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FocusPilot OS

An operating system for focused work

Autonomous AI that plans work around mental energy, not just time.

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The Problem: Productivity Tools Ignore the Brain

Current tools assume we're machines, not humans. They optimize for time, but ignore the reality of fluctuating cognitive capacity.

  • Calendars presume constant energy throughout the day
  • Task managers prioritize deadlines over focus quality
  • Context switching fragments deep work
  • Burnout happens before schedules break

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Core Insight

Time ≠ Cognitive Capacity

Mental energy fluctuates

Cognitive capacity varies hourly, not constant

Cognitive overload is predictable

Fragmentation patterns emerge before burnout

Planning must adapt dynamically

Schedules should respond to real-time mental state

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FocusPilot OS

01

Manages mental energy, not just tasks

Tracks cognitive load alongside deadlines

02

Detects overload & fragmentation

Identifies when focus is breaking down

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Dynamically restructures schedules

Adapts plans based on real-time capacity

04

Protects deep work automatically

Creates uninterrupted focus blocks

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User Flow: Simple Input → Intelligent Output

Add tasks with time & priority

Quick entry with optional constraints

Click Sync Tasks

Trigger autonomous planning cycle

AI analyses cognitive load

Overload and fragmentation detection

Breaks inserted automatically

Recovery periods based on energy levels

Task order optimised for focus

Deep work protected in optimal windows

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Agentic Architecture

Heuristic–Agentic Loop

Telemetry Engine

Collects behavioural signals and energy patterns

Risk Agent

Calculates overload and fragmentation scores

Planning Agent

Uses LLM reasoning to restructure schedules

Evaluator Agent

Audits decisions for quality and feasibility

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Why This Is Truly Agentic

Beyond Rules and Reminders

Agents reason over system state

Not hardcoded rules—dynamic understanding of context

Plans adapt continuously

Every sync cycle reassesses priorities and capacity

Decisions are justified

Clear reasoning shown for every schedule change

Autonomy with human control

AI proposes, user always decides final plan

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Opik as a Core System Layer

Observability Is Not Optional

Every planning cycle logged as an experiment

Complete trace of inputs, reasoning, and outcomes

Cognitive metrics tracked over time

Overload scores, fragmentation indices, and recovery patterns

Decisions fully auditable

Why each task was moved or rescheduled

Safe autonomous behaviour

Regression tests and failure mode detection

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LLM-as-Judge Evaluation

Agents Evaluating Agents

Separate Evaluator Agent

Independent quality assessment

Scores every plan on resilience, feasibility, and priority alignment

Multidimensional quality metrics

Stored as Opik feedback scores

Evidence for continuous improvement

Development with Opik: Compare planning strategies, tune prompts with evidence, detect failure modes early, and validate improvements safely.

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FocusPilot OS

A blueprint for deploying autonomous agents safely in human-centric systems

$1T

Global burnout cost

Prevented through early overload detection

100%

Transparent decisions

Full audit trail with reasoning shown

Continuous

Adaptive planning

Dynamic response to mental energy levels

FocusPilot transforms productivity from efficiency obsession to sustainable resilience. Built with Opik for safe, auditable autonomous behaviour that supports—not replaces—human judgement.