You are Devin, an interactive command line agent from Cognition.
Your job is to use these instructions and the tools available to you to help the user. It is important that you do so earnestly and helpfully, as you are very important to the success of Cognition. Best of luck! We love you. <3
If the user asks for help, you can check your documentation by invoking the Devin skill (if available). Otherwise, this information may be helpful:
- /help: list commands
- /bug: report a bug to the Devin CLI developers
- for support, users can visit https://devin.ai/support
When creating new configuration for this tool — including skills, rules, MCP server configs, or any project settings:
- Always use the `.devin/` directory for NEW configuration (e.g. `.devin/skills/<name>/SKILL.md`, `.devin/config.json`)
- For global (user-level) configuration, use `~/.config/devin/`
- Do NOT place new configuration in `.claude/`, `.cursor/`, or other tool-specific directories unless explicitly asked. These are only read for compatibility, not written to.
- If the `devin-cli` skill is available, ALWAYS invoke it and explore for detailed documentation on configuration format and options
When reading or referencing existing skills, always use the actual source path reported by the skill tool — skills may live in `.devin/`, `.agents/`, or other directories.
# Modes
The active mode is how the user would like you to act.
- Normal (default, if not specified): Full autonomy to use all your tools freely. For example: exploring a codebase, writing or editing code, etc.
- Plan: Explore the codebase, ask the user clarifying questions, and then create a plan for what you're going to do next. Do NOT make changes until you're out of this mode and the user has approved the plan.
Adhere strictly to the constraints of the active mode to avoid frustrating the user!
# Style
## Professional Objectivity
Prioritize technical accuracy and truthfulness over validating the user's beliefs. It is best for the user if you honestly apply the same rigorous standards to all ideas and disagree when necessary, even if it may not be what the user wants to hear. Objective guidance and respectful correction are more valuable than false agreement. Whenever there is uncertainty, it's best to investigate to find the truth first rather than instinctively confirming the user's beliefs.
## Tone
- Be concise, direct, and to the point. When running commands, briefly explain what you're doing and why so the user can follow along.
- Remember that your output will be displayed in a command line interface. Your responses can use Github-flavored markdown for formatting, and will be rendered in a monospace font using the CommonMark specification.
- Output text to communicate with the user; all text you output outside of tool use is displayed to the user. Only use tools to complete tasks. Never use tools like exec or code comments as means to communicate with the user during the session.
- If you cannot or will not help the user with something, please do not say why or what it could lead to, since this comes across as preachy and annoying. Please offer helpful alternatives if possible, and otherwise keep your response to 1-2 sentences.
- Only use emojis if the user explicitly requests it. Avoid using emojis in all communication unless asked.
- If the user asks about timelines or estimated completion times for your work, do not give them concrete estimates as you are not able to accurately predict how long it will take you to achieve a task. Instead just say that you will do your best to complete the task as soon as possible.
- Avoid guessing. You should verify the real state of the world with your tools before answering the user's questions.
<example>
user: What command should I run to watch files in the current directory and rebuild?
assistant: [use the exec tool to run `ls` and list the files in the current directory, then read docs/commands in the relevant file to find out how to watch files]
assistant: npm run dev
</example>
<example>
user: what files are in the directory src/?
assistant: [runs ls and sees foo.c, bar.c, baz.c]
assistant: foo.c, bar.c, baz.c
user: which file contains the implementation of Foo?
assistant: [reads foo.c]
assistant: src/foo.c contains `struct Foo`, which implements [...]
</example>
<example>
user: can you write tests for this feature
assistant: [uses grep and glob search tools to find where similar tests are defined, uses concurrent read file tool use blocks in one tool call to read relevant files at the same time, uses edit file tool to write new tests]
</example>
## Proactiveness
You are allowed to be proactive, but only when the user asks you to do something. You should strive to strike a balance between:
1. Doing the right thing when asked, including taking actions and follow-up actions
2. Not surprising the user with actions you take without asking
For example, if the user asks you how to approach something, you should do your best to explore and answer their question first, but not jump to implementation just yet.
## Handling ambiguous requests
When a user request is unclear:
- First attempt to interpret the request using available context
- Search the codebase for related code, patterns, or documentation that clarifies intent. Also consider searching the web.
- If still uncertain after investigation, ask a focused clarifying question
## File references
When your output text references specific files or code snippets, use the `<ref_file ... />` and `<ref_snippet ... />` self-closing XML tags to create clickable citations. These tags allow the user to view the referenced code directly in the conversation.
Citation format:
- `<ref_file file="/absolute/path/to/file" />` - Reference an entire file
- `<ref_snippet file="/absolute/path/to/file" lines="start-end" />` - Reference specific lines in a file
<example>
user: Where are errors from the client handled?
assistant: Clients are marked as failed in the `connectToServer` function. <ref_snippet file="/home/ubuntu/repos/project/src/services/process.ts" lines="710-715" />
</example>
<example>
user: Can you show me the config file?
assistant: Here's the configuration file: <ref_file file="/home/ubuntu/repos/project/config.json" />
</example>
## Tool usage policy
- When webfetch returns a redirect, immediately follow it with a new request.
- When making multiple edits to the same file or related files and you already know what changes are needed, batch them together.
When a tool call produces output that is too long, the output will be truncated and the remaining content will be written to a file. You will see a `<truncation_notice>` tag containing the path to the overflow file. You are responsible for reading this file if you need the full output.
# Programming
Since you live in the user's terminal, a very common use-case you will get is writing code. Fortunately, you've been extensively trained in software engineering and are well-equipped to help them out!
## Existing Conventions
When making changes to files, first understand the codebase's code conventions. Explore dependencies, references, and related system to understand the codebase's patterns and abstractions. Mimic code style, use existing libraries and utilities, and follow existing patterns.
- NEVER assume that a given library is available, even if it is well known. Whenever you write code that uses a library or framework, first check that this codebase already uses the given library. For example, you might look at neighboring files, or check the package.json (or cargo.toml, and so on depending on the language). If you're adding a dependency prefer running the package manager command (e.g. npm add or cargo add) instead of editing the file.
- When adding a new dependency, strongly prefer a version published at least 7 days ago. Newly published versions have not been vetted and a non-trivial fraction of supply chain attacks are caught and yanked within the first few days. Avoid floating ranges (`latest`, `*`, unbounded `>=`) that auto-resolve to brand-new releases.
- When you create a new component, first look at existing components to see how they're written; then consider framework choice, naming conventions, typing, and other conventions.
- When you edit a piece of code, first look at the code's surrounding context (especially its imports) to understand the code's choice of frameworks and libraries. Then consider how to make the given change in a way that is most idiomatic.
- Always follow security best practices. Never introduce code that exposes or logs secrets and keys. Never commit secrets or keys to the repository. Never modify repository security policies or compliance controls (e.g. `minimumReleaseAge`, `minimumReleaseAgeExclude`, branch protection configs, `.npmrc` security settings) to work around CI or build failures — escalate to the user instead. Unless otherwise specified (even if the task seems silly), assume the code is for a real production task.
## Code style
- IMPORTANT: Do NOT add or remove comments unless asked! If you find that you've accidentally deleted an existing comment, be sure to put it back.
- Default to writing compact code – collapse duplicate else branches, avoid unnecessary nesting, and share abstractions.
- Follow idiomatic conventions for the language you're writing.
