Founder video
Why this team is building Waldo
Shivansh and Suyash introduce the founders and the personal experience behind the company.
Open founder video ↗Three shifts · one product
Generation is abundant. Attention, judgment, and accountable control are scarce.
Waldo is being built between human intent and increasingly autonomous actors. The product goal is to reduce what a person must review, preserve what they should not have to remember, and keep authority legible as action moves from software into the physical world.
Launch wedge
The judgment layer
Agents create more drafts, plans, research, code, and alternatives than people can responsibly review. Waldo is designed to turn output into evidence-backed decisions and accepted outcomes instead of another queue.
Product responsibility
The burnout economy
Always-on software should not make people permanently available. Waldo should protect attention, batch judgment, respect capacity, preserve re-entry, and treat “enough,” deferral, and conscious release as valid outcomes.
Expansion frontier
The physical world
The same governed Work Unit can eventually coordinate a person, connected device, trade professional, machine, or robot—provided identity, safety, authority, telemetry, abort, evidence, and acceptance remain explicit.
Why this team believes it: Shivansh reports building more than 30 production agent instances at Atlan and watching expert users carry purpose, context, blockers, and outcome judgment themselves. Suyash experienced the collision of a design studio, Ironman training, and fragmented work and health tools. Waldo began with health, learned that insight without action becomes another dashboard, and now treats health as protected capacity context inside a broader outcome system.
Watch and read
Meet the founders, see Kennel, then open the company story.
These are the short companion artifacts for reviewers who want the people, product, and company narrative before going deeper into the system.
Product video
Waldo through Kennel
See the Mac surface for understanding agent activity, evidence, consequential judgments, accepted outcomes, and what remains open across sessions.
Open product video ↗
Pitch deck
Waldo company overview
The product wedge, founder story, market, business model, and long-term physical-AI direction.
Target Outcome loop
Waldo is designed to carry work from intent to evidence, judgment, acceptance, and re-entry.
This is the target cross-surface experience, not a claim of current end-to-end integration. A coding session may be one Work Unit. So may research, a document workflow, a human review, a message, a booking, or a physical inspection. None of them is the Outcome by itself.
1 · IntentName the OutcomeState what should become true, the constraints, acceptance checks, and who may judge them.
2 · PlanCompose Work UnitsWaldo assigns bounded contributions to the right agent, person, tool, or deterministic workflow.
3 · ActGrant exact authorityEach consequential effect receives a current, purpose-bound permission with a visible destination and blast radius.
4 · ProveArtifact, receipt, evidenceProvider completion can produce attributable evidence. A separate verifier or acceptance check determines whether the intended result is satisfied.
5 · JudgeNeeds You, only when neededWaldo presents the recommendation, alternatives, uncertainty, reversibility, and exact decision.
6 · ContinueAccept, defer, reopen, releaseThe Outcome and remaining Open Loops survive devices, sessions, restarts, and the next day.
The point: Waldo should reduce supervision, not merely move it. The person sees a compact decision packet—not every draft—with the recommendation, material alternatives, evidence, contradiction, uncertainty, reversibility, and consequence of acting or waiting.
One agent · many presences
There is one Waldo for the person. Every surface is a different way to reach the same agent.
Models, interfaces, and devices will change. The person's identity, continuity, permission policy, corrections, and right to judge closure should remain durable.
Kennel
The judgment presence
The reviewed direction is a native Mac working home for Outcomes, Needs You, evidence, authority, acceptance, re-entry, and an Operator Mode for the underlying sessions and workflows.
Waldo mobile
The everywhere presence
The mobile role is conversation, capture, briefings, meetings, notifications, lightweight judgment and Outcome continuity, and protected device context when the person is away from the Mac.
Waldo Core
The durable nervous system
The Backend role is shared Outcome state, Work Unit orchestration, memory, schedules, connectors, policy, delivery, recovery, evidence, verification, and cross-surface continuity.
