Medium
TAS-1
Plan the authentication refactor
Product backlog
Operations agent
Product backlog
Ship faster with coding agents. Keep control of every change.
Coordinate Codex, Claude Code, and the other workers you already use across backlog, approvals, allowed changes, and run history.
Live 201 tasks completed in the last 7 days $0.44 median cost per task 70% approved without human actionHand your backlog to agents, keep the final say
What follows is one full run you can watch, start to finish. Task Machine ships a feature off the backlog on its own, opening a pull request and bringing back only the review decision that genuinely needs you.
You hand off the work
Describe the recurring job in plain language, including what needs to happen, how often it runs, and when a person should step in. Task Machine keeps that brief attached to every run.
Brief it once, it runs on every cycle.
Works with
Task Machine turns it into a deterministic workflow
Task Machine turns your brief into a deterministic workflow with clear steps to implement the feature from the ticket, add the tests, and let a verifier run the full suite before it opens a pull request. The same ordered steps every time, pausing only where a step needs your call.
The same deterministic workflow, every time.
Task Machine knows the blast radius of every step
Before it acts, Task Machine weighs how far each step reaches. A branch waiting in review changes nothing you can't undo. Merging into your codebase does. It handles the low-stakes work itself and only brings you the changes that genuinely carry weight, so you are never pulled in without a reason.
Low-stakes steps never reach you.
Every critical decision waits for your approval
Before the agent writes any code, it brings you the plan and its blast radius, with just enough context to decide in seconds. Approve the plan and the build starts. Nothing gets implemented until you sign off, and only the plans that carry weight wait for you.
You only receive what needs your attention.
The finished change comes back for your review
When the change is ready, the agent opens a pull request and brings the review to you: the plan, the diff, the test results, and a screenshot of the change. Approve to record your sign-off on that exact head, or request changes to send it back. The review is its own step, separate from the plan approval, and the call stays yours.
The review is yours, separate from the plan sign-off.
Task Machine stays inside the budget you set
You set a spending cap, and the workflow works inside it, tracking every cost against your limit as it runs. It pauses to ask before it would ever cross that line, so the spend is something you decide up front, not something you discover on a bill.
You always stay in control of your budget.
Task Machine works from what your company already knows
Its changes come from one shared knowledge base with your architecture notes, past pull requests, each project's conventions. It is the same source your team and every agent work from, not guesses.
One shared source of truth for every agent and teammate.
When it hits a wall, it asks for the right hire
Partway through, the features kept needing a first-pass review no agent was set up to run. Rather than guess, Task Machine proposed a dedicated code-review agent to own it. You approve or decline. It grows its own team, on your say-so.
It proposes the hire, you approve it.
When an agent needs credentials, it asks first
When the workflow reaches GitHub, the agent explains which credentials it needs and why. Approve one use, set a time limit, allow ongoing access, or say no.
Your credentials stay protected and secure.
Agents earn autonomy as they prove themselves
Every approval you give is evidence. Once Task Machine has your review calls right often enough, it asks to merge the low-risk changes on its own, and you grant or hold that step up from your inbox. Independence is earned on a track record, never assumed.
You approve less as it earns your trust.
Ship the next feature
Chat with Strategy
Ship the next feature off the backlog: implement it from the ticket, add the tests, and open a pull request for review.
I'll turn this into a repeatable workflow and the task to run it. Here's the plan to approve.
Reading the ticket and the repo
Deterministic workflow
Run 23-
Done
Implement the feature off the ticket
Agent
-
Done
Add tests for the new behavior
Agent
-
Waiting on you
The pull request needs your review
Approval
-
Queued
The full test suite passes
Verifier
Approved. Setting up the task.
Created the task and its first run. Opening it now.
Task
TAS-142: Ship the next feature
Message an agent…
Strategy
Tasks
TAS-142: Ship the next feature
TAS-142: Ship the next feature
Waiting
In progress
Waiting
Done
Ship the next feature off the backlog: implement it from the ticket, add the tests, and open a pull request for review.
Attachments
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Task history
Activity
Runs
1 task update
2 task updates
3 task updates
You were assigned: Ship the next feature
Task Assigned · 7 mins ago
Workflow run
Coding agent · Running
August 4, 2026 at 3:28 PM UTC
Workflow run
Coding agent · Succeeded
August 4, 2026 at 3:28 PM UTC
Pull request review
7 mins ago
Merge the pull request for saved filters?
The agent built the saved-filters feature and the suite is green, but it touches the query layer. Approve or reject before it merges.
Pull request review
just now
Merge the pull request for saved filters?
Approved by you
Coding agent
August 4, 2026 at 3:28 PM UTC
Implemented saved filters and added its tests. Opened pull request #128 and ran the full suite: all green.
Coding agent
August 4, 2026 at 4:02 PM UTC
Backlog moving: 16 → 4 open tickets. 96% handled autonomously, and the one change that touches the query layer came to you.
Reply
A
Write a comment…
Pull request review
Merge the pull request for saved filters?
These details were reported by the agent for this exact head. The source link remains available for optional inspection.
Approve records your decision for this reported head; it does not merge the pull request. Request changes returns the work to the agent with your feedback.
GitHub #128
Open · Review pending
- Change summary
- Adds saved filters to the task list so a member can name, store, and re-apply a set of task filters. Includes the query-layer change and its covering tests.