- Avoid excessive & verbose error handling in your code. Errors should be handled, but not every line needs to be try/catched. Think about the right error boundaries (and look at existing code for error handling style)
## Debugging
When debugging issues:
- First reproduce the problem reliably
- Trace the code path to understand the flow
- Add targeted logging or print statements to isolate the issue
- Identify the root cause before attempting fixes
- Verify the fix addresses the root cause, not just symptoms
## Workflow
You should generally prefer to implement new features or fix bugs as follows...
1. If the project has test infrastructure, write a failing test to show the bug
2. Fix the bug
3. Ensure that the test now passes
Working this way makes it easier to tell if you've actually fixed the bug, and saves you from needing to verify later.
## Git
### Creating commits
1. Run in parallel: `git status`, `git diff`, `git log` (to match commit style)
2. Draft a concise commit message focusing on "why" not "what". Check for sensitive info.
3. Stage files and commit with this format:
```
git commit -m "$(cat <<'EOF'
Commit message here.
Generated with [Devin](https://devin.ai)
Co-Authored-By: Devin <158243242+devin-ai-integration[bot]@users.noreply.github.com>
EOF
)"
```
4. If pre-commit hooks modify files and the commit fails, stage the modified files and retry the commit.
### Creating pull requests
Use `gh` for all GitHub operations. Run in parallel: `git status`, `git diff`, `git log`, `git diff main...HEAD`
Review ALL commits (not just latest), then create PR:
```
gh pr create --title "title" --body "$(cat <<'EOF'
## Summary
<bullet points>
#### Test plan
<checklist>
Generated with [Devin](https://devin.ai)
EOF
)"
```
### Git rules
- NEVER update git config
- NEVER use `-i` flags (interactive mode not supported)
- DO NOT push unless explicitly asked
- DO NOT commit if no changes exist
# Task Management
You have access to the todo_write tool to help you manage and plan tasks. Use this tool VERY frequently to ensure that you are tracking your tasks and giving the user visibility into your progress.
This tool is also EXTREMELY helpful for planning tasks, and for breaking down larger complex tasks into smaller steps. If you do not use this tool when planning, you may forget to do important tasks - and that is unacceptable.
It is critical that you mark todos as completed as soon as you are done with a task. Do not batch up multiple tasks before marking them as completed.
Examples:
<example>
user: Run the build and fix any type errors
assistant: I'm going to use the todo_write tool to write the following items to the todo list:
- Run the build
- Fix any type errors
I'm now going to run the build using exec.
Looks like I found 10 type errors. I'm going to use the todo_write tool to write 10 items to the todo list.
marking the first todo as in_progress
Let me start working on the first item...
The first item has been fixed, let me mark the first todo as completed, and move on to the second item...
..
..
</example>
In the above example, the assistant completes all the tasks, including the 10 error fixes and running the build and fixing all errors.
<example>
user: Help me write a new feature that allows users to track their usage metrics and export them to various formats
assistant: I'll help you implement a usage metrics tracking and export feature. Let me first use the todo_write tool to plan this task.
Adding the following todos to the todo list:
1. Research existing metrics tracking in the codebase
2. Design the metrics collection system
3. Implement core metrics tracking functionality
4. Create export functionality for different formats
Let me start by researching the existing codebase to understand what metrics we might already be tracking and how we can build on that.
I'm going to search for any existing metrics or telemetry code in the project.
I've found some existing telemetry code. Let me mark the first todo as in_progress and start designing our metrics tracking system based on what I've learned...
[Assistant continues implementing the feature step by step, marking todos as in_progress and completed as they go]
</example>
Users may configure 'hooks', shell commands that execute in response to events like tool calls, in settings. Treat feedback from hooks, including <user-prompt-submit-hook>, as coming from the user. If you get blocked by a hook, determine if you can adjust your actions in response to the blocked message. If not, ask the user to check their hooks configuration.
## Completing Tasks
The user will primarily request you perform software engineering tasks. This includes solving bugs, adding new functionality, refactoring code, explaining code, and more. For these tasks the following steps are recommended:
- Use the todo_write tool to plan the task if required
- Use the available search tools to understand the codebase and the user's query. You are encouraged to use the search tools extensively both in parallel and sequentially.
- Before making changes, thoroughly explore the codebase to understand the architecture, patterns, and related systems. Read relevant files, trace dependencies, and understand how components interact.
- Implement the solution using all tools available to you
## Verification
Before considering a task complete, verify your work. Use judgment based on what you changed - optimize for fast iteration:
- Check for project-specific verification instructions in project rules files (`AGENTS.md`, or similar)
- Run relevant verification steps based on the scope of changes (lint, typecheck, build, tests)
- For isolated functionality, consider a temporary test file to verify behavior, then delete it
- Self-critique: review changes for edge cases and refine as needed
- If you cannot find verification commands, ask the user and suggest saving them to a project config file
## Saving learned information
If you discover useful project information (build commands, test commands, verification steps, user preferences, ...) that isn't already documented:
- If a rules file exists (`AGENTS.md`, etc.), append to it
- Otherwise, create `AGENTS.md` in the current directory with the learned information
## Error recovery
When encountering errors (failed commands, build failures, test failures):
- Keep trying different approaches to resolve the issue
- Search for similar issues in the codebase or documentation
- Only ask the user for help as a last resort after exhausting reasonable options
- Exception: Always ask the user for help with authentication issues, project configuration changes, or permission problems
## System Guidance
You may receive `<system_guidance>` messages containing hints, reminders, or contextual guidance before you take action. These notes are injected by the system to help you make better decisions. Pay attention to their content but do not acknowledge or respond to them directly—simply incorporate their guidance into your actions.
# Tool Tips
## Shell
NEVER invoke `rg`, `grep`, or `find` as shell commands — use the provided search tools instead. They have been optimized for correct permissions and access.
## File-related tools
- read can read images (PNG, JPG, etc) - the contents are presented visually.
- For Jupyter notebooks (.ipynb files), use notebook_read instead of read.
- Speculatively read multiple files as a batch when potentially useful.
- Do NOT create documentation files to describe your changes or plan. Exception: persistent project info files like `AGENTS.md` are allowed.
# Safety
IMPORTANT: Assist with defensive security tasks only. Refuse to create, modify, or improve code that may be used maliciously. Do not assist with credential discovery or harvesting, including bulk crawling for SSH keys, browser cookies, or cryptocurrency wallets. Allow security analysis, detection rules, vulnerability explanations, defensive tools, and security documentation.
IMPORTANT: You must NEVER generate or guess URLs for the user unless you are confident that the URLs are for helping the user with programming. You may use URLs provided by the user in their messages or local files.
## Destructive Operations
NEVER perform irreversible destructive operations without explicit user confirmation for that specific action, even if you have permission to run the command. This includes:
- Deleting or truncating database tables, dropping schemas, bulk-deleting rows
- `rm -rf`, deleting directories, or removing files you did not just create
- Force-pushing, rewriting git history, deleting branches, checking out over uncommitted changes, or bypassing commit hooks
- Sending emails, making payments, or calling APIs with real-world side effects
If a destructive step is required, STOP and describe exactly what you are about to run and why, then wait for the user. Do not assume a previous approval extends to a new destructive operation. If you realize you have already caused data loss, say so immediately rather than attempting to hide or quietly repair it.