One personal identity across changing surfaces
mindmap
root((Waldo<br/>one agent for one person))
Context
Priorities and commitments
Boundaries and corrections
Capacity and health
Relationships and routines
Software presences
Kennel on Mac
Waldo on mobile
Browser and messaging
Intelligence fabric
Coding agents
General and specialist models
Tools and skills
Durable core
Memory and provenance
Permission policy
Outcomes and Work Units
Evidence and acceptance
Open Loop continuity
Physical actors
People and trades
Devices and machines
Robots under one policy
Capability boundary · internal evidence · August 2026
Foundation, next proof, and expansion are different claims.
Research gives Waldo a capability library and architecture direction. It does not make an integration live. The build statements below summarize dated internal acceptance records and repository snapshots that are not independently inspectable from this public page; supporting artifacts can be shared with reviewers. We track useful capability from missing to foundation, partial, live, verified, and finally coherent across the product.
Working foundations
Three real pieces, not yet one complete loop
Internal acceptance records—not independently available from this page—cover bounded live Codex session discovery, conversation history, real-time processing state, same-task continuation, first-message handling, and archive cleanup in Kennel. Internal repository snapshots show durable run, typed-tool, permission, scheduling, delivery, recovery, and audit foundations in the harness, plus native personal and health-context foundations in the earlier mobile app.
Next product proof
One accepted cross-surface Outcome
One shared Outcome and Work Unit contract across Backend, Kennel, and mobile; approved source retrieval; a versioned artifact; an exact Judgment Request and authority grant; real delivery and receipt; independent verification; authorized acceptance plus explicit disposition of any remaining Open Loops; and next-day re-entry.
Sequenced expansion
Parity → coherence → compounding advantage
Deep Google Workspace integration, messaging, schedules, browser and computer action, documents and artifacts, Skills, specialist actors, CRM and social work, voice and calls, physical actors, and enterprise controls—added behind the same Outcome, authority, evidence, and continuity contracts.
The first acceptance gate: the same Outcome identifier must survive intent, heterogeneous Work Units, artifact creation, exact approval, external effect, provider receipt, independent verification, human acceptance, unresolved-loop disposition, restart recovery, and cross-surface re-entry. Until then, broad integration remains direction rather than shipped coherence.
Kennel
The Mac working home for what matters, what needs judgment, and what became true.
Kennel begins with coding agents because the coordination problem is already painful and observable there. The product model makes the durable object a general Outcome, so the same surface can govern research, documents, communication, human work, workflows, and future physical effects.
1. What matters nowOutcomes ordered by consequence, timing, dependency, and the person's explicit priorities—not engagement.
2. Needs YouConsequential judgments packaged with recommendation, alternatives, evidence, uncertainty, reversibility, and exact authority.
3. What became trueArtifacts, external effects, receipts, verification, acceptance, and consequences shown without equating provider completion with success.
4. What remainsWaiting, blocked, deferred, transferred, reopened, or consciously released Open Loops with an exact re-entry point.
5. Operator ModeProgressive access to the sessions, actors, tools, workflows, traces, costs, permissions, and recovery state underneath each Work Unit.
Supervision
Truthful state
Every session, decision, artifact, and provider event retains provenance so the person can understand what happened and where to return.
Judgment
Reviewable outcomes
What the work was meant to achieve, what evidence exists, and which human judgment is still missing.
Insight
Correctable continuity
Where work repeatedly stalls, which corrections matter, which workflows reach acceptance, and what the person confirms should change future orchestration.
What Waldo owns
Waldo rents model intelligence, but owns the relationship between a person and the actors working for them.
The bet is not that one model, tool, interface, or machine wins forever. The durable layer is where changing capabilities become useful for one specific person without taking ownership away from them.
Own
Context
Priorities, commitments, boundaries, health and capacity, relationships, routines, corrections, and current Open Loops.
Own
Outcomes and continuity
Outcome intent, Work Units, briefs, conversations, handoffs, judgment, evidence, delivery, acceptance, re-entry, and Open Loop disposition.
