Orchestra - Agentic Product Manager

Inspiration

Software teams do not break because engineers cannot code. They break because coordination does.

The moment a product idea leaves a manager’s head, it starts losing clarity. Requirements get scattered across docs, chats, standups, sprint boards, and half-finished tickets. Managers want visibility but cannot read code. Engineers can build, but they spend too much time translating progress, chasing blockers, and sitting in coordination rituals instead of actually shipping.

That gap is what inspired Orchestra.

We asked a simple question:
What if the product manager itself was agentic?

What if a system could take a manager’s intent, absorb the SRS, break it into technical work, distribute it to the right developers, track execution in real time, and report it back in language any manager could understand?

That is the idea behind Orchestra.

It is not a Jira replacement, not a Copilot clone, and not another passive dashboard.
Orchestra is the intelligence layer between managers and engineers.

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What it does

Orchestra is an agentic product manager built across two connected surfaces:

1. Orchestra Insights — for managers

This is the manager-facing control center where teams can:

• upload an SRS and supporting documents
• chat with the Big Boss Interface in plain English
• view team capacity, sprint health, workload, and developer profiles
• monitor execution without needing to understand the codebase

The SRS upload is one of the most important parts of the system because it creates a single source of truth. Every downstream task, update, and progress report can be traced back to the same product requirement baseline.

2. Orchestra in VS Code — for developers

This is the developer-facing side, where each engineer gets:

• a specialized role-aware agent
• an automatically updated Task List
• a live Orchestra Dashboard for sprint progress, blockers, workload, and activity
• contextual coding support directly inside their working environment

The core intelligence: translation in both directions

Orchestra’s biggest strength is its translation layer:

• Downward translation:
  A manager says, “We need OAuth2 login by the end of the sprint.”
  Orchestra converts that into technical execution: auth flow, session management, frontend UI, backend configuration, testing, ownership, and dependencies.

• Upward translation:
  Developer agents track real execution signals and Orchestra converts them into plain-English progress updates, sprint insights, blocker visibility, and feasibility feedback that even a non-technical manager can understand.

In short, Orchestra turns product intent into engineering execution, and engineering activity into manager-readable insight.

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How we built it

We built Orchestra as a multi-agent system with a defined chain of responsibility:

• Big Boss Agent
  The manager-facing reasoning layer. It reads uploaded SRS documents, interprets product requests, checks feasibility, and acts as the interface between leadership and execution.

• Product Task Manager Agent
  The distribution engine. It takes structured work from the Big Boss, breaks it into subtasks, and allocates that work across developers based on role and context.

• Individual Developer Agents
  Each developer gets their own specialized agent inside VS Code. These agents are role-scoped, task-aware, and designed to track progress, monitor blockers, and support execution in real time.

• Reporter Agent
  The aggregation layer. When the manager asks for a live update, this agent pulls signals from all developer agents and synthesizes them into a clear project-level report.

For the demo, we built the full product experience across both surfaces:

In Orchestra Insights

• Document Uploads to ingest the SRS
• Big Boss Interface to simulate requirement absorption and manager chat
• Team Capacity and Budget / Headcount views for allocation realism
• Developer Profiles to show developer-specific visibility
• Sprint Timeline, Workload, and Overview sections to reflect progress and execution state
• Task Scheduler to demonstrate how work is created and pushed downstream

In the VS Code experience

• Orchestra Chat for specialized developer assistance
• Task List that updates based on work assigned from the manager side
• Orchestra Dashboard showing sprint progress, blockers, workload, and activity

Our stack included:

• React 18
• Vite
• VS Code Extension API
• Monaco Editor
• Lucide React
• Recharts
• Anthropic Claude API

For the hackathon demo, we focused on simulating the full orchestration workflow end to end in a way that feels believable, useful, and product-ready.

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Challenges we ran into

The biggest challenge was making Orchestra feel like a real operating system for engineering coordination rather than just a chatbot with a few extra screens.

