Turn messy inputs into ready work.
Convert specs, discovery notes, refinement conversations, and customer signals into actionable tickets that match your team's templates and acceptance criteria.
How Conductance works
Faster, more integrated product teams.
Conductance.ai helps small teams work like a larger, better-connected product organization: product, design, engineering, testing, go-to-market, and AI members moving through one shared system from idea to shipped learning.
Action, not just answers
What the pod can do for the team.
Conductance gives the whole team more leverage. It can create work from messy inputs, raise bottlenecks, investigate connected tools, kick off development, and stop at the right human review points.
Raise bottlenecks before they stay hidden.
Call attention to aging work, too much work in progress, missing readiness, blocked cards, and flow patterns that explain why delivery is slowing down.
Dig through the tools connected to your live product.
Ask what Mixpanel or PostHog has seen about a feature, what GitHub changed, what a Drive doc says, or what the team decided in Slack.
Kick off work and carry it through the lane.
Start dev work against a card, have AI members shape, implement, debug, report, open PRs, and stop at the human review points your team defines.
Ready day zero
An out-of-the-box operating model that adapts with your team.
Conductance starts with a product operating model already built in, so your team does not have to invent the system before getting value. Each part can be configured, refined, and improved as your team learns.
Start with clear ownership, then tune it.
Use built-in role patterns for product and development work, then adapt responsibilities, guidance, and member assignments as the team changes.
Fit the way your work breaks down.
Begin with useful product-development levels, then map initiatives, epics, stories, bugs, tasks, experiments, or your own structure onto the tools you already use.
Make ready work repeatable.
Start with guided sections for common work types, then refine what each card needs before a person or AI member starts building.
Change the flow as you learn.
Configure the stages work moves through, provider states, WIP limits, recommended skills, and the points where AI members can pick work up.
Keep speed from outrunning judgment.
Use explicit gates so the pod can evaluate readiness, surface missing inputs, and stop at the right human review points.
Add the rituals your team needs.
Start with stand-ups, shaping, product reviews, retros, and ideation, then add custom recurring activities with prep, decisions, and follow-through.
The center
The pod sits across the stack and keeps work connected.
Conductance pod
context, flow, skills, memory, approvals
Slack
Docs
Tickets
Code
Analytics
MCP
Three ways in
Use it where the work already happens.
Conductance is not one more place the team has to remember to check. It gives every person the right doorway into the same shared operating model.
See the system.
Start from Pulse to see what needs attention, active AI runs, approvals waiting on humans, the live work board, operating model, connections, skills, memory, and scheduled work.
Work in the team conversation.
Ask questions in shared channels, summarize decisions, post weekly briefs, notify teammates, follow ticket threads, and keep product learning visible where the team already talks.
Bring the pod into your AI workspace.
Connect through MCP so your personal AI can search knowledge, forecast delivery, create templated cards, add comments, delegate tasks, kick off work, and act with your identity and the pod's guardrails.
Normal day examples
The hook is what your team can ask it to do.
The shift is practical: people stop hunting across tools and start asking the product system for answers, action, and follow-through.
What should we focus on today?
Where is product work getting stuck?
When is this likely to finish?
What did we decide about pricing last time?
Turn yesterday's discovery call into implementation-ready cards.
Create tickets from this spec using our templates.
Turn this customer signal into an experiment.
Shape this into an implementation-ready card.
Create a test plan anyone can run.
What does Mixpanel show about usage of the onboarding checklist?
Where do we have too much work in progress?
Kick off dev work on this card and stop before PR approval.
Notify Sam that this needs approval.
Summarize what shipped this week for the team channel.
Which cards are missing acceptance criteria?
Delegate this follow-up to the product member.
How work moves
The operating model in motion.
1
Signal
Feedback, meeting notes, support themes, analytics, Slack threads, docs, and ideas enter the pod.
2
Product judgment
The team clarifies the opportunity, frames the experiment, and keeps decisions attached to context.
3
Shaped work
Intent becomes specs, template-matched tickets, acceptance criteria, test plans, and measurable implementation work.
4
AI-assisted execution
Members help research, shape, build, debug, report, kick off development sessions, and keep delivery moving through connected tools.
5
Approval
Human review stays explicit for judgment, writes, state changes, releases, and sensitive follow-through.
6
Learning
Results, decisions, and lessons become memory for the next product loop instead of disappearing.
AI development lane
A development squad inside the operating model.
Conductance can work with the AI coding systems your team already uses while also running remote development sessions against cards. The dev lane is connected to the same tickets, workflow phases, acceptance criteria, GitHub context, and approval points as the rest of the pod.
shape a card into an implementation-ready spec
start a remote session against a card
debug an issue using repository context
open a PR from completed work
pause at review, release, or other human gates
For each person
The whole team gets leverage from the same context.
See the product system without adding management drag.
Ask what matters, what is blocked, what is likely to finish, and what needs a decision or an action.
Turn signals into strategy, experiments, and clearer work.
Use meeting notes, docs, decisions, analytics, and delivery state to shape tickets and experiments.
Get better inputs and faster follow-through.
Work from stronger specs, visible readiness, AI-assisted implementation, remote sessions, and linked PRs.
Stay connected to what is launching and what the team learned.
Ask for briefs, launch context, customer themes, shipped-work summaries, and follow-up tasks.
Governed AI
Not loose automation. A safer way to let AI act.
Writes need accountability.
Actions are attributed to the person or member acting through the pod.
Some work needs human judgment.
Approval loops keep sensitive changes, posts, and state transitions reviewable.
Teams need consistent inputs.
Templates, exit criteria, and the operating model shape work before it moves.
Development should not outrun the system.
AI work can stop at review, approval, release, or any phase where people need control.
Questions should not get lost.
Durable asks can become cards, threads, scheduled work, or memory.
For AI-forward product teams
Give your team one place to ask, act, decide, and learn.
Conductance connects daily work to the full product loop, with the tools your team already uses and the approval points people still need.