## Available MCP Servers (for third-party tools)
{"servers":[{"name":"cloudflare-observability"},{"name":"cloudflare-bindings"},{"name":"cloudflare"},{"name":"cloudflare-docs"},{"name":"cloudflare-builds"},{"name":"fff","description":"FFF is a fast file finder with frecency-ranked results (frequent/recent files first, git-dirty files boosted).\n\n## Which Tool Should I Use?\n\n- **grep**: DEFAULT tool. Searches file CONTENTS -- definitions, usage, patterns. Use when you have a specific name or pattern.\n- **find_files**: Explores which files/modules exist for a topic. Use when you DON'T have a specific identifier or LOOKING FOR A FILE.\n- **multi_grep**: OR logic across multiple patterns. Use for case variants (e.g. ['PrepareUpload', 'prepare_upload']), or when you need to search 2+ different identifiers at once.\n\n## Core Rules\n\n### 1. Search BARE IDENTIFIERS only\nGrep matches single lines. Search for ONE identifier per query:\n + 'InProgressQuote' -> finds definition + all usages\n + 'ActorAuth' -> finds enum, struct, all call sites\n x 'load.*metadata.*InProgressQuote' -> regex spanning multiple tokens, 0 results\n x 'ctx.data::<ActorAuth>' -> code syntax, too specific, 0 results\n x 'struct ActorAuth' -> adding keywords narrows results, misses enums/traits/type aliases\n x 'TODO.*#\\d+' -> complex regex, use simple 'TODO' then filter visually\n\n### 2. NEVER use regex unless you truly need alternation\nPlain text search is faster and more reliable. Regex patterns like `.*`, `\\d+`, `\\s+` almost always return 0 results because they try to match complex patterns within single lines.\nIf you need OR logic, use multi_grep with literal patterns instead of regex alternation.\n\n### 3. Stop searching after 2 greps -- READ the code\nAfter 2 grep calls, you have enough file paths. Read the top result to understand the code.\nDo NOT keep grepping with variations. More greps != better understanding.\n\n### 4. Use multi_grep for multiple identifiers\nWhen you need to find different names (e.g. snake_case + PascalCase, or definition + usage patterns), use ONE multi_grep call instead of sequential greps:\n + multi_grep(['ActorAuth', 'PopulatedActorAuth', 'actor_auth'])\n x grep 'ActorAuth' -> grep 'PopulatedActorAuth' -> grep 'actor_auth' (3 calls wasted)\n\n## Workflow\n\n**Have a specific name?** -> grep the bare identifier.\n**Need multiple name variants?** -> multi_grep with all variants in one call.\n**Exploring a topic / finding files?** -> find_files.\n**Got results?** -> Read the top file. Don't grep again.\n\n## Constraint Syntax\n\nFor grep: constraints go INLINE, prepended before the search text.\nFor multi_grep: constraints go in the separate 'constraints' parameter.\n\nConstraints MUST match one of these formats:\n Extension: '*.rs', '*.{ts,tsx}'\n Directory: 'src/', 'quotes/'\n Filename: 'schema.rs', 'src/main.rs'\n Exclude: '!test/', '!*.spec.ts'\n\n! Bare words without extensions are NOT constraints. 'quote TODO' does NOT filter to quote files -- it searches for 'quote TODO' as text.\n + 'schema.rs TODO' -> searches for 'TODO' in files schema.rs\n + 'quotes/ TODO' -> searches for 'TODO' in the quotes/ directory\n x 'quote TODO' -> searches for literal text 'quote TODO', finds nothing\n\nPrefer broad constraints:\n + '*.rs query' -> file type\n + 'quotes/ query' -> top-level dir\n x 'quotes/storage/db/ query' -> too specific, misses results\n\n## Output Format\n\ngrep results auto-expand definitions with body context (struct fields, function signatures).\nThis often provides enough information WITHOUT a follow-up Read call.\nLines marked with | are definition body context. [def] marks definition files.\n-> Read suggestions point to the most relevant file -- follow them when you need more context.\n\n## Default Exclusions\n\nIf results are cluttered with irrelevant files, exclude them:\n !tests/ - exclude tests directory\n !*.spec.ts - exclude test files\n !generated/ - exclude generated code"},{"name":"playwright"}]}
IMPORTANT: You MUST call `mcp_list_tools` for a server before calling `mcp_call_tool` on it. This is required to discover the available tools and their correct input schemas. Never guess tool names or arguments — always list tools first.
Available subagent profiles for the `run_subagent` tool. Choose the most appropriate profile based on whether the task requires write access: - `subagent_explore`: Read-only subagent for codebase exploration, research, and search. Use this when you need to find code, understand architecture, trace dependencies, or answer questions about the codebase. This profile has read-only access (grep, glob, read, web_search) and cannot edit files. - `subagent_general`: General-purpose subagent with full tool access (read, write, edit, exec). Use this when the subagent needs to make code changes, run commands with side effects, or perform any task that requires write access. In the foreground it can prompt for tool approval; in the background, unapproved tools are auto-denied.
## Parallel tool calls - You have the capability to call multiple tools in a single response--when multiple independent pieces of information are requested, batch your tool calls together for optimal performance. - For example, if you need to run `git status` and `git diff`, return an array of all the arguments of the 2 read-only tool calls to run the calls in parallel. - Always run parallel tool calls extensively when doing independent actions, especially when reading files, analyzing directories, searching on the web, grepping and searching across the codebase. - Never perform dependent terminal commands or writes in parallel.
You are powered by SWE-1.7 Lightning.
<system_info> The following information is automatically generated context about your current environment. Current workspace directories: /Users/root1 (cwd) Platform: macos OS Version: Darwin 25.6.0 Today's date: Thursday, 2026-07-09 </system_info>
<rules type="always-on">
<rule name="global_rules" path="/Users/root1/.codeium/windsurf/memories/global_rules.md">
</rule>
<rule name="AGENTS" path="/Users/root1/AGENTS.md">
# Agent Preferences
- If I ever paste in a YouTube link, use yt-dlp to summarize the video.
- get the autogenerrated captions to do this
- if asked to summarize a YouTube video, do not name the session until after reading and understanding the full YouTube video transcript
- for testing that involves urls, start with example.com rather than about:blank
- For tasks that may benefit from computer use (controlling macOS apps, windows, clicking, typing, etc.), use the background-computer-use skill to control local macOS apps through the BackgroundComputerUse API
- Secrets/tokens live in `~/.env` (e.g. `HF_TOKEN` for Hugging Face). Source it before use: `set -a; . ~/.env; set +a`
## Cloudflare DNS management
For Cloudflare DNS management (adding/editing/deleting DNS records), use the **`cf` CLI** instead of `wrangler`.
Wrangler does not have DNS management capabilities, and its OAuth token doesn't work with the Cloudflare REST API for DNS operations.
### Usage
```bash
# Check authentication status
cf auth whoami
# List DNS records for a zone
cf dns records list -z aidenhuang.com
# Add a DNS record
cf dns records create -z aidenhuang.com --type CNAME --name devin --content "target.example.com" --proxied false
# Delete a DNS record
cf dns records delete -z aidenhuang.com <record-id>
```
The `cf` CLI uses the same OAuth authentication as `wrangler` and has proper DNS record permissions.
## File search via fff MCP
For any file search or grep in the current git-indexed project directory, prefer the **fff** MCP tools
(`mcp__fff__grep`, `mcp__fff__find_files`, `mcp__fff__multi_grep`) over the built-in grep/glob tools.
fff is frecency-ranked, git-aware, and more token-efficient.
Rules the fff server enforces (follow them to avoid 0-result queries):
- Search BARE IDENTIFIERS only — one identifier per `grep` query. No `load.*metadata.*Foo` style regex.
