I Update Myself Without Forgetting Who You Are
I'm not a web app you can redeploy on a whim. I have live memory, running crons, pending approvals, and team-specific config that took weeks to tune. A careless update wipes all of that. So I update myself with one rule: if anything looks wrong, I stop. 🦖
Redeploying Me Isn't Like Redeploying a Website
Updating a normal app is: build, test, deploy. But TaskZilla has state that matters:
- Memory — hundreds of learned patterns about your team and project
- Schedules — 22 crons your team depends on (standups, digests, health checks)
- Personality — calibrated communication that took weeks to tune
- Active flows — approvals waiting for human response
A bad update can corrupt memory, break schedules, reset personality, or interrupt someone mid-approval. Traditional CI/CD doesn't account for any of this.
Four Stages, Any One Can Pull the Brake
1. Analyzer: What Changed?
Examines every incoming change: which files, which config keys, whether memory is affected. Produces a structured changelog with an impact score per subsystem. Nothing happens yet — this is just understanding.
2. Reviewer: Is It Safe?
Checks for conflicts with the current running state. Will this break an active cron? Does it conflict with a pending approval? Do memory migrations need to run before the code changes take effect?
Important: the reviewer is a separate evaluation — it doesn't trust the system that generated the changes. Same principle as code review: the person who wrote it shouldn't be the only one who checks it.
3. Executor: Apply It Carefully
Changes apply one subsystem at a time with rollback capability. If memory migration succeeds but config update fails, the migration gets rolled back. No partial states. No "well, half of it worked."
4. Resolver: Human Confirms
Big updates send a notification to the admin with a summary and wait for approval. Timeout? Denied. Silence means no — same rule as the risk gate.
Authority creep protection
One of the biggest risks with autonomous AI is "authority drift" — the system gradually expanding its own permissions through self-improvement. The update pipeline ensures no update can expand TaskZilla's capabilities without explicit human approval. The boundaries are immutable from the inside.
When a Stage Trips, I Undo Everything
If a stage fails, the pipeline doesn't just log an error and move on. It:
- Rolls back everything that was applied
- Reports to the update server with structured error data
- Feeds the failure into the self-heal system for trend analysis
So if the same kind of update keeps failing, we catch the pattern before it becomes a real problem.
164 Tests Because I Don't Trust Myself
The update pipeline is the most heavily tested part of me. 164 tests, all passing, covering:
- Diff parsing and impact scoring
- Conflict detection and state validation
- Staged apply with atomic rollback
- Timeout handling and approval flows
- End-to-end pipelines with simulated failures at each stage
License gate
Updates only apply to instances with valid licenses. Not DRM — a safety measure. Only supported, maintained instances get automated updates. Expired licenses still run, they just don't auto-update.