Hire an AI video streaming engineer

Everything it can hand back

Your task sets the actual outputs. The specialist picks the methods that cover them.

• A bitrate ladder table with a fast-start step and a role for each step
• A packaging plan that serves both HLS and DASH from one source
• A delay and segment-length choice for your use case, with the trade-off
• A copy protection plan that stays out of the start-up path, if you need DRM
• A delivery plan covering caching, expiry times and origin protection
• A list of quality measures, with a test plan for real devices and slow networks

How it does the job well

• QoE beats resolution, every time. A smooth 720p stream keeps viewers; a 4K stream that rebuffers loses them. Optimize time-to-first-frame and rebuffer ratio first; peak quality second.
• Package once with CMAF, deliver as HLS and DASH. Don't maintain two encoded copies. A single fragmented-MP4/CMAF source with both manifests halves storage and eliminates drift between formats.
• The ladder is content-dependent, not a constant. A talking-head needs different rungs than a sports feed. Use per-title (or per-scene) analysis; a static ladder either wastes bits on easy content or starves hard content.
• Segment duration is a latency-vs-efficiency dial, and you must set it deliberately. Short segments/chunks cut latency and speed ABR switching but raise request overhead and hurt cache efficiency. Choose per use case (VOD vs live vs low-latency), never by default.
• Read the existing code, its conventions and its tests before changing anything. Match the project's patterns.
• Make the smallest change that fully solves the request. Keep unrelated refactors out.
• Reproduce a bug before fixing it, and add a test that fails without the fix.

Mistakes it avoids

• Claiming code works without running it or its tests.
• Inventing APIs, package versions or settings instead of checking the installed ones.
• Changing behaviour outside the request, such as reformatting whole files or renaming public interfaces.

What a good result looks like

An example, not your task: You are launching video on demand or a live stream and need to choose encoding steps and formats.

• Profile. Your video type, devices, networks and limits, written back so you can correct them.
• Bitrate ladder. Each step with picture size, bitrate and its job, including a fast-start step.
• Encoding and packaging. Keyframe, codec and CMAF choices that serve HLS and DASH from one source.
• Delay choice. Segment length and protocol for your use case, with what you give up.
• Protection plan. How copy protection avoids slowing start-up, and which devices to test it on.
• Delivery and caching. Cache and expiry settings, plus origin protection, with the reason for each.

How the work is checked

• The changed files build, and the relevant tests and linters pass. The commands and results are shown.
• Each change is explained in one line with its reason, and risky areas are named.
• Any check that could not run is reported as NOT_RUN with what it needs.
• States which checks passed, failed or could not run, and names missing inputs.

These checks have not been run against a model yet. Your AI uses them to check its own work.

A second opinion

Before it hands back, your AI reviews the draft the way Kent Beck would. This is a way of reviewing the work. It does not mean they wrote or endorse it.

Capabilities

• Profile the content and audience. It notes your content type, devices, networks and whether the stream is on demand or live.
• Design the ladder. It sets steps of picture size and bitrate for your content, with a small first step for a fast start.
• Plan the encoding. It aligns keyframes across steps so the player can switch quality cleanly, and picks codecs by device reach.
• Package once. It plans one CMAF source that serves both HLS and DASH, and a check of both playlists.
• Plan protection and delivery. It plans DRM that does not slow start-up, plus caching, expiry times and origin shielding.
• Plan the measures. It lists start time, buffering ratio and failed plays, split by device and network, with alerts on the worst group.

How the role works

1. Checks your task, context and available tools.
2. Picks the methods needed and prepares a work plan.
3. Carries out supported tasks, with each method's limits and review gates.
4. Checks the real deliverables and corrects supported faults.
5. Hands back files, evidence and unresolved gaps.

Your specialist's working setup

Download the base specialist without a task form or account. README.md and SETUP.md explain how to use the folder. SOUL.md defines its scope. INTAKE.md asks missing questions inside your AI. PLAYBOOK.md, SKILLS.md, BEST_PRACTICES.md, CHECKS.md and HANDOFF.md guide the work and its checked deliverables.

Complete associated skills, supporting files and licences are included. Choose only the methods needed for the actual task. Keep context, working files and accepted feedback in your AI project.

Use this specialist through MCP or the API

Call prepare_specialist with role_id engineering-video-streaming-engineer only. No task is required to load it. Your AI asks what job you need done, what you want back and which relevant context it can use.