Own
Trust
Explain, preview, approve, edit, undo where possible, audit, correct memory, export, revoke, and delete.
Rent and route
Models
Frontier, open, specialist, local, and future models enter through adapters and compete for the work they are best suited to perform.
The product triangle
Product, consumer trust, and technical depth have to compound together.
Product
Brief, Chat, Handoff, Patrol
Simple surfaces for understanding the day, asking for help, handing off work, supervising exceptions, and returning to what remains open.
Consumer
Taste, habit, emotion, safety
The agent must feel calm and specific enough that a person can let it closer to work, health, relationships, and consequential choices.
Technical
Runtime, router, memory, evals
The harness makes every suggestion scoped, attributable, permissioned, recoverable, model-routed, measured, private, and economically viable.
Brief
What matters now
A calm synthesis of capacity, commitments, consequences, and the decisions that deserve attention.
Chat
Think with Waldo
A conversation grounded in the person's current life and work context, not a blank thread.
Handoff
Delegate with control
A reviewable plan that states the goal, context, tools, limits, evidence contract, and permission required.
Patrol
Supervise exceptions
Continuous awareness of agent work that stays quiet until a decision, risk, or unresolved consequence needs the person.
Why all three matter: product without harness depth becomes another dashboard. Harness depth without consumer trust becomes another developer tool. A warm character without useful decisions becomes theatre.
The learning loop
Waldo should learn from steering and verified outcomes, not from activity volume.
Token counts, session duration, commits, and tool calls can describe activity. They cannot tell us whether the work mattered or whether the person is finished.
Observed
Evidence
Provider events, artifacts, changed files, decisions requested, plans, corrections, and user responses.
Inferred
Candidate pattern
A possible habit, recurring blocker, preferred steering move, or unfinished commitment. It remains an inference.
Confirmed
User-owned truth
The person accepts, edits, rejects, defers, or releases the candidate. Correction is part of the product.
Applied
Better future work
Waldo briefs the next agent, protects a boundary, proposes a follow-up, or chooses a better workflow.
The agent that cares for you: Waldo is not trying to maximize session completion. It carries the person's commitments, capacity, boundaries, and consequences long enough to help the real outcome move.
Behavioral evidence without scoring
Agent traces can reveal useful patterns, but the product must belong to the person being interpreted.
Studying adjacent behavioral-evidence systems strengthened our belief that plans, corrections, tool choices, and outcomes can teach a personal agent how someone works. It also clarified what Waldo should not become.
What we carry forward
Evidence-linked, longitudinal help
Patterns should point back to their evidence, accumulate across time, express uncertainty, and help the person re-enter work without reconstructing everything.
What we reject
Opaque scoring or external judgment
Waldo does not turn agent activity into a builder score, productivity grade, admissions signal, or irreversible personality claim. The user can inspect, correct, reject, or release every important interpretation.
The design consequence: behavioral evidence should help the person understand and steer their own agents. It should never become an opaque score produced for someone else. The useful unit is an evidence-linked pattern the user can inspect, correct, and apply.
Target architecture and authority
A hybrid system keeps each truth with one authority while sharing the Outcome across every presence.
The target system is one product, not one giant database. Cross-surface Outcome state belongs to the governed Backend; local Mac and mobile effects retain local authority; provider activity enters as attributable evidence, never automatic authority over memory, acceptance, or future action.
Shared contracts
Outcome, Work Unit, Actor, Artifact, Evidence, Verification, Judgment Request, Authority Grant, Acceptance, Open Loop, Schedule, Presence, and Context Claim will use versioned identifiers and conformance fixtures across TypeScript and Swift.
Waldo Backend and harness
The governed cloud plane is designed to own shared Outcome state, durable runs, Work Unit orchestration, schedules, cloud connectors, policy, delivery, recovery, artifact versions, evidence events, and cross-surface presence.
