AI-Driven Project Execution

Ship Complex Work One Phase at a Time

Contextium Projects turn any large build into a structured sequence of phases — each planned, implemented, and reviewed by AI. Your team sees the progress. Your AI never loses the thread.

3
Built-in Agent Roles
1
Phase Per Session
100%
Reviewed Before Marking Done
Projects Per Workspace

AI Builds Faster When It Has a Plan

Without structure, large builds stall. With Projects, every session has a clear next step.

Without Contextium Projects

No Structure for Large Builds
AI sessions wander without a defined scope. Migrations run into UI work. APIs are built before the schema is done.
Progress Is Invisible
No way to tell which phases are done, in progress, or blocked. The whole team is guessing at the state of the build.
No Review Gate
Work gets marked done without verification. Bugs ship. The next phase builds on a broken foundation.
Sessions Start Cold
Every new AI session has to be re-briefed on the whole project. Half the session is catching up, not building.

With Contextium Projects

Phases in Dependency Order
The Planner breaks work into phases — DB first, then API, then UI. Each session has exactly one bounded unit of work.
Live Progress Dashboard
The Projects page shows open and completed phase counts for every project in your workspace. Progress is visible at a glance.
Reviewer Gates Every Phase
Nothing is marked complete until the Reviewer has verified it against the acceptance criteria. Quality is built in, not bolted on.
Instant Session Resume
Load a project workflow and the AI immediately calls get_next_phase — no re-briefing, straight into building.

How AI-Driven Projects Work

Plan once. Build phase by phase. Ship with confidence.

1

Planner Breaks Work Into Phases

The Planner agent runs once at the start. It reads your spec, understands the goal, and writes individual phase files — one per database migration, API endpoint, MCP tool, or UI component — ordered by dependency. Each phase has a title, layer, implementation spec, and acceptance criteria.

Example phase breakdown:
phase-001 DB migration — add phase_file_id to tasks
phase-002 API — expose phaseFileId on task endpoints
phase-003 MCP — auto-resolve linked task on phase complete
phase-004 Web UI — show "Phase" badge on linked tasks
2

Builder Implements One Phase Per Session

Each session the Builder calls get_next_phase to find the oldest pending phase, marks it in progress, builds it completely, then hands off to the Reviewer. One phase, one session — no scope creep.

// MCP tool call
get_next_phase(workflowId)
// → Returns phase-002: "API — expose phaseFileId"
3

Reviewer Grades Before Marking Complete

The Reviewer independently reads the phase file, checks every acceptance criterion against the implementation, then either approves or returns it to the Builder with specific feedback. Only approved phases are marked complete via mark_phase_complete.

Pending
Waiting for Builder
In Progress
Builder working
Complete
Reviewer approved

Everything a Production Build Needs

From spec to shipped — structured, visible, and AI-executable.

Three Shared Agents

Every project uses one set of shared agents — Planner, Builder, Reviewer — reused across all your workflows. No per-project setup, no duplication.

Live Progress View

The Projects dashboard shows open and completed phase counts for every project. Filter by active, complete, or archived to focus on what matters.

Task–Phase Linking

When a Task is promoted to a phase, it's linked automatically. Completing the phase resolves the task — no double-tracking, no forgotten work.

Phase Files as Specs

Every phase is a markdown file in the project library — readable by humans and AI alike. Includes implementation spec, layer, status, and acceptance criteria.

Team Visibility

Every team member sees the same phase list. Assign work, track progress, and hand off between sessions — without Slack threads or status meetings.

MCP-Executable

AI agents drive the entire lifecycle via MCP tools — get_next_phase, mark_phase_complete, and load_workflow. No manual tracking required.

MCP Tools That Drive the Whole Lifecycle

Your AI agents call these automatically — no manual wiring needed

get_next_phase

Returns the oldest pending phase file in the project library. The Builder calls this at the start of every session to pick up exactly where the last session ended.

mark_phase_complete

Tags the phase as passing, increments the completed count, and automatically resolves any linked Task. Called by the Reviewer after approving the implementation.

load_workflow

Loads the full project context — agents, libraries, skills, and active phase list. Every session starts here.

close_session

Finalises the session log with an outcome summary. Keeps a full audit trail of what was built, reviewed, and shipped across every session.

What Teams Build with Projects

Any multi-step build becomes a structured, AI-executable project

New Feature Builds

Break a feature into DB migration → API endpoints → MCP tools → UI components. Each phase is implemented and reviewed before the next begins.

Codebase Migrations

Schema renames, library upgrades, authentication rewrites — break the migration into safe, reversible phases with acceptance criteria at each step.

Audits & Hardening

Security reviews, performance audits, or bug sweeps. Each finding becomes a phase file. AI works through them systematically, one per session.

Multi-Layer Integrations

Adding a new service across API, CLI, MCP, and desktop? Each layer gets its own phase. Progress is tracked across all surfaces in one place.

Your Next Build, Phase by Phase

Stop winging it. Give your AI a plan, a role, and a review gate — then watch it ship. Free to start, no credit card required.

Free plan available · Works with Claude Code, Cursor, and any MCP-compatible AI

Projects Work Better With the Full Stack

Projects are one layer of a complete AI collaboration platform

Every Project Lives Inside a Workflow

Workflows bundle your agents, libraries, skills, and project phases into a single loadable context. When your AI loads a workflow, it gets everything — the phase list, the agents, and the acceptance criteria for each phase.

Learn about Workflows

Pair Phases With Day-to-Day Tasks

Tasks are the lightweight to-dos that sit alongside your project phases. Set due dates, assign owners, and get automatic overdue alerts — while your AI reads the task list every session to stay aligned with the team.

Learn about Tasks

Planner, Builder, Reviewer Are Agents

The three project roles are built on Contextium's agent system. Customise them for your domain, share them across every workflow in your workspace, or browse the Marketplace for ready-made specialist agents.

Learn about Skills & Agents

Ask Questions Across Your Project History

AI Chat lets you query your entire workspace — phase files, session logs, task history — without leaving the app. Ask what changed in the last sprint, or why a phase was marked failing, and get answers grounded in your actual docs.

Learn about AI Chat