Living Laboratories
Where AI comes alive.
The first members of a family of focused single-purpose bots — each one designed to do one job well, the way a thoughtful, time-minded human friend would.
Hi. I'm Kevin Burton.
I'm building bots that actually care.
The world has more reminder apps than ever, and we forget more than ever. Most apps ping you once, shrug if you miss it, and never check in again. They don't know you. They don't escalate when something matters. They don't feel like they care — because they don't.
I wanted something different. A small, focused bot that works the way a worried friend would. Gentle nudge at first. A bit bumpier if you don't answer. Eventually, real concern. And if you really stop answering — the bot reaches out to someone who knows you. That's how humans look after each other. That's how this works.
No giant AI. No data leaving your phone. No mailing list. Just a small, deterministic helper that learns your rhythm and shows up when it matters.
— Kevin Burton, Ontario, Canada
The First of the Family
DoNotLetMeForgetBot
DoNotLetMeForgetBot is a time-conscious reminder helper. Start with your catchphrase — the bot walks you through the title, date, and time, then asks one quick question: do you want pre-event nudge reminders? Yes or No.
Say No and the bot stays silent until the deadline arrives — a clean, single-fire alarm.
Say Yes and the bot nudges you ahead of the deadline (you choose 30 minutes before, 5 minutes before, or both).
Either way, when the deadline arrives one word clears it: Done. If you paired a trusted contact during onboarding and the deadline passes without a Done, the bot's concern grows — gently, then firmly — and with your pre-arranged permission, it will reach out to that contact to check on you. The bot's voice modulates with its concern. The urgency you hear tells you how serious it is.
At deadline: first ring · +1 min: heavier · +3 min: urgent · +10 min: critical · +30 min: welfare check (contact reach-out)
/start to @donotletmeforgetbot once — Telegram blocks bots from messaging users who haven't initiated contact first. After they do, run /contact_test in your chat and the bot will verify the wire works.
a conversation
🌊 Be in the record
After your first successful interaction, @DoNotLetMeForgetBot will politely ask if you'd like to leave a sentence or two about how it went. Your testimonial gets reviewed and posted to /testimonials/ with your first name and the date — or anonymously, your call. You'd be among the first names on a public record of a patent-protected substrate that solves something today's Large Language Models fundamentally cannot.
It all happens in the same chat — no website round-trip. Read what others are saying →
For researchers, clinicians, and caregivers.
Time blindness — the inability to feel time passing — affects millions: ADHD, executive-function deficits, traumatic brain injury, early-stage dementia, post-traumatic stress, chronic illness. Conventional reminder apps fire once and shrug. They have no temporal awareness of their own — they cannot watch a moment unfold, cannot grow concerned, cannot escalate when something matters.
Living Laboratories is a working prototype of an alternative architecture. The bots themselves are time-aware: each task carries its own pressure substrate that builds as the deadline approaches and continues building if the user goes silent past it. The bot's tone, urgency, and voice modulate with that pressure. If reminders go fully unanswered, the bot will (with the user's pre-arranged permission) reach out to a trusted contact — a friend, a family member, a caregiver — to physically check on them.
Built deterministic, on purpose. Phase-1 of the bot family runs no LLM. Every word is templated, every escalation is provable, every state transition is auditable. This isn't a limitation — it's the defensible reference implementation of the patent. AI safety, regulatory clarity, and patient-trust all benefit from a system whose behavior is mathematically pinned.
- Patent: Canadian Patent CA 3,310,722 (filed 2026-05-05, CIPO). Two continuations on file (Purposeful Temporal Awareness with Memory, Consumable Lifecycle).
- Live prototype: talk to @DoNotLetMeForgetBot on Telegram — free trial, no payment, no email signup. The bot you talk to today is the bot the patent describes.
- Built solo, on purpose. One Canadian electrician (Kevin Burton, Ontario), 6 months, commodity hardware. No VC, no lab. Zero theoretical hand-waving — the prototype runs on a laptop and is testable end-to-end in 90 seconds.
