AI app for it and development · no coding needed
Team progress and conversation operations portal
Reduce manual status writing while keeping an accurate, reviewable record of team work.
Made for: Engineering managers and team leads running software teams across several connected work tools
What it does for you
The problem
Progress lives in scattered tools and chat threads, so standups, updates and issue records are rebuilt by hand and follow-ups are lost.
What it gives you
Manager-approved standup summaries, update emails and issue records
What you give it
Connected tool activitychat threadscode issuesteam decisions
Build your own version of KATA Teams, Stepsize AI and more
One app with what these 3 AI tools do, yours to keep and change: KATA Teams, Stepsize AI, Cleo.
Everything these tools do, in one app
- Tool activity dashboard Shows a single self-updating overview of work happening across the team's connected tools.Found in KATA Teams
- Automated standup updates Generates daily standup summaries so teams can reduce or replace standup meetings.Found in KATA Teams, Cleo
- Follow-up tracking Tracks follow-ups so tasks and open items are not forgotten.Found in Cleo
- Conversation summaries Summarizes lengthy chat threads on demand to pull out the key points.Found in KATA Teams
- Team update emails Drafts team update emails from daily work so no one writes them manually.Found in KATA Teams
- Team demo feed Highlights progress in a shared feed so updates can be seen across the organization.Found in KATA Teams
- Decision capture Records decisions, the trade-offs behind them, and the conversation they came from, and flags missing context.Found in Cleo
- Transparent memory Shows the source and a confidence score for each stored fact and lets users correct it.Found in Cleo
- Configurable trust levels Lets teams control how much the assistant observes versus acts on their behalf.Found in Cleo
- Code issue detection Automatically finds and organizes code issues inside the development environment.Found in Stepsize AI
- AI fix suggestions Provides contextual suggestions to help understand and fix bugs.Found in Stepsize AI
- Issue history visualization Visualizes the history and progress of issues so teams can monitor resolution efforts.Found in Stepsize AI
- Issue discussion collaboration Lets team members share and discuss code problems in one place.Found in Stepsize AI
- Existing tool integration Connects to the tools teams already use instead of forcing a single ecosystem.Found in KATA Teams, Stepsize AI
- Quick setup Gets running with minimal setup and maintenance.Found in KATA Teams, Cleo
How it works, step by step
- Show one self-updating dashboard of activity across connected tools
- Generate daily standup summaries from that activity
- Track follow-ups so open items are not forgotten
- Summarize long chat threads on demand
- Draft team update emails from daily work
- Highlight progress in a shared team demo feed
- Record decisions, trade-offs and the conversation they came from
- Flag missing decision context
- Show source and confidence for each stored fact
- Let users correct stored facts
- Set configurable trust levels for observe versus act
- Detect and organize code issues in the development environment
- Suggest contextual fixes for detected bugs
- Visualize issue history and resolution progress
- Host issue discussion in one place
- Connect existing tools instead of forcing one ecosystem
- Compare the reviewed result with the recorded baseline and value assumptions
- Capture corrections and named-owner approval before consequential use
- Export a versioned manager-approved standup summaries, update emails and issue records with source references and unresolved questions
Build it yourself with your AI system
Build this app yourself, no coding needed
Start with a quick version you can try in a few minutes. Like it? Then build the full app by copying and pasting our step-by-step instructions: everything is prepared for you.
Sign in to see how to build it yourself
Build a quick version to try, or get the full app pack for Team progress and conversation operations portal with the step-by-step building instructions. You don't need any technical skills: you copy, paste and answer a few questions. Both are included in the membership.
4 Have it built for you days to a few weeks
Rather not do it yourself, or want it fully tailored to your data, your way of working and your brand? Nexibeo builds Team progress and conversation operations portal with you.
What's in the app pack
Included in the Complete AI Training membership.
