Slack AI

Slack AI AI

Slack AI AI

Slack AI AI

Slack AI AI

Slack AI AI

Slack AI AI

Slack AI AI

Slack AI AI

Slack AI AI

Slack AI AI

the take that 'ai doesn't do anything useful yet' held up for me until i ditched the chat window

Counted it last week: one monday review had me opening 6 apps and copy-pasting between all of them, while a chatbot sat in a 7th tab handing me summaries i still had to go act on. that's the part the 'ai is useless' crowd is actually right about. text out, the work is still on you. what moved me off that take wasn't a smarter model. it was dropping the chat window for a desktop agent that reads gmail, calendar and slack inside the same task and takes the next step itself, with a permission prompt before each action so it isn't running wild. the $500m-wasted-on-claude thread up top is the same thing from the money side. paying for tokens that spit out paragraphs nobody executes is just the expensive way to do nothing. If you're still in the 'it doesn't actually do anything' camp, fair, i was there too. the line for me was the day it finished a task instead of describing one. written with ai submitted by /u/Deep_Ad1959 [link] [comments]

the hard part of an automated sprint review isn't the summary, it's the join

Spent a while trying to get one sprint digest out of linear, github, and slack and the summarization was never the hard part. the join is. linear calls it ENG-1432, github calls it PR #890, the incident is a slack thread with no shared id at all. a chat-window model summarizes each source fine but it can't reconcile that the PR closed the issue that caused the incident, because it never holds all three at once with the relationships intact. what actually moved this for me was a desktop agent (Runner) where the connectors aren't thin rest wrappers. they do association traversal, so the github side already knows which PR references which linear issue, and the digest comes out as 'this deploy shipped these issues, one reopened after an incident' instead of three disconnected bullet lists. deploy status and incident notes in the same view is where it gets useful and also where most tool-calling setups quietly fall apart, the model guesses the cross-references instead of resolving them. if you wired this up with raw function calling, did the entity resolution end up living in the prompt or down in the tool layer? written with ai submitted by /u/Deep_Ad1959 [link] [comments]

Claude Code Source Deep Dive (Part 5) — Literal Translation & Tool-Call Loop Self-Repair Core Mechanism

