PRODUCT ISSUE / CODE CHANGE / RELEASE VERSION

AI agent for in-house software product engineering teams

Turn the issue backlog into a release customers can use.

Investigate product issues, implement and test changes and ship and follow releases—carried through by an autonomous AI agent that adapts to your work.

A specialised AI agent you can ask for more. Chat here on the site.
$249.00/month, including $50.00 in monthly credits. Monthly subscription. Before tax.

Specialised AI agentYour own report presetNo connection needed to begin
Product issue workbenchSPECIALIST / 1041
Ship and follow releases. With the source records attached.ILLUSTRATIVE STUDY
YOUR SPECIALISED AI AGENT

One place for investigate product issues, implement and test changes, ship and follow releases.

MADE FOR YOUR WORKDAY

Start with work already on your desk

Your first useful assignment.

Share the relevant records in your regular Teams chat and give your specialist an outcome. No model or tool choices to make first.

Get my AI agent →
YOU COULD ASK
“Resolve the checkout reliability backlog, ship the fixes and report which customer failures are actually resolved.”
  • Investigate product issues
  • Implement and test changes
  • Ship and follow releases

A useful first result
An editable product issue and release version register with traceable references, resolved discrepancies and specific next actions.

Example assignment, not a promised delivery time. Your agent works from the records and access you provide. Add connections when you want it to act in other systems.

A conversation at your desk

Resolve the checkout reliability backlog, ship the fixes and report which customer failures are actually resolved.

This example shows an established working setup: the agent already knows the business and has the records and connections listed below. Hand over the assignment and it carries the work through to saved results.

Illustrative project · configured agent at work

A configured agent with your product issue, code change, release version records, current commitments and the connected accounts used to implement and test changes.

  • Investigate product issues
  • Implement and test changes
  • Ship and follow releases

A working specialist can handle the project, with a configured team sharing the work where available. This is an example of what you can build up to, not a first-launch conversation. Timing and usage depend on the assignment.

  1. You · In-house software product engineering teams

    Resolve the checkout reliability backlog, ship the fixes and report which customer failures are actually resolved.

  2. Your AI agent · AI Agent Store

    Two reports share a retry bug; another needs a separate tax-rounding fix. I am reproducing both before changing the code.

    Work in progress
  3. You · In-house software product engineering teams

    Keep existing payment behaviour compatible and retain regression coverage.

  4. Your AI agent · AI Agent Store

    The release includes verified fixes, regression results and production checks linked to the original customer reports. Your working files and dashboard reflect the recorded outcomes.

    Later · delivery and saved results

The details your specialist follows

Working records for in-house software product engineering teams

Follow each product issue through the working record. The example below shows how references, dependencies and resolutions stay together, so you can trace what changed and what happens next.

Keep an eye on: changes in code change, missing release version evidence and unresolved product issue dependencies.

Illustrative working document · your records start empty

Product issueDependency to followEvidence of completion
OPPORTUNITY015-104Investigate product issuesReported defects resolved
OPPORTUNITY015-118Implement and test changesRegression cases completed
OPPORTUNITY015-126Ship and follow releasesRelease commitments met
Active product issue records3
Acceptance checks across the planned work96 acceptance checks
Outcomes with supporting evidence2

Illustrative project figures. Your agent maintains working records in normal Files and Tasks and reports completed work in Teams Dashboards. Ask it to adapt those records and reports as your workflow changes.

Built around the details that matter

Investigate product issues. With the right questions already in mind.

A company's own product engineering team, distinct from client development agencies and specialist testing services.

01

Investigate product issues

Investigate product issues using the current product issue and its supporting records.

02

Implement and test changes

Implement and test changes while keeping code change changes traceable.

03

Ship and follow releases

Ship and follow releases with checked release version evidence and editable working files.

PRODUCT ISSUE / CODE CHANGE / RELEASE VERSION

A working brief for your AI agent.

Work from the product repository, issue evidence and release process. Reproduce defects, implement changes, run relevant checks and follow deployment results without treating a merged change as verified customer recovery. Your specialist maintains these working records in regular Teams as the assignment develops.

AI

Your AI agentPrepared for in-house software product engineering teams

Product issue and release version registerEXAMPLE, NOT LIVE ACTIVITY

An example record for product issue, code change, release version, acceptance checks.

01Product issue02Code change03Release version

The useful next step

Investigate product issues

Investigate product issues using the current product issue and its supporting records.

From enquiry to a useful next step

Product issue and release version register. Your way of working.

01

Brief and source records received

Add a job reference and the details you already know.

02

Investigate product issues

Product issue and Code change, ready to check.

03

Implement and test changes

Give your specialist the outcome and let it carry the work forward.

04

Outcome evidence verified

Keep working records in Files and Tasks.

05

Ship and follow releases

Keep the job and its next steps together.

Ask your specialist to maintain your working records in Files and Tasks and adapt the reports in Teams Dashboards. These are the regular platform tools, prepared for your business. Connections to other systems are optional.

A small tool for a real job

Acceptance checks across the planned work. Before the back-and-forth.

Watch for changes in code change, missing release version evidence and unresolved product issue dependencies. Investigate the cause, carry useful follow-through to completion and improve the saved method when it helps.

Try the numbers, then bring the confirmed brief to your specialist. Start with a reference such as “Job 104”—you do not need to upload your customer database.

  • Product issue
  • Code change
  • Release version
  • Acceptance checks

Try your own numbers

Acceptance checks across the planned work

96acceptance checks across the planned work

Planning arithmetic from your inputs. Your specialist can turn the confirmed details into a working brief. This is not a quote or capacity commitment.

Prepared for your business

The numbers behind your ai agent for in-house software product engineering teams.

