MANO 1.1 AGI roadmap

MANO 1.1 is not general intelligence and we will not claim it is. This page tracks the capabilities that separate a chat model from a genuinely autonomous agent, and exactly how far MANO has come on each one.

Overall roadmap progress

51%

Averaged across 8 milestones. Updated as capabilities ship.

Milestones

Tool use

Shipped · 85%

Choosing and running the right tool for a step instead of answering from memory alone.

Where MANO is
MANO picks its own tool each step from a whitelist: knowledge search, deep sub-reasoning, note-taking, finish.
Next step
Add code execution and web retrieval as first-class mission tools.

Long-term planning

Partial · 70%

Breaking a goal into ordered steps and adapting the plan as results come in.

Where MANO is
Missions run a bounded plan-act-observe loop (up to 8 steps) with a deep plan stage before drafting.
Next step
Multi-session plans that survive across days and resume where they stopped.

Self-review

Shipped · 75%

Attacking its own answer before delivering it, and scoring the result against the goal.

Where MANO is
Every deep run has an adversary pass plus synthesis; missions self-score 0-100 against the goal.
Next step
Executable checks (tests, builds) as the scoring signal instead of self-judgement.

Memory

Partial · 65%

Recalling relevant facts and past work rather than starting cold each time.

Where MANO is
Vector knowledge memory feeds chat and missions; missions store durable lessons per user.
Next step
Automatic consolidation and forgetting so memory stays sharp as it grows.

Self-training

Early · 45%

Turning its own past work into rules that change future behaviour.

Where MANO is
Missions and lessons compile into an operating doctrine that loads back into MANO's context.
Next step
Score-weighted training and fine-tuned weights served behind the same mano-1.1 ID.

Goal prioritization

Early · 30%

Deciding what to work on first when several goals compete.

Where MANO is
Scheduled agents run goals on a timetable; ordering within a mission is model-chosen.
Next step
A standing goal queue with value, urgency, and cost ranking across missions.

Self-awareness (operational)

Early · 25%

Knowing its own limits, cost, and confidence — not consciousness.

Where MANO is
MANO reports depth, domain, substrate, stage timings, and refuses out-of-scope requests.
Next step
Calibrated confidence and explicit 'I cannot verify this' signals on every claim.

Autonomous initiative

Not started · 10%

Starting useful work without being asked, safely and within budget.

Where MANO is
Nothing runs unprompted except schedules the user creates.
Next step
Opt-in background missions with hard spend caps and an approval log.

How progress is measured

A milestone counts as shipped only when it runs in production for real users, is bounded by safety limits, and leaves a record we can inspect. Anything self-reported by a model without a stored trace is treated as unproven.