Reader’s Note On March 31, 2026, the Claude Code package Anthropic published to npm accidentally included .map files that can be reverse-engineered to recover source code. Because the source maps pointed to the original TypeScript sources, these 512,000 lines of TypeScript finally put everything on the table: how a top-tier AI coding agent organizes context, calls tools, manages multiple agents, and even hides easter eggs. I read the source from the entrypoint all the way through prompts, the task system, the tool layer, and hidden features. I will continue to deconstruct the codebase and provide in-depth analysis of the engineering architecture behind Claude Code. 3.14 EnterWorktree Tool (Enter Worktree) Create isolated git worktree and switch current session into it. When to Use: - User explicitly says "worktree" When NOT to Use: - User asks to create/switch branches - User asks to fix bug or work on feature without mentioning worktrees - NEVER use unless user explicitly mentions "worktree" Behavior: - Creates new git worktree inside `.claude/worktrees/` with new branch - Switches session's working directory to new worktree 3.15 AskUserQuestion Tool (Ask User Question) Ask user multiple choice questions to gather info, clarify ambiguity, understand preferences, make decisions, offer choices. Usage Notes: - Users always able to select "Other" for custom text input - Use multiSelect: true to allow multiple answers - If recommend specific option, make first option with "(Recommended)" at end Preview Feature: - Use optional `preview` field on options when presenting concrete artifacts needing visual comparison (ASCII/HTML mockups, code snippets, diagrams) - Preview content rendered as monospace markdown - When any option has preview, UI switches to side-by-side layout 3.16 LSP Tool (Language Server) Interact with Language Server Protocol servers for code intelligence. Supported Operations: - goToDefinition, findReferences, hover, documentSymbol, workspaceSymbol, goToImplementation, prepareCallHierarchy, incomingCalls, outgoingCalls All Operations Require: - filePath, line (1-based), character (1-based) 3.17 Sleep Tool (Wait) Wait for specified duration. Usage: - When user tells to sleep/rest - When nothing to do / waiting for something - May receive periodic check-ins (tick tags) - Can call concurrently with other tools - Prefer over `Bash(sleep ...)` — doesn't hold shell process - Each wake-up costs API call - Prompt cache expires after 5 min inactivity 3.18 CronCreate Tool (Scheduled Task) Schedule prompts to run at future times. Uses standard 5-field cron in user's local timezone. One-Shot Tasks (recurring: false): - "remind me at X" → pin minute/hour/day to specific values Recurring Jobs (recurring: true, default): - "every 5 min" → "*/5 * * * *" - "hourly" → "0 * * * *" CRITICAL: Avoid :00 and :30 Minute Marks (when task allows) - Every user asking "9am" gets 0 9, causing thundering herd - When approximate: pick minute NOT 0 or 30 - "every morning around 9" → "57 8 * * *" (not "0 9 * * *") Durability: - Default (durable: false): lives only in Claude session - durable: true: writes to .claude/scheduled_tasks.json Recurring tasks auto-expire after 7 days. 3.19 TeamCreate Tool (Create Team) Create team to coordinate multiple agents working on project. When to Use (Proactively): - User explicitly asks to use team, swarm, or group agents - Task complex enough for parallel work Team Workflow: 1. Create team with TeamCreate 2. Create tasks using Task tools 3. Spawn teammates using Agent tool with team_name + name params 4. Assign tasks using TaskUpdate with owner 5. Teammates work on assigned tasks 6. Shutdown gracefully via SendMessage with shutdown_request IMPORTANT: Always refer to teammates by NAME. Plain text output NOT visible to other agents — MUST call SendMessage tool to communicate. 3.20 ToolSearch Tool (Deferred Tool Search) Fetch full schema definitions for deferred tools so they can be called. Query Forms: - "select:Read,Edit,Grep" — fetch exact tools by name - "notebook jupyter" — keyword search, up to max_results best matches - "+slack send" — require "slack" in name, rank by remaining terms submitted by /u/Ill-Leopard-6559 [link] [comments]

Best Practices for CSM Account Handover + AI-Powered Transition Docs?

I’m a new CSM at a tech company and I’m taking over existing client accounts from other CSMs. We want to build a Claude/AI workflow that pulls info from Slack, Notion, Jira, CRM, Planhat, etc. to make customer handovers smoother. What are the most important things that should ALWAYS be included in an account handover? Examples: Account health/status Open projects/tickets Key stakeholders Risks/escalations Renewal/adoption status Executive relationships Also, what are the “unwritten” things that matter most? Like: Political dynamics Who really influences decisions Difficult stakeholders Communication preferences Hidden frustrations Things that never appear in Salesforce And finally: during the actual handover meeting between CSMs, what are the must-ask questions? Would love examples/templates from SaaS or tech teams. submitted by /u/Dapper_Whereas7024 [link] [comments]

Is this tagline intentional?

submitted by /u/JoshMJohns [link] [comments]

My Cowork has been broken for 48 hours. I dug into the session files and found my Max account is enrolled in a prompt variant "testfoo"?

