You need to trust an outcome, not merely watch a terminal.
Your work spans real repositories, repeatable workflows, quality gates, and human approval, on one project or across a fleet.
Plan → run → audit → review
A local control panel for planning AI coding work and checking whether it really passed.
Point it at a codebase, give it a spec, and choose the agent or model you already use. aidd builds the backlog, runs bounded agent sessions, keeps features open until the gates pass, and leaves behind the run history you need later. In current market language it is a local, agent-agnostic agentic development environment: delegated work and durable results are the primary units, not files in an editor. Your projects, your keys, your machine.
The field
In 2026 you can rent a cloud agent by the task, put a board over your terminal agents, or generate a clean spec. Those are useful pieces. aidd is for the awkward part after that: turning the spec into work, running the agent under limits, and making the result pass the project gate.
Your work spans real repositories, repeatable workflows, quality gates, and human approval, on one project or across a fleet.
aidd is not the coding agent. If you do not need an evidence trail, it is more process than you need.
Hosted agents make it easy to hand off work without keeping a local machine running. Pricing, sandbox access, and the evidence returned with a run vary by provider.
aidd: uses the agent subscription you already have, on your machine, under iteration and wall-clock caps with the run cost reported as it accrues.
Kanban boards, worktree apps, and terminal managers provide useful views of active sessions and diffs. Planning depth, automated gates, and platform support depend on the product and configuration.
aidd: keeps a feature open until tests, typecheck, lint, and browser verification pass.
Spec-driven kits help turn an idea into structured requirements. Execution and verification are usually handled by the agent workflow that consumes those artifacts.
aidd: keeps the spec connected to dependency-ordered work, acceptance criteria, gate checks, and a decision queue for the calls a tool should not fake.
| What you need | Cloud agents | Agent boards | Spec kits | aidd |
|---|---|---|---|---|
| Where the work runs | Provider-managed environment | Your machine | Your repo | Your machine, your keys |
| Spec becomes a backlog | Task or issue based | Often user-managed | Requirements and planning artifacts | Dependency-ordered, with acceptance criteria |
| “Done” means | Provider workflow completed | Project-defined review | Requirements are ready for execution | Tests, typecheck, lint, and browser gates passed |
| Cost model | Per-task metering | Free, futures vary | Free CLI | aidd is free; your existing agent plan, metered per run |
| Run receipts | Provider-dependent | Session history | Planning artifacts | Commits, iterations, tool activity, cost |
| Windows | Browser-accessible | Product-dependent | Varies | Smoke-tested, first-class |
High-level category snapshot, July 2026, rather than a feature-by-feature comparison. Examples include Devin, OpenAI Codex cloud, Google Jules, Copilot coding agent, Factory, Vibe Kanban, Conductor, Sculptor, Claude Squad, GitHub Spec Kit, AWS Kiro, and BMAD. Capabilities and pricing change; aidd is focused on the local planning, run, and verification loop.
The loop
aidd turns intent into backlog items, selects runnable work, launches bounded agent sessions, checks the result, and parks anything that needs a human call.
Add application roots in Settings. Any folder with an
.aidd/ contract becomes a project,
including foreign stacks.
Onboarding turns a plain-language spec into dependency-ordered feature work with verifiable acceptance criteria.
Use Claude Code, Cline, Codex, Grok, OpenCode, or KiloCode, or OpenAI-compatible endpoints including OpenAI, LM Studio, and Ollama.
Features complete only after the project gate passes: tests, typecheck, lint, and browser-level verification when the project has a UI to drive.
Every run keeps commits, iterations, tool activity, cost, and an honest summary. Unclear work lands in the decision queue.
Receipts
aidd built and repaired real applications through seven different creation lanes. The runs were there to find rough edges, file the failures, fix them, and leave a public trail.
All seven are published in full - app snapshots, run ledgers, iteration evidence, and scrubbed transcripts - in the build-proofs repository, including the lane that failed. This is first-party evidence, not a benchmark or an independent audit.
| Lane | App | Stack | Result |
|---|---|---|---|
| Fresh scaffold from a spec | Habit tracker | Bun + TS + React | 25/25 features passing, gate clean, roughly 2.5 h |
| Third-party template init | Kanban board | Vite + React | 23/23 features, 10/10 headless acceptance scenarios in the gate |
| Full-stack template init | SMB infrastructure dashboard | Bun + Elysia + React + Drizzle | 26 features passing plus one retained remediation record, 30-step gate green |
| Existing-codebase ingest | Flask tutorial app | Python + Flask |
Profiled the foreign stack, produced a grounded security
audit, then fixed findings with pytest as the gate. Zero
writes outside
.aidd/.
|
| GitHub-template clone | Pantry tracker | PowerShell + Pode + htmx | 26/26 features, Pester 88/88, analyzer clean |
| Local model only | Markdown TOC tool | Bun + TS, LM Studio, no cloud calls | 0/14 features. Five coding runs finished nothing, and the completion contract refused to record success. Published exactly as it ran. |
| Agent-driven build | Margin calculator | Bun + Elysia + React + Drizzle | 29/29 features across 48 supervised iterations, gate green at the end |
Trust model
The default posture is deliberately plain: local data, no account, explicit model backends, bounded runs, and documented write surfaces.
The runtime, panel, ledger, and project metadata live locally. Network traffic goes only to the model backends you configure.
There is no aidd account and no hosted control plane. It sends no
telemetry and does not phone home; network traffic comes only from
providers or integrations you configure, or downloads you initiate.
The write allowlist is documented, including what lives under
.aidd/ and when source can change.
Iteration caps, wall-clock caps, dirty-tree guards, and parked decisions stop a run outright; cost and token budgets are warn-only, reported against the run rather than cutting it off mid-edit.
Included under FSL
Run aidd supervised or unattended, on one project or across a fleet. Every capability ships together under FSL. You provide access to the AI providers you choose.
One product
Everything aidd does ships together, for any number of projects and machines.
Source-available under FSL-1.1-ALv2, converting to Apache 2.0 two years after each release.
Install from source.aidd/ metadataGet it
Windows 11 + PowerShell 7 is the current smoke-tested path. Install Git and Bun 1.4.0 or newer, then run aidd directly from its source checkout.
git clone https://github.com/NomadicDaddy/aidd.git C:\Tools\aidd
Set-Location C:\Tools\aidd
bun install
bun run start:web
# Open http://127.0.0.1:3210
aidd ships under
FSL-1.1-ALv2: available for any use except making it available to others as a
competing commercial product or service, and each version automatically
becomes Apache 2.0 two years after release. The
.aidd/ contract format is an open spec
anyone may implement. Spernakit, the companion full-stack template, is
MIT.