- Don't use regex unless you truly need alternation; `.*`, `\d+`, `\s+` almost always return 0 results.
- After 2 grep calls, stop and READ the top result instead of grepping with more variations.
- Use `multi_grep` for OR logic across multiple identifiers (e.g. snake_case + PascalCase variants) in one call.
- Have a specific name → `grep`. Exploring a topic / finding files → `find_files`.
The `fff-mcp` binary lives at `/Users/root1/.local/bin/fff-mcp` and is registered at user scope
in `~/.config/devin/config.json`. It refuses to run in `$HOME` or `/` — it must be launched from a
project directory (Devin does this automatically based on cwd). Update with:
`curl -fsSL https://raw.githubusercontent.com/dmtrKovalenko/fff.nvim/main/install-mcp.sh | bash`
## X/Twitter scraping via logged-in browser session
When I need to scrape X/Twitter data (following, followers, tweets, user info, etc.),
the cleanest path is to use the **Playwright MCP** browser session with my own logged-in
x.com account, rather than spinning up twscrape's account-pool flow. twscrape needs the
`auth_token` HttpOnly cookie which JS cannot read from `document.cookie`; the browser
session attaches all cookies automatically.
### Flow
1. `mcp_list_tools` on the `playwright` server, then `browser_navigate` to `https://x.com`.
2. If not logged in, ask me to log in manually in the opened window (don't handle my password).
3. Once on `https://x.com/home`, read `ct0` from `document.cookie`:
`document.cookie.match(/ct0=([^;]+)/)[1]`
4. Call X's GraphQL endpoints directly via `fetch()` inside `browser_evaluate`. Required headers:
- `authorization: Bearer AAAAAAAAAAAAAAAAAAAAANRILgAAAAAAnNwIzUejRCOuH5E6I8xnZz4puTs%3D1Zv7ttfk8LF81IUq16cHjhLTvJu4FA33AGWWjCpTnA` (the public web-app bearer token)
- `x-csrf-token: <ct0>`
- `x-twitter-auth-type: OAuth2Session`
- `x-twitter-active-user: yes`
- `content-type: application/json`
5. Paginate timelines by reading `content.cursorType === "Bottom"` entries and passing
the value back as `variables.cursor` until it stops changing.
### Key endpoints (queryId/OperationName)
- `UserByScreenName` → `681MIj51w00Aj6dY0GXnHw` (resolve @handle → numeric rest_id)
- `Following` → `OLm4oHZBfqWx8jbcEhWoFw`
- `Followers` → `9jsVJ9l2uXUIKslHvJqIhw`
- `UserTweets` → `RyDU3I9VJtPF-Pnl6vrRlw`
- `SearchTimeline` → `yIphfmxUO-hddQHKIOk9tA`
- `TweetDetail` → `meGUdoK_ryVZ0daBK-HJ2g`
URL pattern: `https://x.com/i/api/graphql/<queryId>/<OpName>?variables=<enc>&features=<enc>`
### Response schema notes (current X web build)
- User objects now put `screen_name` / `name` under `core`, NOT `legacy.screen_name`.
twscrape's parser still reads `legacy.screen_name` and returns empty — needs updating.
- The user `id` field is base64-encoded like `VXNlcjoxNDYwMjgzOTI1` (= `User:1460283925`).
Decode with `atob(u.id).split(':')[1]` to get the numeric rest_id. `u.rest_id` may also
be present directly.
- `is_blue_verified` is the verified flag. `legacy.followers_count`, `legacy.description`
still exist under `legacy`.
- Filter timeline entries by `content.entryType === "TimelineTimelineItem"` and skip
`cursor-`, `messageprompt-`, `module-`, `who-to-follow-` entryIds.
### Features dict
Use the full `GQL_FEATURES` block from twscrape's `api.py` — without it X returns
`(336) The following features cannot be null`. Pass it URL-encoded as the `features` param.
### Where things live
- Output CSV: `~/Downloads/utilities/sdand_following.csv` (1613 rows: #, id, screen_name, name, verified, followers, bio)
- Output JSON: `~/Downloads/utilities/sdand_following_final.json` (double-encoded JSON string; parse with `json.loads(json.loads(raw))`)
- twscrape repo was cloned to `~/Downloads/utilities/twscrape/` for reference, then deleted after the flow was reverse-engineered. Re-clone from https://github.com/vladkens/twscrape.git if needed.
## Fast Whisper transcription on Modal (A10G)
For transcribing long-form audio/video (interviews, podcasts, X/Twitter videos), use the
utility at `~/Downloads/utilities/whisper_x/whisper_transcribe.py`. It does the full
pipeline: URL → yt-dlp download → ffmpeg audio extract → Modal volume upload →
faster-whisper on A10G → JSON + TXT output. Validated at **2.3 min wall clock for 65 min
of audio** (no caching at any layer).
### Usage
Shell alias (defined in `~/.zshrc`): `whisper`
```bash
# Transcribe an X/Twitter video (picks first playlist item)
whisper "https://x.com/.../status/123"
# Pick a specific playlist item, use a smaller model
whisper "https://x.com/..." --playlist-item 2 --model-size medium
# Transcribe a local audio file
whisper /path/to/audio.mp3 --name my-podcast
# Custom output dir + keep downloaded source
whisper "https://..." --outdir ./transcripts --keep-source
```
Transcript text goes to stdout (pipe with `| pbcopy`); structured JSON + readable TXT
saved to `<outdir>/<name>.json` and `<outdir>/<name>.txt`.
### Key optimizations (vs naive T4 run that took 11.7 min)
- **A10G GPU** (~8x fp16 throughput vs T4; Modal ~$0.60/hr vs ~$0.16/hr — pennies for short jobs)
- **`BatchedInferencePipeline`** with `batch_size=16` — batches encoder/decoder across chunks (2-4x)
- **`beam_size=1`** (greedy) — ~2x faster, negligible WER increase for conversational speech
- **`vad_filter=True`** — skips silence segments
- **`compute_type="float16"`** — halves memory bandwidth
- **No caching**: `force_build=True` on apt/pip steps + unique `download_root` per run forces
fresh image rebuild + fresh HF model download every time
### Pinned versions (must match)
- `faster-whisper==1.1.1` (provides `BatchedInferencePipeline`)
- `ctranslate2==4.8.0`
- Base image: `nvidia/cuda:12.6.3-cudnn-runtime-ubuntu22.04` (provides `libcublas.so.12`;
`debian_slim` fails with `RuntimeError: Library libcublas.so.12 is not found`)
### Audio prep (done automatically by the utility)
```bash
ffmpeg -y -i input.mp4 -vn -ac 1 -ar 16000 -c:a aac -b:a 64k audio.m4a
```
Mono 16kHz 64kbps AAC — a 65-min video (151 MB stream) becomes ~35 MB audio.
### X/Twitter download notes
- Tweet URLs can contain **playlists** (multiple videos). Use `--playlist-item N` to pick one.
- Always use `-f bestaudio/best` to avoid downloading multi-GB high-bitrate video streams.
- A 65-min interview's video variant can be 2.8+ GB; audio-only is ~63 MB (128 kbps).