- The building instructions your AI follows, step by step
- The questions your AI will ask you about your business before it starts
- A clickable demo you can open in your browser, to see how it should work
- A detailed blueprint of the screens, the information it keeps and the checks it runs
Become a member to get the app packAlready a member? Sign in
The files, for the technically curious
- START-HERE.mdHow to build it with your own AI (read first)3 KB
- README.mdOverview and links3 KB
- questions.mdQuestions to answer before you build3 KB
- prompt-cloudflare.mdThe full build prompt, hosted on Cloudflare26 KB
- prompt-vps.mdThe same build on your own server (Docker)26 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria13 KB
- demo/index.htmlThe working demo on sample data196 KB
Questions
Do I need to know how to code?
No. You copy and paste the prompts on this page into ChatGPT or Claude, and the AI does the building. When it asks you something, you answer in your own words.
What does it cost?
The quick version, the app pack and the step-by-step instructions are for members: you pay the membership price, not a price per app (see the plans). Building the full app uses your own ChatGPT or Claude subscription. Putting it online is often cheap or no cost at the start, and your AI tells you before anything costs money.
How long does it take?
The quick version: about two minutes. The real app: an afternoon for a first version you can use, longer if you want every feature.
Can I change it to fit my business?
Yes. Tell your AI what to change in plain words, like “add a column for the price” or “use our logo and colours”. Or have Nexibeo build and customise it for you.
More detailsHow the AI works, safeguards and what to build first
Reduce manual status writing while keeping an accurate, reviewable record of team work. For engineering managers and team leads running software teams across several connected work tools, convert connected tool activity, chat threads, code issues and team decisions into manager-approved standup summaries, update emails and issue records. The benefit is a testable hypothesis, measured through accepted standup summaries per manager hour and follow-ups closed before due date; do not assume that AI output alone produces business value.
Confirm the buyer's problem and scope, collect connected tool activity, chat threads, code issues and team decisions, then follow this sequence: 1. Show one self-updating dashboard of activity across connected tools. 2. Generate daily standup summaries from that activity. 3. Track follow-ups so open items are not forgotten. 4. Summarize long chat threads on demand. 5. Draft team update emails from daily work. 6. Highlight progress in a shared team demo feed. 7. Record decisions, trade-offs and the conversation they came from. 8. Detect and organize code issues in the development environment. Resolve uncertain cases with qualified reviewers, approve manager-approved standup summaries, update emails and issue records, and measure accepted standup summaries per manager hour and follow-ups closed before due date against a documented baseline.
How the AI works
Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. One connected tool set and one team structure; final status, decision and code-fix judgments remain human. A model suggestion is never a verified fact, professional decision or authorization to act.
Safeguards
Preserve team privacy, source attribution, decision accuracy and usage permissions. Managers approve substantive status, decision and code-fix changes and publication scope. One connected tool set and one team structure; final status, decision and code-fix judgments remain human. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.
What to build first
Pilot scope: One connected tool set and one team structure; final status, decision and code-fix judgments remain human. Implement one approved input format, a bounded representative case set and the first two task modules: show one self-updating dashboard of activity across connected tools; generate daily standup summaries from that activity. Support the remaining modules with operator review: track follow-ups, summarize chat threads, draft update emails, record decisions, detect code issues. Include source references, corrections, basic organization access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.
What it can connect to
Team-owned chat, issue tracker, code repository and calendar tools. Cloud storage, identity provider and notification destinations. Start with file exchange and validate destination specifications before promising direct publishing. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.
The screens in detail
Primary screens: Connected tools and trust settings, Live team activity board, Review and send queue. Use a board view for teams and workstreams, a central activity timeline, and a right-hand panel for sources, confidence and comments. Let users compare a generated summary against the underlying activity. Display draft, changes requested and approved states. Provide a shared demo feed with comments anchored to the relevant item. Make the task-specific outcome manager-approved standup summaries, update emails and issue records visible beside its evidence, review state and value baseline.
