watch?v=JqDsgEMPAlg
- Topic: Agentic Engineering
- My current learning frame: Take a hypothetical OpenCode 1.0 setup with an LSP, a plugin, and external-file access, then draft its 2.0 architecture and a migration checklist that preserves the intended safeguards.
- Why this matters: New playlist item from AI Stack Engineer; queued for transcript-backed review, topic mapping, and a practical learning artifact.

Transcript anchors from this exact video:
- 1:01 / Evidence 1: "day. A lot of that growth came after Anthropic blocked third-party tools from using Claude Pro and Mac subscriptions back in January. People wanted an agent that wasn't tied to one model company. Kilo even rebuilt its CLI..."
- 3:27 / Evidence 2: "The new one covers sessions, history, event streams, permissions, shell processes, snapshots, and more. There's a new package at open code {slash} client with plain JavaScript and effect versions. Scripts auto discover the local service, so a scheduled..."
- 5:33 / Evidence 3: "because the agent searches for the tools it needs instead of loading all of them up front. If you've connected five or six servers and watched half your context disappear before writing any code, that's the problem this..."
- 7:10 / Evidence 4: "it. Plugins are stable now and everything hot reloads. You can ask Open Code to write a plugin for itself mid-session and use it right away, no restart. The @OpenCode/SDK package is the same code that runs the..."
- 9:01 / Evidence 5: "expose LSP tools and won't show diagnostics. The docs say to use your lint, type check, or compiler commands instead. V1 also used to ask before touching files outside your project, and V2 allows it by default. To..."
- 10:38 / Evidence 6: "array format. Hacker News comments were split. One person said nearly all their bugs vanished after upgrading. Others moved to pie, a lighter agent. Someone running a local llama model noticed it kept generating after closing open code,..."

Video-aware target:
- Prompt lane: Agent harness
- Mechanism to extract: Identify what surrounding harness makes the model more useful than chat alone.
- Artifact to produce: A one-page agent harness map with tool boundaries, state ownership, and proof signals.
- Artifact must include: model role; tools; state/memory; permission boundary; verification proof

Your task:
1. Use the transcript anchors above as the primary source packet. If you add outside context, label it clearly as outside context and keep it secondary.
2. Create a source-check table with columns: timestamp, claim, transcript support, what the demo proves, confidence, and what still needs verification.
3. Extract the actual teachable mechanism from the video: Identify what surrounding harness makes the model more useful than chat alone. Do not invent claims that are not supported by the title, lesson frame, or transcript anchors.
4. Build a reusable learning artifact: A one-page agent harness map with tool boundaries, state ownership, and proof signals.
5. Include:
   - a plain-English definition of the core idea
   - a diagram or structured model using this sequence: User intent -> Model role -> Tool surface -> State and memory -> Verification loop -> Reusable operating rule
   - answers to these source questions: What does the video claim the agent can do? | What surrounding system makes that claim plausible? | What proof is shown instead of merely asserted?
   - 3 concrete examples that apply the video idea to real agentic work, such as a repo-editing harness; a local research assistant; a recurring refresh agent
   - 2 failure modes the video helps prevent, chosen from the transcript evidence and these likely risks: treating model choice as architecture; ignoring tool permissions; missing verification evidence
   - a checklist for the next real workflow, focused on: tool boundaries, state ownership, done signal, recovery path
   - one practical exercise with a clear done signal: Map one current coding workflow as a harness and mark the first missing proof signal.
6. Add a "learning transfer" section: what changes in my workflow tomorrow if I actually learned this?
7. Add a "source check" section that cites which transcript anchor supports each major takeaway.

Quality bar:
- Make this specific to "OpenCode 2.0: Background Service, Code Mode and What Breaks When You Upgrade", not a generic Agentic Engineering essay.
- Tie each harness element to a transcript anchor that names a tool, state boundary, permission, model behavior, or verification step.
- Prefer operational examples, failure modes, and reusable artifacts over broad definitions.
- Call out uncertainty instead of smoothing over weak evidence.
- Avoid these generic drifts: generic agent definitions; model leaderboard claims; tool list without operating boundaries.
- If evidence is weak or missing, stop and say what transcript segment or timestamp needs review instead of guessing.
- Finish with a concise artifact I could paste into my learning app.