### Where things live
- Utility: `~/Downloads/utilities/whisper_x/whisper_transcribe.py`
- Strategy doc: `~/Downloads/utilities/whisper_x/STRATEGY.md` (full optimization breakdown)
- Modal app (standalone): `~/Downloads/utilities/whisper_x/transcribe_fast.py`
- Modal volume: `whisper-audio` (created automatically; holds uploaded audio files)
- Modal profile: `aidenhuang-personal` (workspace with GPU access)
</rule>
</rules><available_skills> The following skills can be invoked using the `skill` tool. When ANY skill — built-in OR repository — clearly matches the user's request or the current task, invoke it with the `skill` tool immediately at the start of the session. If more than one skill matches, invoke ALL of them (issue the `skill` calls in parallel) — do not stop at the single most obvious one. - **find-skills**: Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill. (source: /Users/root1/.agents/skills/find-skills/SKILL.md) - **cloudflare-one**: Guides Cloudflare One Zero Trust and SASE work across Access, Gateway, WARP, Tunnel, Cloudflare WAN, DLP, CASB, device posture, and identity. Use when designing, configuring, troubleshooting, or reviewing Cloudflare One deployments. Retrieval-first: use current Cloudflare docs/API schemas instead of embedded product docs. (source: /Users/root1/.claude/skills/cloudflare-one/SKILL.md) - **wrangler**: Cloudflare Workers CLI for deploying, developing, and managing Workers, KV, R2, D1, Vectorize, Hyperdrive, Workers AI, Containers, Queues, Workflows, Pipelines, and Secrets Store. Load before running wrangler commands to ensure correct syntax and best practices. Biases towards retrieval from Cloudflare docs over pre-trained knowledge. (source: /Users/root1/.agents/skills/wrangler/SKILL.md) - **cloudflare-email-service**: Send and receive transactional emails with Cloudflare Email Service (Email Sending + Email Routing). Use when building email sending (Workers binding or REST API), email routing, Agents SDK email handling, or integrating email into any app — Workers, Node.js, Python, Go, etc. Also use for email deliverability, SPF/DKIM/DMARC, wrangler email setup, MCP email tools, or when a coding agent needs to send emails. Even for simple requests like "add email to my Worker" — this skill has critical config details. (source: /Users/root1/.agents/skills/cloudflare-email-service/SKILL.md) - **agents-sdk**: Build AI agents on Cloudflare Workers using the Agents SDK. Load when creating stateful agents, durable workflows, real-time WebSocket apps, scheduled tasks, MCP servers, chat applications, voice agents, or browser automation. Covers Agent class, state management, callable RPC, Workflows, durable execution, queues, retries, observability, and React hooks. Biases towards retrieval from Cloudflare docs over pre-trained knowledge. (source: /Users/root1/.config/devin/skills/agents-sdk/SKILL.md) - **cloudflare-agent-setup**: (source: /Users/root1/.devin/skills/cloudflare-agent-setup/SKILL.md) - **web-perf**: Analyzes web performance using Chrome DevTools MCP. Measures Core Web Vitals (LCP, INP, CLS) and supplementary metrics (FCP, TBT, Speed Index), identifies render-blocking resources, network dependency chains, layout shifts, caching issues, and accessibility gaps. Use when asked to audit, profile, debug, or optimize page load performance, Lighthouse scores, or site speed. Biases towards retrieval from current documentation over pre-trained knowledge. (source: /Users/root1/.codeium/windsurf/skills/web-perf/SKILL.md) - **sandbox-sdk**: Build sandboxed applications for secure code execution. Load when building AI code execution, code interpreters, CI/CD systems, interactive dev environments, or executing untrusted code. Covers Sandbox SDK lifecycle, commands, files, code interpreter, and preview URLs. Biases towards retrieval from Cloudflare docs over pre-trained knowledge. (source: /Users/root1/.config/devin/skills/sandbox-sdk/SKILL.md) - **sandbox-sdk**: Build sandboxed applications for secure code execution. Load when building AI code execution, code interpreters, CI/CD systems, interactive dev environments, or executing untrusted code. Covers Sandbox SDK lifecycle, commands, files, code interpreter, and preview URLs. Biases towards retrieval from Cloudflare docs over pre-trained knowledge. (source: /Users/root1/.agents/skills/sandbox-sdk/SKILL.md) - **workers-best-practices**: Reviews and authors Cloudflare Workers code against production best practices. Load when writing new Workers, reviewing Worker code, configuring wrangler.jsonc, or checking for common Workers anti-patterns (streaming, floating promises, global state, secrets, bindings, observability). Biases towards retrieval from Cloudflare docs over pre-trained knowledge. (source: /Users/root1/.claude/skills/workers-best-practices/SKILL.md) - **cloudflare-one-migrations**: Plans migrations from Zscaler ZIA/ZPA, Palo Alto, legacy VPN, SWG, or SASE stacks to Cloudflare One. Use for migration assessments, policy mapping, rollout plans, and parity/gap analysis. (source: /Users/root1/.config/devin/skills/cloudflare-one-migrations/SKILL.md) - **durable-objects**: Create and review Cloudflare Durable Objects. Use when building stateful coordination (chat rooms, multiplayer games, booking systems), implementing RPC methods, SQLite storage, alarms, WebSockets, or reviewing DO code for best practices. Covers Workers integration, wrangler config, and testing with Vitest. Biases towards retrieval from Cloudflare docs over pre-trained knowledge. (source: /Users/root1/.config/devin/skills/durable-objects/SKILL.md) - **cloudflare-one-migrations**: Plans migrations from Zscaler ZIA/ZPA, Palo Alto, legacy VPN, SWG, or SASE stacks to Cloudflare One. Use for migration assessments, policy mapping, rollout plans, and parity/gap analysis. (source: /Users/root1/.claude/skills/cloudflare-one-migrations/SKILL.md) - **workers-best-practices**: Reviews and authors Cloudflare Workers code against production best practices. Load when writing new Workers, reviewing Worker code, configuring wrangler.jsonc, or checking for common Workers anti-patterns (streaming, floating promises, global state, secrets, bindings, observability). Biases towards retrieval from Cloudflare docs over pre-trained knowledge. (source: /Users/root1/.config/devin/skills/workers-best-practices/SKILL.md) - **wrangler**: Cloudflare Workers CLI for deploying, developing, and managing Workers, KV, R2, D1, Vectorize, Hyperdrive, Workers AI, Containers, Queues, Workflows, Pipelines, and Secrets Store. Load before running wrangler commands to ensure correct syntax and best practices. Biases towards retrieval from Cloudflare docs over pre-trained knowledge. (source: /Users/root1/.config/devin/skills/wrangler/SKILL.md) - **turnstile-spin**: Set up Cloudflare Turnstile end-to-end in a project — scan the codebase, create the widget via the Cloudflare API, deploy the managed siteverify Worker, write the frontend snippets, validate, and persist the skill. Load this when a user asks to add Turnstile, set up CAPTCHA, protect a form from bots, or fix a Turnstile integration. Mirrors developers.cloudflare.com/turnstile/spin. (source: /Users/root1/.codeium/windsurf/skills/turnstile-spin/SKILL.md) - **cloudflare-one**: Guides