| status | active | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| updated | 2026-11-03 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| section | Agents at Your Keyboard | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| level | applied | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| duration | 45 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| format | core-talk | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| decision | Where can I put AI help so decisive evidence and the right decision maker stay within reach? | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| references |
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The Question This Talk Answers: "How do I get AI help right where I’m working?"
Duration: 45 minutes | Audience: Developers and platform engineers working with repository, CI, and running-system evidence
Thesis: Bring intelligence to the work, and keep the worker within reach.
- Open the deck: 36 slides (25 teaching, 11 spine); estimated 40:00 talk plus 5:00 for questions. Press
Nfor speaker notes. - Speaker notes and handout: Complete talk track, proposed live checks, source evidence, boundaries, and recovery paths.
The native teaching source owns the talk. Product evidence was reviewed November 2, 2026; stable baseline v1.0.105. The distance-first narrative was approved November 3. Representative traces are scripts, not observed results.
Why use CLI here? It can minimize the distance between the person, the evidence, the process, and the next useful moment. This is a practitioner thesis, not a historical origin claim or a ranking of other surfaces.
Keep the developer’s request, Docker tool outputs, and next decision in one inspectable loop. Clarify the task, review a scoped plan, and use the listener and valid 5001:5000 mapping to choose a proposed HTTP probe. No successful repair is claimed.
Start Copilot on the authorized staging host so tools can reach decisive evidence. Inspect inference placement separately, compare a bounded log finding with its synthetic source, and choose cloud deliberately for repository work. Host-local tools do not imply host-local inference or zero data movement.
Let failed CI run copilot -p and return a proposed why beside the original red test. Save recurring staging investigation as a public-preview dynamic workflow: understand the process, describe and review its creation, confirm registration, then invoke it and inspect the report. Permissions and containment bound the actions close to the system.
Carry forward the right thing: a reusable procedure, delegated task, scheduled intent, checked context, reviewed guidance, recoverable edits, or continuing session. Experimental schedules require an active session. Original-host steering requires a running host and process; connected cloud continuation preserves different state. Verify identity, scope, files, and actual test evidence.
- Ask for two read-only checks beside a runtime task; inspect their outputs and choose the next probe.
- Analyze an approved synthetic source on its host; inspect the provider and compare the finding with source.
- Return one bounded CI failure explanation; compare
why.mdwith the log and keep the original failed test status.
- Continue a low-risk task; verify the session, retained scope, files, and actual next check. Confirm access and current billing before cloud work.
- Candidate task: Choose one distance in a real task; capabilities can close several distances.
- Decisive context: Identify the host, files, service state, and provider allowed to receive context.
- Delegation and authority: Name the permission decision maker and the human who accepts the result.
- Evidence: Define an artifact and a signal that makes you keep, adjust, or stop the pattern.
- Boundary: Stop when source evidence disagrees or access, data handling, or acceptance ownership is unclear. Preserve the artifact and re-scope with the owner.
- Walkthrough and proposed checks: Safe rehearsal paths for planning, CI, model placement, permissions, containment, workflows, and both continuity paths.
- Illustrative workflow extension: The kind of
extension.mjsCopilot writes for the staging investigation, using the API in the guidance bundled with CLI v1.0.105; syntax-checked and stub-SDK tested, not a recorded run. and fixture inputs: Dependency-free Node.js fixture checks; a Copilot extension adapter requires separate authoring and audit. - Teaching source: Slide data, full notes, source map, and timing.
- Approved recipe: Structural rationale and actual per-slide plan.
- Copilot Web: GitHub-hosted collaboration and context.
- Copilot CLI + Azure MCP: CLI workflows with Azure evidence and tools.
- Copilot Configuration Primitives: Stable instructions and reusable context.
- Enterprise Patterns: Plugin packaging and layered distribution across enterprise, team, and repository.