My Cowork has been unusable for two days. Every prompt fires the wrong skill, connectors won't load, and Granola/Notion/Figma/Slack all show as "Connected" while exposing zero tools in sessions. The same connectors work fine in Chat mode. I went deep on diagnosing this with Claude Code, read Cowork's local session JSON files, the gb-cache feature flags, the 45,000-character system prompt, the works. Here's what I found after going back and forth with Claude Code: The smoking gun: My account is enrolled in two simultaneous A/B prompt variants. One of them is literally named`testfoo` — that's a developer placeholder name, not a production variant. The other one is `0526`, which appears to be a rollout from May 26 (lines up with when everything broke for me). Both variants contain the same directive: "user skills... should be attended to closely and used promiscuously when they seem at all relevant." Applied twice, that directive gets weighted heavily; which is exactly why the skill auto-router has been firing wrong skills on weak keyword matches all day. Paired with this: Cowork's runtime is throwing the error "ToolSearch exists but is not enabled in this context" meaning my account has deferred-tool-loading enabled but ToolSearch (the mechanism to load deferred tools) disabled. Anthropic's own Fin AI Agent confirmed this and said "a human engineer will need to adjust feature flags," but that human escalation hasn't happened yet. What I've tried (all useless): - Fresh Claude Desktop reinstall - Sign out + back in - Disconnect/reconnect every connector - Local cache flag overrides (overwritten on resync) - File edits to project memory (overwritten on resync) Related GitHub bugs that match exactly: - #20377 — Cowork MCP tools not exposed - #23736 — Granola MCP fails silently in Cowork specifically - #45306 — Slack, Notion, Gmail, Calendar all fail (verbatim match) - #61344 — marketplace migration race making user skills unreachable - #58172 — Cowork connectors broken after auto-update Anyone else hit this? Anyone on Anthropic see this and can route it internally? I'm on Max plan, this is core to my daily workflow, and I'd really love to not lose another day of work to an internal-test cohort that leaked into production. (Anthropic team — happy to share the full session JSON privately if it helps.) Thanks!! submitted by /u/notseano [link] [comments]

I used Claude Code to build a place to track my prompts like Github

I'm building a place where people share their Claude Code sessions with friends and coworkers. The ideas, the experiments, the discoveries made... Think: Github for Prompts. I work on a team and one of the hardest parts of code review is reading other people's code. Everyone is generating their PRs with Claude Code and yet, there's a good chance they didn't read their own code.. so why should I have to read it? I started by making a tool that lets you visualize your Claude Code threads and share them with your friends. The reason why was because sometimes I'd forget where a thread was and /resume wasn't enough for me. Claude Code can access the history of conversations on disk but it's hit or miss. Others can comment on the thread. Plans get archived so you can send them around, and others can comment on them so you can involve others in the planning process or get their feedback before letting it rip with auto mode. Programming code is now object code. People are doers, and software is the execution. I'm more concerned now with the intent behind the person and what they are thinking and saying to AI rather than what gets generated under the hood. Never quite sure which way this project will go, but something that I love about it is when you and your friends/coworkers are on Claude Code at the same time, you can see them online and what they're working on (if they allowed the activity). There's something about that; it feels like a new class of product almost (like Slack activity). After using it for a couple days I started noticing it was a major pain to read and scroll through large threads/conversations with Claude, so I added thread summaries and decisions. For every thread there's now a map that shows the decisions made by the human and you can click around to access that part of the thread. Once that was built, the team realized it would be extremely powerful to be able to chat with the entire knowledge base and ask how someone was approaching a problem... how we built a certain feature in the past... etc. I hope this project helpful to you in some way. Visualizing, sharing, and seeing your decisions is 100% free and will remain free (I want this to be like Github) https://lore.tanagram.ai submitted by /u/Novelicas [link] [comments]

Went down the Claude Code add-ons rabbit hole

I installed Claude Code, thinking that was basically the whole thing. But after I talked to some folks, I found are adding a bunch of extra stuff on top of it Some of the things I found useful, I feel, could be helpful to share - superpowers https://github.com/obra/superpowers codex-plugin-cc https://github.com/openai/codex-plugin-cc claude-skills https://github.com/anthropics/skills marketingskills https://github.com/coreyhaines31/marketingskills gstack https://github.com/garrytan/gstack frontend-design https://claude.com/plugins/frontend-design hyperframes https://github.com/heygen-com/hyperframes ai-second-brain https://github.com/coleam00/second-brain-starter notebooklm-skill https://github.com/PleasePrompto/notebooklm-skill humanizer https://github.com/blader/humanizer claude-seo https://github.com/AgriciDaniel/claude-seo antfu-skills https://github.com/antfu/skills caveman https://github.com/JuliusBrussee/caveman granola mcp https://github.com/proofsh/granola-mcp-server slack mcp https://github.com/atlasfutures/claude-mcp-slack notion claude code plugin https://github.com/makenotion/claude-code-notion-plugin clj-kondo mcp https://github.com/hive-agi/clj-kondo-mcp zapier mcp https://github.com/zapier/zapier-mcp browser agent mcp https://github.com/imprvhub/mcp-browser-agent I haven't tried all of them yet but trying to build a list of what could be useful and then start trying one by one. It kind of reminds me of installing VS Code and a mix of extensions, shortcuts, git tools, etc. The only downside is that I can already see this becoming chaos. But still interesting though. submitted by /u/Product_Enthusiast24 [link] [comments]