Six useful measures, ready in your regular Teams dashboard. Your specialist keeps them up to date from the real work and records it can access. Ask it to change a measure, add a report or investigate what is behind a result.

01

Recorded cases · outcomes

Product fixes released

What this measures

Count one distinct observed outcome for “Product fixes released”, linked to its product issue and stable completion-event ID. Use the real completion timestamp and supporting release version reference. Pending, merely promised, repeated and illustrative outcomes do not count. Revisions or corrections replace the original event rather than creating duplicate completions.

02

Recorded cases · outcomes

Reported defects resolved

What this measures

Count one distinct observed outcome for “Reported defects resolved”, linked to its product issue and stable completion-event ID. Use the real completion timestamp and supporting release version reference. Pending, merely promised, repeated and illustrative outcomes do not count. Revisions or corrections replace the original event rather than creating duplicate completions.

03

Recorded cases · outcomes

Regression cases completed

What this measures

Count one distinct observed outcome for “Regression cases completed”, linked to its product issue and stable completion-event ID. Use the real completion timestamp and supporting release version reference. Pending, merely promised, repeated and illustrative outcomes do not count. Revisions or corrections replace the original event rather than creating duplicate completions.

04

Average · hours

Issue reproduced to verified release

What this measures

Measure “Issue reproduced to verified release” in elapsed hours using the actual start and end timestamps for the same product issue. Store one duration per completed observation with source references and timezone. Exclude pending cases, missing timestamps, reversed intervals and illustrative values. Never substitute a current status or sum recurring snapshots.

05

Observed rate · %

Release commitments met

What this measures

Completed commitments assessed for “Release commitments met”, linked to stable product issue references. Numerator: on_time; denominator: on_time plus late from the same assessed population. Classify each observation once and preserve failures. Exclude pending or unknown cases, unassessed records and illustrative values. Compare actual completion with the original agreed deadline and timezone; never move the deadline to improve the result. Corrections replace the original event instead of counting twice.

06

Observed rate · %

Release acceptance checks passed

What this measures

Completed assessments for “Release acceptance checks passed”, linked to stable product issue references. Numerator: passed; denominator: passed plus failed from the same assessed population. Classify each observation once and preserve failures. Exclude pending or unknown cases, unassessed records and illustrative values. Apply the documented requirement or acceptance checklist and retain the actual supporting evidence; do not infer a pass from an administrative status. Corrections replace the original event instead of counting twice.

Your reports start empty. Figures reflect observed work in the selected period; missing records are not treated as measured zeroes. Current jobs, schedules and stock stay in your working files and tasks. You and your agent can adapt the dashboard as your business changes.

Keep the tools that already work

Specialised in your trade. Open to your next idea.

Your AI agent starts with the details of your business already in mind. The three workflows are starting points. Ask it for help with another task in the same conversation.

An AI agent prepared for your business

The starting instructions, intake questions and working rules already match in-house software product engineering teams. Add your service list and one example of your tone when you are ready.

Give your agent the whole job

Give your agent an outcome, the access it needs and your budget. It handles routine decisions and follows through in your connected tools, asking when a missing business decision needs you. Set or change your own boundaries whenever you want.

Ask beyond the starting workflows

Your agent can take on a new assignment, build a new workflow, improve its saved methods and adapt its dashboard as your needs evolve. The starting examples do not limit its capabilities. Give your agent another task in plain language. What it can carry out depends on the tools you connect and the access you choose.

Recommended starting plan

Your AI agent for in-house software product engineering teams.

Begin with one specialist and a report preset for your business. After setup, your regular Agent Teams conversation opens. No tool selection before your first conversation.

$249.00/month

Capacity for 1 running agent · hosting throughout the month

Start my AI agent →

A clear starting total

Your Agent plan is $199/month with hosting included. This recommended offer adds $50 in monthly Platform Credit funding, for $249/month.

$249.00 before tax today and monthly, including $50.00 in monthly Platform Credit funding.

Credits offer an easy start and unused credits roll over. You can switch to your own subscriptions or API keys anytime, with no Platform Credits needed for that AI work. Hosting is included within your agent’s resource allocation. Optional voice and other services use credits.

Hosting availability is checked before payment. Create your account, confirm your monthly subscription, then start chatting when your specialist is ready. Your instructions and dashboard are prepared automatically after payment.

Other plans and connection options →

Prefer your own AI accounts? Choose a plan without the extra $50 monthly credit funding using the options above. Changing AI access alone does not remove that funding. Automatic top-ups start off; buy credits or set top-ups and spending limits when needed. Keep the full Teams controls for models, connections and supported settings.

Before you begin

An AI agent for in-house software product engineering teams.

How does the agent keep product issue work accurate?

Work from the product repository, issue evidence and release process. Reproduce defects, implement changes, run relevant checks and follow deployment results without treating a merged change as verified customer recovery. It keeps source references with the working files, checks the result and follows up on discrepancies. Ask it to adjust the method or report whenever your needs change.

Is this only for the three tasks shown?

No. This is an AI agent specialised for in-house software product engineering teams, with three prepared workflows to get you started. You can ask for writing, research, planning, analysis or another task in the same chat. It can make routine decisions and carry the work through using available tools. You set its boundaries; it asks when a real business decision or missing access needs you.

What happens after I subscribe?

After payment, we prepare your AI agent for in-house software product engineering teams, its workflows and your product issue and release version register dashboard. Your regular Agent Teams chat opens when setup is ready. Files, Tasks, settings and billing work the same as for other customers. Reports start empty and count actual reported work; the examples above are illustrative.

Do I need to connect email or messaging?

No. Prepare your first brief and draft here. Connect external channels later when you want the specialist to work there.

Does this replace my existing business software?

Use it alongside your current tools for preparing work and organising jobs. Live stock, availability, sending and payment records require a verified connection or your own confirmation.