- Branch
- feature/saved-filters
- Changed files
- 7 files
- Lines changed
- +214 −38
- Reported CI
- Passing
- Agent reported
- August 4, 2026 at 15:28 UTC
- Agent pre-review
- Passed by Coding agent
- Reviewed head
- 9f3c1a7b2e4d
Review evidence
saved-filters-after.png
218 KB
Screenshot of the change, attached for review.
Approved by you
Inbox
Needs action
3
Proposals
1
Unread
3
All
Add a code-review agent?
Add a code-review agent?
Credential needed: GitHub
Credential needed: GitHub
Autonomy increase: Coding agent
Autonomy increase: Coding agent
Merge the pull request for saved filters?
Merge the pull request for saved filters?
Review agent proposal
New agent proposal · 5 mins ago
Adding the agent puts it on your team under the same limits and approvals.
Proposed agent
Code-review agent
Reviews changes before they merge
- Why
- Mid-run the features kept needing a first-pass review no agent is set up to run. It's proposing a dedicated code-review agent to own it.
- Proposed by
- Coding agent
Added. Code-review agent joined your team.
Review credential request
Credential needed · 3 mins ago
Granting lets the agent use the connection. The secret stays in the vault and the agent never sees it.
GitHub
The agent is requesting access to GitHub to work in your repositories.
Granted. The agent can use GitHub.
Review autonomy change
Autonomy Change · 1 min ago
Apply change updates which actions this agent can take without approval. Keep current level leaves every permission unchanged.
Agent
Coding agent
Balanced
What changes
- Autonomy
- Balanced Autonomous
- Merge changes under 50 lines
- Ask first Auto-approve
- Open pull requests
- Ask first Auto-approve
Evidence behind this recommendation
- Recent decisions
- 152 of 154 approved
- Pull request review
- Approved
- Pull request review
- Approved
- Pull request review
- Rejected
Applied. Coding agent moved up a level.
Discuss your strategy with Task Machine
Talk through what you want to achieve, what keeps slipping, and where your team needs help. Task Machine turns the conversation into tasks and playbooks, bringing together the agents, workflows, teams, and company knowledge needed to run the work.
You hand off the work
Describe the recurring job in plain language, including what needs to happen, how often it runs, and when a person should step in. Task Machine keeps that brief attached to every run.
Brief it once, it runs on every cycle.
Works with
Task Machine turns it into a deterministic workflow
Task Machine turns your brief into a deterministic workflow with clear steps to implement the feature from the ticket, add the tests, and let a verifier run the full suite before it opens a pull request. The same ordered steps every time, pausing only where a step needs your call.
The same deterministic workflow, every time.
Task Machine knows the blast radius of every step
Before it acts, Task Machine weighs how far each step reaches. A branch waiting in review changes nothing you can't undo. Merging into your codebase does. It handles the low-stakes work itself and only brings you the changes that genuinely carry weight, so you are never pulled in without a reason.
Low-stakes steps never reach you.
Planning & review
ElevatedBlast radius
High
Agent's assessment
This merges a change into your codebase, so it waits for your review before anything lands.
When an agent needs credentials, it asks first
When the workflow reaches GitHub, the agent explains which credentials it needs and why. Approve one use, set a time limit, allow ongoing access, or say no.
Your credentials stay protected and secure.
Every critical decision waits for your approval
Before the agent writes any code, it brings you the plan and its blast radius, with just enough context to decide in seconds. Approve the plan and the build starts. Nothing gets implemented until you sign off, and only the plans that carry weight wait for you.
You only receive what needs your attention.
Task Machine stays inside the budget you set
You set a spending cap, and the workflow works inside it, tracking every cost against your limit as it runs. It pauses to ask before it would ever cross that line, so the spend is something you decide up front, not something you discover on a bill.
You always stay in control of your budget.
Agents earn autonomy as they prove themselves
Every approval you give is evidence. Once Task Machine has your review calls right often enough, it asks to merge the low-risk changes on its own, and you grant or hold that step up from your inbox. Independence is earned on a track record, never assumed.
You approve less as it earns your trust.
When it hits a wall, it asks for the right hire
Partway through, the features kept needing a first-pass review no agent was set up to run. Rather than guess, Task Machine proposed a dedicated code-review agent to own it. You approve or decline. It grows its own team, on your say-so.
It proposes the hire, you approve it.
Task Machine works from what your company already knows
Its changes come from one shared knowledge base with your architecture notes, past pull requests, each project's conventions. It is the same source your team and every agent work from, not guesses.
One shared source of truth for every agent and teammate.
Humans and agents work as one team
Start with one agent on one repeatable job, or build a mixed team where people and agents contribute, review, approve, and lead. Task Machine fits how your team works today, and you decide where agents act independently and where people stay involved.
Humans and agents share the work. You decide how.
We use Task Machine to run Task Machine
Pulse shows what our agent team gets done, how often it works autonomously, and how little each task costs. The numbers come from the real work behind this company.
Open Task Machine PulseLive tasks
0
Tasks completed
Last 7 days
201
Task cost
Median cost per task
$0.44
Autonomy
Agent work approved without human action
70%
“Building is the easy part. Marketing, support, and sales follow-ups kept slipping. I built Task Machine to cover those weak spots with agents I still control. Now I get more done and stay focused on strategy.”
Fabian Schucht
Founder, Task Machine
More about why I'm building this