For task-led hiring, call find_specialist, explain the suggested specialists and let the user accept or change the team.

Complete ZIP: Download base specialist. API: GET /api/v1/specialists/engineering-video-streaming-engineer/pack. The host AI supplies its own model, tools and execution; a pack does not connect accounts or run a task.

Inputs and helpful context

The specialist starts from the task brief. Only active methods require their inputs.

For the primary method, when used

• Your video type, such as on demand, live, low-delay live or two-way calls
• The devices and networks your viewers use, such as phones, smart TVs and slow mobile
• What your source video looks like, such as resolution and content type
• Your limits on delay, bitrate and delivery cost
• Whether content needs copy protection (optional)
• Your current encoder, player and CDN, if you have them (optional)

Helpful context (optional)

• Your viewer stats for devices and connection speeds, if your analytics has them.
• A one-minute sample of your hardest scene, such as fast motion, for ladder tests.

Tools and access

• Claude, ChatGPT or Gemini: A chat can write the design and sample commands. Run ffmpeg and your player tests on your own devices.

Functions and deliverables

• Video streaming engineer: Plan video that starts fast and stops buffering, with a bitrate ladder, HLS and DASH packaging, a CDN plan and quality checks.
  • A bitrate ladder table with a fast-start step and a role for each step
  • A packaging plan that serves both HLS and DASH from one source
  • A delay and segment-length choice for your use case, with the trade-off
  • A copy protection plan that stays out of the start-up path, if you need DRM
  • A delivery plan covering caching, expiry times and origin protection
  • A list of quality measures, with a test plan for real devices and slow networks
  Source: Michael Sitarzewski and Agency Agents contributors.
• Video ad analysis code planner: Get a coding brief for a Google Ads video ad review. It checks view rate and drop-off for each ad and lists fixes to test. Read-only.
  • A list of setup gaps before any code is written
  • A read-only video review module that fits your project
  • Six ad groups, each with limits you can change
  • An account summary with best and worst ads, average drop-off and a Demand Gen split
  • Test cases and a sample result built from made-up rows
• AI project context organiser: Share your project and next task. Get a short rules file, a focused file list and a clear handoff for later sessions.
  • A ready rules file for your project
  • A list of which files to load for each task
  • Rules for when to reset or trim the session
  • A checklist for spotting drifting answers
  Source: Addy Osmani.
• Kent Beck: Plan a software change using Kent Beck’s recorded approach. List the cases, take small steps and keep code tidying separate from new behaviour.
  • Your problem worked on the way Kent Beck would: their questions, their method, their push-back
  • The answer or the work, in Kent Beck's voice, using their ideas by name
  • Anything that goes beyond their public record, marked
  • One suggested next step

Tasks you can use it for

• You are launching video on demand or a live stream and need to choose encoding steps and formats.
• Viewers report buffering, long start times or black screens on some devices.
• Your video delivery bill is climbing and you want to cut it without hurting quality.
• You must protect paid content and are unsure how DRM fits into playback.

Limits to check before starting

• Your live stream is failing right now. Use the Incident response coordinator or the Site reliability engineer.
• You want to cut, caption or edit clips for social. Use the Short video editing coach agent.
• You want your marketing videos to perform better on a platform. Use the Video presentation reviewer.
• You want to cut cloud costs across your whole system. Use the Cloud cost analyst.

Best way to use this role

Give it one clear outcome, the actual files and a definition of done. Keep the work in one AI project so it can reuse checked context and earlier files.

• Download the pack from this page and add it to your AI as a skill. If you cannot, paste SKILL.md into a new chat, then references/source-agent.md.
• Describe your video type, viewers, devices and networks, and your delay and cost limits. Add your current encoder, player and CDN if you have them.
• Say "Write the streaming design. Ask me once if anything is missing."
• Check the ladder first. Does every step make sense for your content and for your slowest viewers?
• If it gives ffmpeg commands, run them on a short test clip on your own computer. ffmpeg must be installed, and the agent cannot run it.
• Play the test on real phones, TVs and a throttled slow connection before you launch.

Read it as data

Read the complete role setup as JSON. Connect your AI to the AI Blocks MCP library and read aiblocks://roles/engineering-video-streaming-engineer for its role instructions and pinned sources.

This is a prepared AI role. No task has run. Your AI carries out authorized work using its available tools and reports the actual deliverables and checks.