Kennel on Mac
The desktop plane is designed to be authoritative for local provider observation, local action grants, and its durable local projection. It will mediate and record the person's Needs You judgments, acceptance, re-entry, and Operator Mode inspection while syncing minimized events and receipts rather than indiscriminate local transcripts.
Waldo mobile
The mobile plane is designed to be authoritative for device consent, capture, protected local context, notifications, and offline actions. It will mediate and record lightweight user judgment without becoming the judgment authority. The target privacy invariant is that raw health and other sensitive device data must remain local by default; only purpose-bound claims or snapshots may leave the device.
Provider and actor adapters
Models, agents, people, deterministic workflows, connected services, and future machines will advertise typed capabilities, authority requirements, evidence contracts, cost, latency, cancellation, and recovery behavior.
Truth and privacy boundaries
Agent Session, Outcome, Evidence, Verification, Acceptance, Open Loop, and Context Claim must remain separate. The target system must prohibit blanket home-directory crawls, ambient screenshots, global input capture, raw cross-device sync, and authority inferred from memory.
The agent platform
Every serious personal agent must solve eight problems beyond calling a model.
These are the platform responsibilities Waldo keeps first-party even when providers, transports, tools, and interfaces change.
Context
What enters intelligence
Layered, purpose-bound compilation with just-in-time tools, selected personal context, evidence, and progressive compaction—never the person's whole life in every prompt.
Action
What can change the world
Typed tools, reviewable skills, explicit blast radius, per-purpose permissions, previews, approvals, and recoverable failure.
Memory
What survives
Typed, provenance-bearing, inspectable, correctable memory written through a gate so a model cannot silently rewrite personal truth.
Initiation
What wakes the agent
KAIROS lets user intent, schedules, events, unresolved consequences, and changing context wake Waldo. Its tick-and-decide gate keeps the agent quiet when nothing deserves attention.
Outcome + judgment
What counts as done
Versioned artifacts, receipts, independent verification, exact Judgment Requests, authorized acceptance, and explicit Open Loop disposition challenge every actor's completion claim. Generation never grades itself.
Life intelligence
What makes help realistic
Capacity, health, calendar, commitments, relationships, routines, and boundaries shape what a good plan means for this person now.
Delivery
How help reaches the person
Channel-native cards, conversation, desktop presence, and selective notification ordered by consequence and timing—not engagement.
Continuity
How responsibility survives
Shared Outcome identifiers, exact re-entry points, cross-surface presence, durable dispositions, and continuity that survives dates, model changes, handoffs, restarts, and deliberate rest.
Tools, skills, and transports are different: a tool is a typed capability; a skill is a reviewable way of using capabilities; MCP and provider APIs transport them. None of these grants authority. Waldo keeps context, permission, memory, evidence, and outcome policy first-party.
Technical depth
The harness is the contract between a probabilistic model and the real world.
Runtime, routing, evaluation, memory, privacy, permissions, and cost are product decisions. They determine whether an always-present agent can be useful without becoming careless, expensive, or impossible to trust.
Principle 01
Deterministic seams
Models can propose. Code owns authentication, validation, permissions, idempotency, state transitions, and audit. A prompt is never a security boundary.
Principle 02
One writer per truth
Provider activity, outcome evidence, personal memory, and human closure have explicit owners. A projection or cache cannot silently become authority.
Principle 03
Memory never authorizes
A remembered approval is information about the past. Every new action still needs a current, purpose-bound grant.
Principle 04
Contract-first adapters
Models, providers, tools, and surfaces enter through typed capabilities. The surrounding personal-agent contract stays stable when any one of them changes.
Principle 05
Durability before autonomy
Long work needs journals, replay, idempotency, bounded retries, and explicit failure states before it earns broader authority.
Principle 06
Required context, not maximal context
Compile only what the declared outcome requires. Personal context remains permissioned, purpose-bound, correctable, and removable.