Cloudflare One Zero Trust and SASE work across Access, Gateway, WARP, Tunnel, Cloudflare WAN, DLP, CASB, device posture, and identity. Use when designing, configuring, troubleshooting, or reviewing Cloudflare One deployments. Retrieval-first: use current Cloudflare docs/API schemas instead of embedded product docs. (source: /Users/root1/.config/devin/skills/cloudflare-one/SKILL.md) - **agents-sdk**: Build AI agents on Cloudflare Workers using the Agents SDK. Load when creating stateful agents, durable workflows, real-time WebSocket apps, scheduled tasks, MCP servers, chat applications, voice agents, or browser automation. Covers Agent class, state management, callable RPC, Workflows, durable execution, queues, retries, observability, and React hooks. Biases towards retrieval from Cloudflare docs over pre-trained knowledge. (source: /Users/root1/.codeium/windsurf/skills/agents-sdk/SKILL.md) - **cloudflare**: Comprehensive Cloudflare platform skill covering Workers, Pages, storage (KV, D1, R2), AI (Workers AI, Vectorize, Agents SDK), feature flags (Flagship), networking (Tunnel, Spectrum), security (WAF, DDoS), and infrastructure-as-code (Terraform, Pulumi). Use for any Cloudflare development task. Biases towards retrieval from Cloudflare docs over pre-trained knowledge. (source: /Users/root1/.codeium/windsurf/skills/cloudflare/SKILL.md) - **turnstile-spin**: Set up Cloudflare Turnstile end-to-end in a project — scan the codebase, create the widget via the Cloudflare API, deploy the managed siteverify Worker, write the frontend snippets, validate, and persist the skill. Load this when a user asks to add Turnstile, set up CAPTCHA, protect a form from bots, or fix a Turnstile integration. Mirrors developers.cloudflare.com/turnstile/spin. (source: /Users/root1/.config/devin/skills/turnstile-spin/SKILL.md) - **durable-objects**: Create and review Cloudflare Durable Objects. Use when building stateful coordination (chat rooms, multiplayer games, booking systems), implementing RPC methods, SQLite storage, alarms, WebSockets, or reviewing DO code for best practices. Covers Workers integration, wrangler config, and testing with Vitest. Biases towards retrieval from Cloudflare docs over pre-trained knowledge. (source: /Users/root1/.codeium/windsurf/skills/durable-objects/SKILL.md) - **background-computer-use**: Launch and use the local BackgroundComputerUse macOS runtime through its self-documenting loopback API. Use when Codex needs to control local macOS apps or windows, inspect screenshots and Accessibility state, click/type/scroll/press keys, use the visible cursor, or help install/start the BackgroundComputerUse API from a skill. (source: /Users/root1/.devin/skills/background-computer-use/SKILL.md) - **web-perf**: Analyzes web performance using Chrome DevTools MCP. Measures Core Web Vitals (LCP, INP, CLS) and supplementary metrics (FCP, TBT, Speed Index), identifies render-blocking resources, network dependency chains, layout shifts, caching issues, and accessibility gaps. Use when asked to audit, profile, debug, or optimize page load performance, Lighthouse scores, or site speed. Biases towards retrieval from current documentation over pre-trained knowledge. (source: /Users/root1/.config/devin/skills/web-perf/SKILL.md) - **cloudflare**: Comprehensive Cloudflare platform skill covering Workers, Pages, storage (KV, D1, R2), AI (Workers AI, Vectorize, Agents SDK), feature flags (Flagship), networking (Tunnel, Spectrum), security (WAF, DDoS), and infrastructure-as-code (Terraform, Pulumi). Use for any Cloudflare development task. Biases towards retrieval from Cloudflare docs over pre-trained knowledge. (source: /Users/root1/.config/devin/skills/cloudflare/SKILL.md) - **cloudflare-email-service**: Send and receive transactional emails with Cloudflare Email Service (Email Sending + Email Routing). Use when building email sending (Workers binding or REST API), email routing, Agents SDK email handling, or integrating email into any app — Workers, Node.js, Python, Go, etc. Also use for email deliverability, SPF/DKIM/DMARC, wrangler email setup, MCP email tools, or when a coding agent needs to send emails. Even for simple requests like "add email to my Worker" — this skill has critical config details. (source: /Users/root1/.config/devin/skills/cloudflare-email-service/SKILL.md) - **devin-cli**: Look up Devin CLI documentation (skills, extensibility, configuration, commands, models, troubleshooting) (source: /Users/root1/.local/share/devin/cli/_versions/3000.1.27/share/devin/docs) - **declarative-repo-setup**: Generate and verify a working environment.yaml (Devin snapshot-setup blueprint) for a repo (source: builtin:drs) </available_skills>
do you have any instructions on how to use whisper?
The user is asking how to use whisper. Looking at the AGENTS.md rule that was provided, there's a section titled "Fast Whisper transcription on Modal (A10G)" which has detailed instructions. I should summarize those instructions for the user.
Yes — here are the whisper instructions from your AGENTS.md rules:
Utility location:
~/Downloads/utilities/whisper_x/whisper_transcribe.py
Shell alias (in ~/.zshrc): whisper
Basic usage:
# Transcribe an X/Twitter video (picks first playlist item)
whisper "https://x.com/.../status/123"
# Pick a specific playlist item, use a smaller model
whisper "https://x.com/..." --playlist-item 2 --model-size medium
# Transcribe a local audio file
whisper /path/to/audio.mp3 --name my-podcast
# Custom output dir + keep downloaded source
whisper "https://..." --outdir ./transcripts --keep-source
| pbcopy)<outdir>/<name>.json and <outdir>/<name>.txtPipeline: URL → yt-dlp download → ffmpeg audio extract → Modal volume upload → faster-whisper on A10G → JSON + TXT output.
Key optimizations:
BatchedInferencePipeline with batch_size=16beam_size=1 (greedy)vad_filter=Truecompute_type="float16"Pinned versions (must match):
faster-whisper==1.1.1ctranslate2==4.8.0nvidia/cuda:12.6.3-cudnn-runtime-ubuntu22.04Audio prep (automatic):
ffmpeg -y -i input.mp4 -vn -ac 1 -ar 16000 -c:a aac -b:a 64k audio.m4a
X/Twitter download tips:
--playlist-item N to pick one.-f bestaudio/best to avoid downloading multi-GB high-bitrate video streams.Other files:
~/Downloads/utilities/whisper_x/STRATEGY.md~/Downloads/utilities/whisper_x/transcribe_fast.pywhisper-audio (created automatically)aidenhuang-personalDo you want me to run it on a specific URL or file?
okay run that on the laszt mp4 in downloads
The user wants me to run whisper on the last mp4 in Downloads. I need to: 1. Find the last mp4 file in Downloads 2. Run the whisper utility on it Let me first list the mp4 files in Downloads to find the latest one.
{
"command": "ls -lt ~/Downloads/*.mp4 2>/dev/null | head -20",
"interactive_shell": "bash"
}Output from command in shell 357691: -rw-r--r--@ 1 root1 staff 18694563 Jul 9 07:20 /Users/root1/Downloads/-IVHoru G94cs7nea.mp4 Exit code: 0
There's one mp4 file in Downloads: `/Users/root1/Downloads/-IVHoruG94cs7nea.mp4`. Note the filename has a newline/space issue in the output - it shows as: ``` -rw-r--r--@ 1 root1 staff 18694563 Jul 9 07:20 /Users/root1/Downloads/-IVHoru G94cs7nea.mp4 ``` This might be a literal newline in the filename. I need to handle that carefully. Let me get the exact filename.
