The way we work now.
Not another blank chat. ConvOps starts each AI session inside your process, with the rules and remembered context your team already works from.
Continue the vendor DPA review.
I know the step, the rules, and what happened last time.
ConvOps turns the next AI answer into a continuation, not another re-brief.
- 3
- Layers present when work starts: process, rules, context
- 2
- Brain layers underneath: WHAT memories and WHERE routes
- 0
- Blank re-briefs when relevant context is stored
The session does not open blank anymore.
ConvOps turns an AI chat into a work session with an operating layer already attached: the workflow step that is active, the policies that apply, and the remembered context the AI should carry forward.
- Start from the team operating model, not an empty prompt.
- Give the AI process, rules, and context before it answers.
- Make the first response feel like a continuation of the work.
Memories preserve decisions, learnings, preferences, and gotchas.
Brain stores durable knowledge as memories: the decisions a team made, the correction that should not be forgotten, the customer preference that changes the answer, or the implementation gotcha that saves a future agent from rediscovering it.
- Capture durable knowledge from completed work.
- Recall prior decisions before repeating analysis.
- Keep corrections and preferences available across sessions and AIs.
Continue the vendor DPA review.
I know the step, the rules, and what happened last time.
ConvOps turns the next AI answer into a continuation, not another re-brief.
Semantic routes tell agents where the work lives.
Routes are not memories. They are the map: file paths, code locations, MCP resources, docs, commands, or agent handoffs that tell an AI where to go when a topic comes up again.
- Point agents at the right files, resources, or tool handlers.
- Reduce repeated repo spelunking on familiar product areas.
- Separate factual memory from operational routing.
Continue the vendor DPA review.
I know the step, the rules, and what happened last time.
ConvOps turns the next AI answer into a continuation, not another re-brief.
Session start loads the context layer in one move.
At the start of a session, context_query searches both Brain layers: memories for what matters, routes for where to look next. The mechanism stays technical. The experience is simple: work starts with the right background already present.
- Recall relevant WHAT knowledge and WHERE routes together.
- Start with product context before exploring files or tools.
- Give the AI enough context to follow the workflow sooner.
Continue the vendor DPA review.
I know the step, the rules, and what happened last time.
ConvOps turns the next AI answer into a continuation, not another re-brief.
A different AI can pick up with the same remembered context.
ConvOps workflows preserve process state. Brain preserves the context around that state. Together they make handoffs less dependent on copy-pasted summaries and one person remembering every prior detail.
- Resume later without rebuilding the whole brief.
- Hand work to another AI with the relevant context available.
- Keep workflow state and remembered context working together.
Workflows define process. Policies inject rules. Brain preserves context.
ConvOps becomes more than a workflow runner when the operating layer has all three parts: workflows for movement, policies for reusable behavioral rules, and Brain for durable context plus routing.
- Workflows decide what step runs next.
- Policies tell the AI how to behave inside the active step.
- Brain keeps the remembered knowledge and semantic map available.
Active rules on this step
Always cite the task ID in every status update.
Reproduce the bug before proposing a fix.
Every claim must include a source link.
Rules that apply across every workflow in the org.
Rules assigned only to one workflow template.
Injected into the active step exactly when it runs.
Brain makes saved context findable. It does not pretend to know everything.
The value is not omniscience. Brain helps agents retrieve context that has been stored or routed on purpose, then continue through the workflow with better grounding and less repeated discovery.
- Stored memories are explicit knowledge, not mystical awareness.
- Routes point to known places; they do not replace verification.
- Agents still follow workflows, gates, and policies when context is loaded.
See a session start with its operating layer attached
A task resumes with process state, rules, memories, and routes already available. The AI is not waiting for a human to rebuild the whole brief.
Plan Lifecycle
Discuss requirements with the user before planning.
Create architecture and define implementation phases.
Structured review for completeness and correctness.
Run each phase sequentially with implementation agents.
Full acceptance testing against running environment.
Capture context, store learnings, update routes.
Blank chats vs the way work happens now
Without Brain
- Every new session starts by asking the operator to rebuild the brief.
- The AI has to rediscover process, rules, files, and prior decisions.
- Important corrections stay trapped in old chats and summaries.
- Work depends on whoever remembers what happened last time.
With Brain
- The session opens with process, rules, memories, and routes attached.
- Agents start from the team operating model instead of a blank prompt.
- Decisions, gotchas, and preferences become reusable work context.
- Workflows, policies, and remembered context move together.
Frequently asked questions
Explore the rest of the platform.
The way we work now.
Not another blank chat. ConvOps starts each AI session inside your process, with the rules and remembered context your team already works from.