non coder, 6 months on max, my favorite use of claude is honestly the boring ai content generator stuff

I am not a developer. I run a small training and content business. Have been on Max since february. Everyone in this sub talks about agents and skills and Claude Code. I do not use most of that. My favorite use of claude is the most boring thing imaginable. It is the ai content generator for the work I find tedious. Specifically: 80% of my client emails. I write a 2 sentence brief, claude drafts, I edit, I send. Training material first drafts. I dump notes, claude builds an outline with timing. The 800 word weekly update to my retainer clients. Claude drafts, I revise. Slack messages I have rewritten 3 times in my head. I tell claude what I am trying to say and what I am worried about. It writes the version I would have if I had 20 more minutes. I will not use claude for: my newsletter intro, instagram captions, anything that needs to sound like me to people who know me, anything emotional. I also use google docs ai for the surface polish on long documents claude has drafted. They are different tools doing different work. What I have not yet figured out: a use case where claude is actually replacing my judgment rather than my typing. I think that's correct? The judgment is the work. Curious what other non coders are doing past 6 months.

i benchmarked Anthropic's tool-search-tool head to head against our own MCP gateway on Opus 4.7. ours held up noticeably better

i'd been running Claude Code with a long list of MCP servers connected. Linear, Notion, GitHub, Slack, a few internal ones. and i was pretty confident that Opus 4.7 plus Claude Code's built in tool-search-tool would just absorb all of it. it mostly did. but i was still hitting ~20% context saturation way too often, before doing any actual work. tried Ratel (our own MCP gateway, we built it for exactly this problem) kind of out of curiosity. then we benchmarked it properly, head to head against Anthropic's own tool-search-tool, same model (Opus 4.7), realistic tool catalogs at 50 / 100 / 180 tools. at the 180 tool pool, measured against the full-catalog baseline: Ratel: near parity on accuracy (about -1.7pp) and roughly -81% input tokens. Anthropic's tool-search-tool: about -8.4pp accuracy. so somewhere around 5x the accuracy hit, same model, same catalog. the takeaway for me: a big context window and a built in tool search are not the same thing as a gateway thats actually optimised for the one job of deciding what enters context. repo plus the full benchmark, numbers and methodology, is here: github.com/ratel-ai/ratel happy to be wrong on parts of this. if you run it differently and get other numbers id genuinely want to see them. submitted by /u/AbjectBug5885 [link] [comments]

Claude Status Update : Elevated errors for Claude Code in Slack on 2026-05-26T05:19:13.000Z

This is an automatic post triggered within 2 minutes of an official Claude system status update. Incident: Elevated errors for Claude Code in Slack Check on progress and whether or not the incident has been resolved yet here : https://status.claude.com/incidents/fl8sx824x72r Also check the Performance Megathread to see what others are reporting : https://www.reddit.com/r/ClaudeAI/comments/1s7f72l/claude_performance_and_bugs_megathread_ongoing/ submitted by /u/ClaudeAI-mod-bot [link] [comments]

Claude Status Update : Elevated errors for Claude Code in Slack on 2026-05-26T01:59:21.000Z