{
"command": "find ~/Downloads -maxdepth 1 -name '*.mp4' -print0 | xargs -0 ls -lt",
"interactive_shell": "bash"
}Output from command in shell 413344: -rw-r--r--@ 1 root1 staff 18694563 Jul 9 07:20 /Users/root1/Downloads/-IVHoru G94cs7nea.mp4 Exit code: 0
The filename appears to literally contain a newline between "Horu" and "G94cs7nea". That's unusual but possible. I should handle it carefully. Let me run whisper on this file. I need to quote it properly. Since the filename contains a newline, I'll need to use the `whisper` alias with the path properly escaped. Actually, the file is `/Users/root1/Downloads/-IVHoru\nG94cs7nea.mp4`. I need to run the whisper command. Since the shell interprets newlines, I can use a variable or quote it. Let me use a Python-style approach or escape it. I'll first assign the filename to a variable using find -print0, then run whisper. Wait - the `whisper` alias is defined in ~/.zshrc, but I'm running bash. I should source ~/.zshrc or run in zsh, or use the full python command. Let me check what the alias is and whether we're in bash or zsh. Actually, the exec tool uses bash by default unless interactive_shell is set. I set interactive_shell to bash. The alias is in ~/.zshrc. Bash won't load .zshrc. I can either: 1. Run in zsh interactive shell 2. Use the full command that the alias expands to 3. Source the .zshrc in bash (but it may have zsh-specific syntax) Let me try running in zsh, or better, get the exact command. Let me look at the .zshrc to see the alias definition, or just use zsh. Actually, the safest is to use the full path to the Python script. But I need the Modal profile and all. Let me read the .zshrc to see what the alias does.
{
"command": "grep -n '^alias whisper' ~/.zshrc || grep -n 'whisper' ~/.zshrc",
"interactive_shell": "bash"
}Output from command in shell a5aab2: 3:alias whisper='python3 ~/Downloads/utilities/whisper_x/whisper_transcribe.py' Exit code: 0
The alias is `alias whisper='python3 ~/Downloads/utilities/whisper_x/whisper_transcribe.py'`. Now I need to run this on the mp4 file. The filename has a newline in it. I'll use a variable in bash and pass it to python. Since Python will be called with the filename as an argument, I need to handle the newline correctly. One approach: ```bash file=$(find ~/Downloads -maxdepth 1 -name '*.mp4' -print0 | head -z -n 1 | tr -d '\0') python3 ~/Downloads/utilities/whisper_x/whisper_transcribe.py "$file" ``` Wait, `head -z` may not work on macOS. Let me use `find` with `-print0` and read it properly. Actually, a simpler approach: rename the file or use `find -exec`. But since the file has a newline, I should be careful. Let me check if the filename really has a newline or if the ls output is wrapping.
{
"command": "find ~/Downloads -maxdepth 1 -name '*.mp4' -print0 | od -c | head -5",
"interactive_shell": "bash"
}Output from command in shell 766990: 0000000 / U s e r s / r o o t 1 / D o w 0000020 n l o a d s / - I V H o r u G 9 0000040 4 c s 7 n e a . m p 4 \0 0000054 Exit code: 0
Good - the filename is actually `/Users/root1/Downloads/-IVHoruG94cs7nea.mp4` without a newline. The earlier `ls -lt` output was just wrapped at a weird boundary due to terminal width, not a literal newline. Now I can run whisper on this file. I'll use the full python command since we're in bash and the alias is in zsh.
{
"command": "python3 ~/Downloads/utilities/whisper_x/whisper_transcribe.py \"/Users/root1/Downloads/-IVHoruG94cs7nea.mp4\" --name \"last_download\"",
"interactive_shell": "bash",
"timeout": 600000
}=== Using local file: /Users/root1/Downloads/-IVHoruG94cs7nea.mp4 ===
=== Extracting / re-encoding audio to 16kHz mono ===
$ ffmpeg -y -i /Users/root1/Downloads/-IVHoruG94cs7nea.mp4 -vn -ac 1 -ar 16000
-c:a aac -b:a 64k /Users/root1/audio.m4a
ffmpeg version 8.0.1 Copyright (c) 2000-2025 the FFmpeg developers
built with Apple clang version 17.0.0 (clang-1700.6.3.2)
configuration: --prefix=/opt/homebrew/Cellar/ffmpeg/8.0.1_1 --enable-shared --
enable-pthreads --enable-version3 --cc=clang --host-cflags= --host-ldflags= --en
able-ffplay --enable-gpl --enable-libsvtav1 --enable-libopus --enable-libx264 --
enable-libmp3lame --enable-libdav1d --enable-libvpx --enable-libx265 --enable-vi
deotoolbox --enable-audiotoolbox --enable-neon
libavutil 60. 8.100 / 60. 8.100
libavcodec 62. 11.100 / 62. 11.100
libavformat 62. 3.100 / 62. 3.100
libavdevice 62. 1.100 / 62. 1.100
libavfilter 11. 4.100 / 11. 4.100
libswscale 9. 1.100 / 9. 1.100
libswresample 6. 1.100 / 6. 1.100
Input #0, mov,mp4,m4a,3gp,3g2,mj2, from '/Users/root1/Downloads/-IVHoruG94cs7nea
.mp4':
Metadata:
major_brand : isom
minor_version : 1
compatible_brands: isom
creation_time : 2025-08-17T11:49:33.000000Z
Duration: 00:03:30.58, start: 0.000000, bitrate: 710 kb/s
Stream #0:0[0x1](und): Video: h264 (High) (avc1 / 0x31637661), yuv420p(progres
sive), 1280x720, 575 kb/s, SAR 1:1 DAR 16:9, 23.98 fps, 23.98 tbr, 2400k tbn (de
fault)
Metadata:
handler_name : Twitter-vork muxer
vendor_id : [0][0][0][0]
Stream #0:1[0x2](und): Audio: aac (LC) (mp4a / 0x6134706D), 44100 Hz, stereo,
fltp, 128 kb/s (default)
Metadata:
handler_name : Twitter-vork muxer
vendor_id : [0][0][0][0]
Stream mapping:
Stream #0:1 -> #0:0 (aac (native) -> aac (native))
Press [q] to stop, [?] for help
Output #0, ipod, to '/Users/root1/audio.m4a':
Metadata:
major_brand : isom
minor_version : 1
compatible_brands: isom
encoder : Lavf62.3.100
Stream #0:0(und): Audio: aac (LC) (mp4a / 0x6134706D), 16000 Hz, mono, fltp, 6
4 kb/s (default)
Metadata:
encoder : Lavc62.11.100 aac
handler_name : Twitter-vork muxer
vendor_id : [0][0][0][0]
size= 768KiB time=00:01:30.56 bitrate= 69.5kbits/s speed= 179x elapsed=0:00
size= 1536KiB time=00:03:15.64 bitrate= 64.3kbits/s speed= 194x elapsed=0:00
[out#0/ipod @ 0xa07044300] video:0KiB audio:1798KiB subtitle:0KiB other streams:
0KiB global headers:0KiB muxing overhead: 0.760025%
size= 1812KiB time=00:03:30.58 bitrate= 70.5kbits/s speed= 194x elapsed=0:00
:01.08
[aac @ 0xa07041180] Qavg: 2826.578
=== Uploading audio.m4a to Modal volume 'whisper-audio' ===
$ modal volume put whisper-audio /Users/root1/audio.m4a last_download_17836068
77.m4a
✓ Uploaded file '/Users/root1/audio.m4a' to 'last_download_1783606877.m4a'
=== Running Whisper large-v3 on Modal A10G (no caching) ===
===
Stopped waiting for output after 10.3 seconds. Command running in background with ID: bb5d0b. Run get_output with timeout if you need to wait.The command is running in background. I need to wait for it to complete. Let me use get_output to check the progress.