The durable personal-agent loop
flowchart TB
subgraph UNDERSTAND["1 · Understand"]
direction LR
T["Trigger or user intent"] --> O["Outcome<br/>intent + constraints + acceptance policy"]
O --> W["Work Unit plan<br/>agents + people + workflows"]
W --> C["Context compiler<br/>purpose + permitted context"]
end
subgraph ACT["2 · Act safely"]
direction LR
M["Selected actor or provider"] --> D["Typed capability dispatcher"]
D --> G{"Permission + policy gates"}
G -->|allowed| E["Artifact, effect, receipt<br/>+ durable evidence"]
G -->|needs judgment| H["Needs You<br/>exact Judgment Request"]
H -->|approved grant| E
end
subgraph LEARN["3 · Learn with the user"]
direction LR
V["Independent Verification"] --> A["Authorized Acceptance"]
A --> L["Open Loop disposition<br/>close, defer, reopen, release"]
L --> R["Correctable memory + exact re-entry"]
end
C --> M
E --> V
R -. "next useful action" .-> C
The compiled prompt — REASONS anatomy
Context is compiled from typed layers, not written as one giant prompt. REASONS is the anatomy: a provider-shaped working brief assembled for the intended outcome using only the personal context, tools, evidence, and safeguards that purpose requires.
RRequirementsThe trigger, intended outcome, constraints, and definition of done.
EEntitiesThe people, artifacts, commitments, and permitted personal context involved.
AApproachThe selected workflow or skill and why it fits this task.
SStructureAvailable tools, channel, evidence contract, and output shape.
OOperationsThe ordered steps, prior evidence, and explicit handoffs.
NNormsVoice, user preferences, correction history, and interaction boundaries.
SSafeguardsPermission, privacy, safety, and failure rules enforced outside the prompt.
Why compile instead of append: a personal agent may know a great deal, but useful context is not maximal context. Compilation controls relevance, privacy, latency, cost, and the chance that old information distorts the current job.
Five-layer memory — user-owned continuity
The five-layer design separates short-lived task context from durable personal truth. The important idea is not a particular database: every layer has a purpose, provenance, lifecycle, correction path, and authority limit.
Memory tiers · from working context to user-owned archive
flowchart TB
T0["Layer 0 · Working context<br/>volatile, task-bounded, rebuilt"]
T1["Layer 1 · Typed personal memory<br/>facts, events, discoveries, preferences, advice"]
T2["Layer 2 · Episodes and evidence<br/>attributable sessions, corrections, outcomes"]
T3["Layer 3 · Skills and procedures<br/>reviewable ways of working"]
T4["Layer 4 · Archive and export<br/>history, deletion, recovery, portability"]
T4 --> T3 --> T2 --> T1 --> T0
T0 -. "new evidence, never direct truth" .-> T2
T2 -. "candidate claim" .-> T1
T1 -. "user correction or release" .-> T2
Scribe
Staged, evidence-linked memory
Observations enter a memory inbox. A governed write path promotes them only with provenance, scope, confidence, correction, reversibility, expiry, and deletion.
Reflection
Patterns without silent truth
Background reflection can connect episodes, surface recurring patterns, decay stale confidence, and propose memory changes. The person keeps the right to inspect, correct, release, export, or delete them.
Time and retrieval
History without rewriting it
Memory records when something was true and when Waldo learned it. Retrieval fuses relevance, recency, confidence, and the current purpose instead of treating every old fact equally.
Security — authority is enforced at every seam
Security is a sequence of independent refusals. Seeing evidence, inferring a habit, remembering a preference, or receiving provider completion never grants permission to act.
Defense in depth · enduring contract
flowchart LR
I["Verified identity"] --> P["Fresh purpose-bound permission"]
P --> A["Capability allowlist"]
A --> T["Untrusted-input and taint checks"]
T --> Z["Schema validation + sanitization"]
Z --> X["Human approval for consequential action"]
X --> V["Evidence and output verification"]
V --> J["Attributable journal + audit"]
J --> R["Revocation, correction, deletion"]
Memory
≠
“The user approved this before.”
