Deep Work Plan vs Keel — An AI assistant whose memory belongs to you.: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Deep Work Plan and Keel — An AI assistant whose memory belongs to you. — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Deep Work Plan
Dailybot
Open-source, spec-driven methodology that turns any repo into a harness so coding agents finish long-horizon work.
Key features
- Spec-In-Repo Planning: Writes atomic tasks, acceptance criteria, validation gates, and resumable state directly into the repository as a durable plan.
- Drift Resistance: Keeps agents from losing context or abandoning multi-hour tasks by anchoring them to the plan as the source of truth.
- Resumable Long Runs: State survives context resets so any agent can pick up exactly where the previous one stopped.
- DWP-Verify: Produces an objective pass/fail report against the spec so AI-first completion is verified, not assumed.
- Agent-Agnostic: Works with Claude Code, Codex, Cursor, or any coding agent, with no lock-in.
- Open Source: Released under the MIT license and free to adopt in any repository.
Best for
- Large Migrations: Driving multi-file migrations to completion without the agent drifting or stalling.
- New Subsystems: Building a new subsystem against explicit acceptance criteria and validation gates.
- Cross-File Refactors: Coordinating refactors across dozens of files with a durable, resumable plan.
- Verified Delivery: Producing an objective pass/fail report to confirm work meets the specification.
Keel — An AI assistant whose memory belongs to you.
Keel Labs
Local-first desktop assistant for Mac/Windows that stores plain Markdown on your disk and lets you swap models while keeping your context.
Key features
- Local-First Storage: Stores all assistant memory and workspace data as plain Markdown files on the user's disk to ensure portability, offline access, and easy backup/versioning with Git.
- Model-Agnostic Integration: Supports swapping between model providers (e.g., Claude, GPT, OpenRouter, Ollama) allowing users to change inference backends without losing context or notes.
- Plain Markdown Workspace: Uses human-readable Markdown as the native data format, enabling easy editing, searching, and integration with existing text-based workflows and tools.
- Cross-Platform Desktop App: Provides a native desktop experience for both macOS and Windows users optimized for local performance and file-system based storage.
- Privacy-First Design: Keeps context and memory under user control by defaulting to local storage and enabling use of local or self-hosted model endpoints.
- Bring-Your-Own-Model (BYOM): Allows connecting to local or third-party model runtimes (e.g., Ollama or OpenRouter) so users can run models they trust or prefer.
- Open Source Repository: Project source and releases are available on GitHub, facilitating community contributions, audits, and self-hosted deployments.