This is an automatic post triggered within 2 minutes of an official Claude system status update. Incident: Elevated errors for Claude Code in Slack Check on progress and whether or not the incident has been resolved yet here : https://status.claude.com/incidents/fl8sx824x72r Also check the Performance Megathread to see what others are reporting : https://www.reddit.com/r/ClaudeAI/comments/1s7f72l/claude_performance_and_bugs_megathread_ongoing/ submitted by /u/ClaudeAI-mod-bot [link] [comments]

Spec: Version Control for AI Agent Intent

AI agents are getting good at writing code. That is not the hard problem anymore. The hard problem is coordination. When you have multiple agents working on the same codebase, who decides what gets built? How do two agents with conflicting opinions resolve a disagreement? How does a human stay in control without reviewing every line before it gets written? Git does not solve this. Git is brilliant at tracking what changed, when, and by whom. But it operates on code that has already been written. By the time a conflict shows up in Git, two agents have already done the work, made assumptions, and written implementations that may be fundamentally incompatible — not at the line level, but at the intent level. I wanted to solve the problem one layer up. Before the code. The Core Idea Every code file in a Spec project has a paired .spec file living right next to it. app/Http/Controllers/HomeController.php app/Http/Controllers/HomeController.php.spec The .spec file is a plain Markdown description of what the code file is supposed to do. It is the source of truth for intent. Agents do not write code directly — they write proposals against the spec. The code only gets written once every agent has explicitly agreed on what it should do. The spec is never “checked out.” It has one canonical state at any moment. Agents read it, propose changes to it, and debate those proposals. When all agents agree, the session locks, the spec is updated, and only then does an implementer generate the code. Code is always the output of consensus. Never the battleground. The Flow A typical session looks like this: An agent reads the current spec and submits a proposal with reasoning attached. Not just what they want to change, but why. A second agent reads the proposal and responds — accepting it, rejecting it with specific objections, or suggesting modifications. If they get stuck, a mediator surfaces the contradiction and helps them find common ground. The mediator has no vote and no authority — it just asks better questions. When every agent has explicitly agreed on the same spec state, the session locks. An implementer reads the locked spec and writes the code. One pass. From a fully agreed specification. This means a few things that feel unusual at first: A build is never produced from a broken or partial spec. If agents cannot agree, nothing gets built. That is a feature, not a bug — better to surface the disagreement at the intent level than to discover it six files deep in an implementation. Conflicts in Spec are semantic, not syntactic. Two agents can touch completely different parts of a spec and still be contradictory. One says the controller should cache responses for 60 seconds. The other says it should always fetch fresh data. No line conflict. Completely incompatible intent. Spec is designed to catch this before a line of code is written. Every message carries reasoning. Proposals alone are not enough. The full session log — with reasoning trails — is what keeps the human comfortable staying hands-off. The Human Role The human operates at what I call a god level. You provide the original request. You can observe at any granularity — project, session, agent, or individual message. You can intervene at any point: rewrite the spec, stop a session, override an agent, shut the whole thing down. And critically, every intervention you make becomes a lesson — captured with full provenance and fed back into future sessions so the system learns from it. The goal is not to remove the human from the loop. It is to move the human up the stack. Mission commander, not task manager. You set the intent. The agents work out the details. You intervene when they get it wrong, and the system gets smarter from each intervention. The Technical Details Spec is built in Rust. Three dependencies: serde, serde_json, and tokio. LLM calls go over raw HTTP via curl — no SDKs. The provider layer is deliberately abstract. Agents, the mediator, and the implementer all talk to the same interface. Swap the provider in config and nothing else changes. Different agents can run on different models. You can run fully local with Ollama for cost control or privacy. Agent identity is explicit. You set SPEC_AGENT_ID before running commands. Without it, Spec errors with a clear message. This is intentional — the system cannot coordinate identity automatically, and a silent fallback to hostname:pid would make consensus unreachable in practice. The lesson graph lives at: ~/.spec/lessons.json It lives outside the repo entirely. Lessons accumulate across all projects and branches. Check out an old branch and you do not lose what the system has learned. Lessons are knowledge about how your agents work, not knowledge about any particular codebase. A hook system lets you plug in your own behavior at defined lifecycle points: • post-agree: fires when a session locks • post-build: fires after code is written • pre-release: fires befor