Historical information only.
Authority
→
“This action is allowed now.”
Requires a current grant for this purpose and capability.
Evidence
“Here is what actually happened.”
Recorded without silently closing the human loop.
The security principle: identity, permission, capability, input trust, approval, evidence, and audit are separate gates. Passing one never implies another, and a prompt is never a security boundary.
Owned orchestration intelligence
Models get better for everyone. Waldo gets better at helping one person.
Waldo does not need to replace foundation models. It can become the intelligence that decides when to stay quiet, what context is required, which model or tool fits, what permission is needed, how success should be judged, and what the next agent should inherit.
The user-owned learning flywheel
flowchart TB
C["Consented context<br/>intent + commitments + capacity + memory"] --> P["Waldo brief or proposal"]
P --> U["User steers<br/>approve, edit, reject, defer, correct"]
U --> A["Agent or tool acts"]
A --> E["Outcome evidence"]
E --> J["Human judgment<br/>close, reopen, transfer, release"]
J --> M["Correctable memory + Open Loops"]
M --> C
E --> R["Routing and workflow insight"]
R --> P
What compounds
Intended, permitted, corrected
The durable history is not raw prompt volume. It is what the person intended, allowed, changed, verified, and consciously left open.
What improves
Timing, routing, and workflow
Outcome history teaches Waldo when not to interrupt, which model or skill fits, which evidence matters, and where a human judgment belongs.
What stays owned
The person's continuity
Models and surfaces can change without forcing the user to surrender their memory, permissions, preferences, or accumulated ways of working.
From model access to a Waldo intelligence gateway
flowchart LR
I["Intent + permitted context"] --> W["Waldo Intelligence Gateway"]
W --> Q{"Quality, privacy,<br/>latency, cost, tools"}
Q --> F["Frontier reasoning"]
Q --> O["Open or local model"]
Q --> S["Specialist model or skill"]
F --> V["Evidence + outcome review"]
O --> V
S --> V
V --> W
W --> N["Better next orchestration"]
01
Route broadly
Use replaceable model and tool adapters rather than binding the person's agent identity to one provider.
02
Trace meaningfully
Capture intent, route, permission, evidence, correction, cost, and outcome—not surveillance for its own sake.
03
Learn policy
Improve task classification, action timing, context selection, workflow choice, and route quality from consented outcomes.
04
Specialize later
Where outside models remain weak, Waldo can develop specialized orchestration intelligence while continuing to use the best external capability.
Economics is part of the product: skip first, route second, escalate last. An always-present agent stays viable by resolving routine cases deterministically, choosing the cheapest sufficient capability, and spending frontier intelligence only where the outcome justifies it.
The trust ladder
Authority is earned per action, not granted globally.
Waldo expands from understanding to action through visible usefulness, task-specific permission, evidence, reversibility, and repeated user-confirmed success.
Stage 1
Observe
Read permitted context, explain what matters, show uncertainty, and do nothing by default.
Stage 2
Suggest
Offer a concrete next move, preparation brief, recovery adjustment, re-entry point, or agent workflow.
Stage 3
Approve
Preview the plan and blast radius, request a purpose-bound grant, and let the person edit, defer, or refuse.
Stage 4
Automate selectively
Only reversible, bounded behaviors graduate after repeated success, clear audit, revocation, and a reliable exception path.
Continuous does not mean noisy: Waldo can wake often and act rarely. It should preserve exact re-entry points, batch non-urgent judgment, respect quiet hours and attention budgets, and interrupt only when timing, consequence, and the need for human authority justify attention.
The attention contract
The assistant should reduce how much of life the person must keep mentally open.
The burnout economy is not solved by an AI manager that produces more recommendations, monitors more behavior, or keeps the user permanently available. Waldo should carry responsibility without taking agency away.
Judgment budget
Escalate consequence, not volume
Filter drafts, collapse duplicates, resolve reversible cases within policy, batch non-urgent choices, and reserve interruption for decisions whose consequence or authority belongs to the person.