We had to solve for two very different users at once:

• managers who think in goals, deadlines, and hiring risk
• developers who think in code, tickets, blockers, and execution flow

That meant the product could not just “answer questions.” It had to translate context across roles.

Another challenge was designing the agent structure clearly. Each agent needed a distinct responsibility:

• one to absorb and reason on product intent
• one to distribute tasks
• one to support each developer individually
• one to aggregate and report progress back up

We also had to be careful not to overcomplicate the demo. The full vision includes self-learning workload allocation, behavioral modeling, skills-gap analysis, and HR-facing insights — but for a hackathon, the challenge was choosing the most compelling slice to demonstrate without losing the bigger story.

Finally, trust was a major design challenge. If a system is going to assign work, flag blockers, or tell a manager that a deadline is unrealistic, it cannot feel generic. It has to feel grounded, specific, and honest.

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Accomplishments that we're proud of

We are proud that Orchestra feels like a real product, not just a collection of AI features.

A few things we are especially proud of:

• Building two fully connected product surfaces
  One for managers and one for developers, each designed around how they actually work.

• Making the SRS the single source of truth
  This gives the whole workflow a strong product anchor instead of relying on scattered instructions.

• Designing a believable multi-agent architecture
  Big Boss → Product Task Manager → Individual Developer Agents → Reporter is a workflow that feels intuitive and operational.

• Simulating end-to-end task orchestration
  We demonstrated how requirements can flow from an uploaded SRS into structured work, into developer task lists, and back into manager-facing progress reporting.

• Building a real translation layer
  Orchestra does not just summarize. It translates manager language into technical execution and technical execution back into manager language.

• Creating the foundation for self-learning coordination
  The system is designed to learn from sprint history, workload behavior, blocker patterns, and developer strengths so allocation gets smarter over time.

Most importantly, we are proud that Orchestra proposes a new model for software teams:

Humans should build and decide.
Software should coordinate.

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What we learned

We learned that the most painful bottleneck in software teams is often not writing code — it is aligning people around the code.

We also learned that AI becomes much more valuable when it moves beyond generation and into orchestration. The real power is not in answering one prompt well. It is in maintaining continuity across requirements, tasks, developers, blockers, and progress updates.

Another major lesson was that translation is a product category in itself. Managers and engineers do not fail because they are bad at their jobs — they fail because they live in different contexts. Building Orchestra showed us how powerful it is to create a system that can sit between those contexts and make both sides more effective.

We also learned that if an AI system is going to influence execution, it has to be opinionated. It has to tell the truth about workload, feasibility, and delivery risk instead of just sounding helpful.

Most importantly, we learned that the future of engineering tools is not just AI that helps individuals work faster. It is AI that helps teams move better together.

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What's next for Orchestra - Agentic Product Manager

The next step for Orchestra is turning the simulated workflow into a live connected system.

That means:

• real SRS ingestion and parsing
• persistent agent memory across sessions and sprints
• live task propagation between Orchestra Insights and the VS Code extension
• stronger behavioral models for individual developers
• smarter workload balancing based on historical sprint performance
• richer execution insights for team health, risk, and capacity planning

Long term, we want Orchestra to become the operating layer above the modern software stack — the system that understands what the team is building, who is best suited to build it, where delivery risk is forming, and how to explain all of that clearly to leadership.

As Orchestra learns from each sprint, task allocation becomes less biased, more precise, and more efficient. The system starts understanding who thrives under pressure, who works consistently, who becomes a dependency blocker, and where the team needs stronger hiring coverage.

The vision is simple:

• managers express outcomes
• developers stay in flow
• Orchestra handles the coordination in between

That is what an agentic product manager should do.

Built With

• anthropic-claude-api
• css
• groq
• html
• javascript
• lucide-react
• monaco-editor
• react-18
• recharts
• vite
• vs-code-extension-api