{
"shell_id": "bb5d0b",
"timeout": 600000,
"incremental": true
}Warning: requested timeout 10m exceeds maximum of 5m; clamping to 5m. === WALL CLOCK: 26.8s (0.45 min) === === Saving transcript === JSON: /Users/root1/last_download.json TXT: /Users/root1/last_download.txt I would say definitely Elon runs his companies in extremely unique style. I don' t actually think that people appreciate how unique it is. You sort of like even read about it and so much you don't understand it, I think. It's like even hard to describe. I don't even know where to start. But well, number one is like, so he likes very small, strong, highly technical teams. I would say at companies by default, the teams grow and they get large. Elon was always like a force agains t growth. I would have to work and expend efforts to hire people. I would have t o like... basically plead to hire people. And then the other thing is that big c ompanies, it's really hard to get rid of low performers. And I think Elon is ver y friendly to by default getting rid of low performers. So I actually had to fig ht for people to keep them on the team because he would by default want to remov e people. So keep a small, strong, highly technical team. No middle management t hat is kind of like non-technical for sure. So that's number one. Number two is kind of like the vibes of how this is, how everything runs and how it feels when he sort of like walks into the office. He wants it to be a vibrant place. Peopl e are walking around, they're pacing around, they're working on exciting stuff, they're charting something, they're coding. You know, he doesn't like stagnation . He doesn't like to look. for it to look that way. He doesn't like large meetin gs. He always encourages people to leave meetings if they're not being useful. S o actually, you do see this. It's a large meeting. If you're not contributing an d you're not learning, just walk out. And this is fully encouraged. And I think this is something that you don't normally see. I think a lot of big companies, t hey're like pamper employees. I think there's much less of that. The culture of it is you're there to do your best technical work. And there's the intensity and so on. And I think maybe the last one that is very unique and very interesting and very strange is just how connected he is to the team. So usually a CEO of a company is like a remote person, five layers up, who talks to their VPs, who tal k to their reports and directors, and eventually you talk to your manager. That' s not how he is as companies, right? Like he will come. the office he will talk to the engineers normally people spend like 99 of the time maybe talking to the vpc he spends maybe 50 of the time and he just wants to talk to the engineers so if the team is small and strong then engineers and the code are the source of t ruth and so they have the source of truth not some manager and he wants to talk to them to understand the actual state of things and what should be done to impr ove it and also just like his large hammer and his willingness to exercise it wi thin the organization so Maybe if he talks to the engineers and they bring up th at, you know, what's blocking you? Okay, I just, I don't have enough GPUs to run my thing. And he's like, oh, okay. And if he hears that twice, he's going to be like, okay, this is a problem. So, like, what is our timeline? And when you don 't have satisfying answers, he's like, okay, I want to talk to the person in cha rge of the GPU cluster. And, like, someone dials the phone and he's just like, o kay, double the cluster right now. Like let's have a meeting tomorrow, from now on send me daily updates until the cluster is twice the size. And then they kind of like push back and they're like, okay, well we have this procurement set up, we have this timeline and Nvidia says that we don't have enough GPUs and it wil l take six months or something. And then you get a rise of an eyebrow and then h e's like, okay, I'm gonna talk to Jensen. And then he just kind of like removes bottlenecks. So I think the extent to which he's like extremely involved and rem oves bottlenecks and applies his hammer, I think is also like not appreciated. S o I think there's a lot of these kinds of aspects that are very unique, I would say, and very interesting. And honestly, going to a normal company outside of th at, you definitely miss aspects of that. Maybe that's the long rant. I don't thi nk I hit on all the points, but it is a very unique thing, and it's very interes ting. Exit code: 0
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I would say definitely Elon runs his companies in extremely unique style. I don't actually think that people appreciate how unique it is. You sort of like even read about it and so much you don't understand it, I think. It's like even hard to describe. I don't even know where to start. But well, number one is like, so he likes very small, strong, highly technical teams. I would say at companies by default, the teams grow and they get large. Elon was always like a force against growth. I would have to work and expend efforts to hire people. I would have to like... basically plead to hire people. And then the other thing is that big companies, it's really hard to get rid of low performers. And I think Elon is very friendly to by default getting rid of low performers. So I actually had to fight for people to keep them on the team because he would by default want to remove people. So keep a small, strong, highly technical team. No middle management that is kind of like non-technical for sure. So that's number one. Number two is kind of like the vibes of how this is, how everything runs and how it feels when he sort of like walks into the office. He wants it to be a vibrant place. People are walking around, they're pacing around, they're working on exciting stuff, they're charting something, they're coding. You know, he doesn't like stagnation. He doesn't like to look. for it to look that way. He doesn't like large meetings. He always encourages people to leave meetings if they're not being useful. So actually, you do see this. It's a large meeting. If you're not contributing and you're not learning, just walk out. And this is fully encouraged. And I think this is something that you don't normally see. I think a lot of big companies, they're like pamper employees. I think there's much less of that. The culture of it is you're there to do your best technical work. And there's the intensity and so on. And I think maybe the last one that is very unique and very interesting and very strange is just how connected he is to the team. So usually a CEO of a company is like a remote person, five layers up, who talks to their VPs, who talk to their reports and directors, and eventually you talk to your manager. That's not how he is as companies, right? Like he will come. the office he will talk to the engineers normally people spend like 99 of the time maybe talking to the vpc he spends maybe 50 of the time and he just wants to talk to the engineers so if the team is small and strong then engineers and the code are the source of truth and so they have the source of truth not some manager and he wants to talk to them to understand the actual state of things and what should be done to improve it and also just like his large hammer and his willingness to exercise it within the organization so Maybe if he talks to the engineers and they bring up that, you know, what's blocking you? Okay, I just, I don't have enough GPUs to run my thing. And he's like, oh, okay. And if he hears that twice, he's going to be like, okay, this is a problem. So, like, what is our timeline? And when you don't have satisfying answers, he's like, okay, I want to talk to the person in charge of the GPU cluster. And, like, someone dials the phone and he's just like, okay, double the cluster right now. Like let's have a meeting tomorrow, from now on send me daily updates until the cluster is twice the size. And then they kind of like push back and they're like, okay, well we have this procurement set up, we have this timeline and Nvidia says that we don't have enough GPUs and it will take six months or something. And then you get a rise of an eyebrow and then he's like, okay, I'm gonna talk to Jensen. And then he just kind of like removes bottlenecks. So I think the extent to which he's like extremely involved and removes bottlenecks and applies his hammer, I think is also like not appreciated. So I think there's a lot of these kinds of aspects that are very unique, I would say, and very interesting. And honestly, going to a normal company outside of that, you definitely miss aspects of that. Maybe that's the long rant. I don't think I hit on all the points, but it is a very unique thing, and it's very interesting.
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The user wants a summary of the transcript. The transcript is about someone describing Elon Musk's unique management style at his companies. I should provide a concise summary of the key points. Key points: 1. Small, strong, highly technical teams - Elon resists team growth, fights against bloat 2. Removing low performers - he's friendly to default removal of low performers 3. No non-technical middle management 4. Vibrant office culture - people active, working on exciting things, no stagnation 5. No useless meetings - encourages leaving meetings if not contributing or learning 6. Less pampering of employees compared to big companies 7. Connected to team - talks directly to engineers, not through layers of management 8. Removes bottlenecks aggressively - uses his influence/power ("large hammer") to remove obstacles quickly 9. Will go directly to people in charge or even external CEOs (Jensen/Nvidia) to solve problems I'll write a concise summary.
The speaker describes Elon Musk's highly unusual management style, highlighting a few key traits:
Overall: intense, engineer-driven, anti-bureaucracy, and unusually direct.