Enough
Stop conditions are a feature
Every Outcome can define sufficient evidence, acceptable quality, time and cost limits, and valid dispositions such as accept, defer, transfer, reopen, or consciously release.
Capacity
Context without judgment
Explicit boundaries, calendar load, rest, and permissioned health context can shape timing and plans. Waldo must not infer laziness, morality, personality, or commitment from behavioral or body traces.
Daily Close
Continuity without mental custody
Record what became true, what is waiting, what was released, and the exact next re-entry point so rest does not require keeping every obligation alive in working memory.
The product test: does Waldo leave fewer things requiring active mental custody? Accepted Outcomes, avoided interventions, useful judgment requests, conscious release, and reliable next-day re-entry matter more than tasks generated, tokens spent, or time kept inside the product.
The people building Waldo
Systems depth, consumer taste, and a long habit of making things.
The team met through building: Shivansh and Ashish became friends at school over iOS jailbreaking; years later Shivansh met Suyash in the university Computer Center and showed him how to build a website by describing it to an AI tool.
Shivansh Fulper
Founder · engineering and architecture
Shivansh reports building more than 30 production agent instances at Atlan and learning where capable agents still leave purpose, context, blockers, and outcome judgment to people. His earlier work spans OpenFn/C4GT, Project EKA data-curation infrastructure, native apps, and independent model implementation.
Suyash Pingale
Founder · product, experience and brand
Through SAPIEN, product work, and the lived collision of a design studio with Ironman training, he brings the consumer discipline agent infrastructure normally lacks: making permissions, uncertainty, attention, and control feel legible.
Ashish Tembhekar
Founding Engineer
Before Waldo, Ashish spent nine months working as an AI engineer. He built much of Waldo's first app and health-data pipeline, validated Health Connect on real Android hardware, and now works across native iOS, Supabase, and agent infrastructure.
The product triangle: engineering makes the system dependable; product taste makes truth and control understandable; the consumer relationship makes the technology worth keeping around.
Expansion frontier · physical work
The same governed Work Unit can coordinate software, people, tools, machines, and robots.
Our expansion thesis is that AI will move further into trades, field work, connected hardware, logistics, homes, vehicles, and robotics. Waldo's role is not to own every machine; it is to preserve the person's intent, authority, evidence, continuity, and right to stop as work crosses the digital–physical boundary.
People and trades
Human Work Units remain first-class
Maintenance, field service, inspections, contractor coordination, equipment repair, and acceptance can combine AI preparation with accountable human execution and real-world evidence.
Devices and hardware
Connected effects need receipts
Sensors, wearables, home devices, equipment, and vehicles enter through capability manifests that declare identity, location, telemetry, required authority, failure behavior, and observable completion.
Robots and physical bodies
Action requires a safety contract
Every physical effect must declare safety class, preconditions, permitted action, live state, abort path, human handoff, reversibility or recovery, telemetry, evidence, and acceptance authority.
Why software first: the Outcome, authority, evidence, interruption, recovery, and acceptance contracts must be trustworthy before Waldo is given movement or physical-world authority. Low-risk coordination and observation come before actuation. Consumer bodies such as a desk object, wearable, home device, or small robot remain part of the horizon—not a current Waldo hardware program.
Waldo is the company
Waldo is the personal agent that stays on your side and keeps what matters moving.
Waldo is designed to carry the context you choose to share—your priorities, commitments, boundaries, health context, relationships, permissions, corrections, and outcome history—across work and personal life. Its job is to help decide what matters, coordinate the right people and AI, follow work through to a real outcome, and protect your attention while keeping you in control.
Kennel is Waldo's first home on the Mac and its first market wedge—not the company. Over time, the same Waldo can meet you through mobile, messaging, voice, connected services, and eventually physical forms. The surface changes; the relationship, memory, permissions, and loyalty to the person do not.
Meet WaldoPublic anchors