Built a Claude Meeting Assistant Plugin

I had the itch to build something… works great for me so sharing in case someone else here can benefit. Built with claude, for claude. And yes, it's free. my entire job (product manager) is constantly referencing every context channel we have (slack, emails, CMS, Github, Linear, etc.) --> scoping features, resource planning, digging up those tiny details the stakeholders mentioned they needed… Claude works great as my command center with all the connectors. But the most critical juncture of needing all this is IN my team meetings. what I tried: Granola, Firefly, etc: all just notetakers, no actual in-meeting action Gemini: our team is on Claude/Claude Code, it’s what everyone is used to, and can’t afford another company AI subscription Meeting participant bots: a bot having its own participant window felt intrusive and like we were being watched Claude but outside the meeting: our team is entirely remote and I need our team present during these meetings. I am strongly against having other tools open during meetings unless we absolutely have to. my solution: I created a Claude plugin that lets me dial-in my Claude, so I can have all my MCP’s, skills, connectors, and context available in the chat panel of the meeting, available to the whole team No more I’ll check and we can schedule a follow-up No more spending meeting time looking something up No more list of misc to-do’s post-meeting Everything can be ascertained and delegated in the meeting, by all participants so meetings are actually productive and everyone leaves with zero tedious follow-ups features: Claude can reference both what was discussed in the current meeting as well as chat messages live + historical records of meetings of course Two modes: DIAL which is where you can "@claude" in the chat panel to ask/delegate and WIRETAP which is just recording meeting + chat messages Everything is spawned directly from wherever you Claude Code - meaning your chat before you dial in claude gets loaded in as context (I typically set an agenda/reminders or just use it for prep) and after the meeting you can debrief/recap in the very same chat session Meeting data lives on your machine and your machine only Yes, it uses your subscription and NOT the API; we are within anthropic’s TOS here. Just had to be creative about it limitations: Claude replies under your name but with a visible prefix (see demos below) The plugin opens its own version of a chrome browser to get Claude in there with you FYI Mac only — linux/windows next Google meet only — teams/zoom next Claude only — I want to add codex, openclaw, and local LLMs next How it's going for us now... we got rid of our Granola subscription which we love but was getting costly for us, and I just want less UI’s in my life tbh. So it’s worked great for us so far. Some demos below - give it a spin and give me some feedback if you want! GitHub repo: https://github.com/1-800-operator/operator/fork quickstart run in terminal: # 1. One-line install — sets up the / slash commands curl -fsSL 1-800-operator.com/install | bash # 2. Open Claude Code and type: /dial https://meet.google.com/xxx-yyyy-zzz # 3. Go further — more slash commands: /dial-yolo # no asks, full speed /wiretap # just record, no bot https://i.redd.it/qp998satxc3h1.gif https://i.redd.it/afjsve8yxc3h1.gif submitted by /u/unpopular_parsnip [link] [comments]

Chatgpt vs catch agent

one of the things i’m being asked is why i use an ai executive assistant vs just chatgpt. here's how i see it: chatgpt amazing in drafting documents, emails, longer forms of content, images + general copywriting can be connected to many other tools brainstorming & ideation - great tool to think with about things, amazing general understanding of the world really shines in research - if i want to learn something or get instructions on how to do something (both for work or personal - from how to change things on meta ads to how to fix my washing machine) good for work and for personal catchagent shine on work related admin tasks available on imessage + slack + phone call focused / limited scope - only for work proactive no code, no images, no data analysis, no long form content stronger integration with mail, calendar and notion more responsive to feedback - one chat and one context can speak with other people over email or text bottom line: chatgpt - research, email drafts, long form content or data analysis (tool), personal use case catchagent - calendar, email, tasks, delegation vs other people in or out of the org (admin assistant) submitted by /u/CartographerFeisty66 [link] [comments]