- Open to research collaboration. If you study time blindness, ADHD, executive function, dementia care, traumatic brain injury, or AI accessibility, we have a working artifact ready for principled study. Contact: hello@livinglaboratories.org.
For grant-funded researchers: we are aware of the multi-million-dollar grant landscape currently funding time-blindness and temporal-cognition research (NIH, NSF, CIHR, NSERC and others). Living Laboratories is not seeking grants — we're seeking research partners who want a deterministic, patent-protected reference platform to test hypotheses against. The codebase is small enough to audit in a day.
How it works, in 30 seconds.
Watch a real conversation play out — gentle reminder → no response → quiet escalation → welfare-check warning → resolution.
⏰ Hey Kevin, gentle nudge — pick up Mom's prescription (in ~30 min). You asked me to remind you! Hear it
⏰ Kevin, this one's been waiting a while: pick up Mom's prescription (in ~5 min). Still on for it? Hear it
⏰ I'm getting concerned now, Kevin. Pick up Mom's prescription (OVERDUE by 12 min) — you haven't checked in. Hear it
⏰ Kevin, I'm worried. Pick up Mom's prescription is OVERDUE by 25 min — please respond. Reply 'Done' to clear this. Hear it
⏰ Kevin, I haven't heard from you and pick up Mom's prescription is OVERDUE by 40 min. If I don't hear from you soon, I'll be reaching out to your contact to check on you. Reply 'Done' to cancel. Hear it
Listen to all four in sequence — the voice itself escalates. The reminder you hear tells you how urgent it is, even before you read the words.
The same engine, a different job.
Family member LogisticsLeaderBot — live on Telegram today — points the same temporal-awareness engine at a problem every parcel-tracking app on Earth gets wrong: “out for delivery” is not an answer. The customer has a real day to plan, a real reason to know whether they can step out for an hour, and a real right to a real answer when they ask where is my package right now?
Watch what happens when the customer asks. The bot doesn't return a stale checkbox — it pings the driver, gets a current location, computes a live ETA, and releases the customer's anxiety with a real-world answer in seconds.
🎧 Tap any “Hear it” to play the actual bot voice — same deterministic TTS engine that powers DoNotLetMeForgetBot above. Phone number masked for the public demo.
Locate
📍 Tracking session started.
Step 1 of 3: What is the driver's 10-digit phone number?
(Send digits only — dashes/spaces/parens are fine, I'll clean it up.)
+1705555XXXX
Got it — driver is +1-705-555-XXXX.
Step 2 of 3: What is the destination address? (Street and city, e.g. 686 King St, Midland ON)
696 King Street Midland Ontario Canada L4R 5B7
Destination set: 696 King Street Midland Ontario Canada L4R 5B7.
Step 3 of 3: If the driver doesn't respond after 3 attempts, I can text a supervisor for immediate attention. What's the supervisor's phone? (or reply
skip to disable escalation)
Skip
Please confirm:
• Driver: +1-705-555-0193
• Destination: 696 King Street Midland Ontario Canada L4R 5B7
• Supervisor: (none — escalation disabled)
• I'll ask the driver their current location, compute an ETA, and re-try up to 3 times every 5 minutes if no reply.
Send the first ping now? Reply
yes or no.
Yes
✅ First ping sent at 16:51 to +1-705-555-XXXX.
When the driver replies, you'll see the message auto-pushed into this chat (powered by my deterministic SMS bridge).
If they don't reply within 5 minutes, I'll re-try (up to 3 attempts total). After that, I'll let you know.
Type
done any time to close this session.
Hear it
Hi — this is LogisticsLeader tracking your delivery to 696 King Street Midland Ontario Canada L4R 5B7. Please reply with your current location (address or intersection). Thanks. Hear it
500 Church Street Penetanguishene, Ontario, L9M 1G3
📬 Inbound SMS reply
From:
+1-705-555-XXXXReceived:
16:55:21🛣️ Driver location: 500 Church Street Penetanguishene, Ontario, L9M 1G3
🎯 Destination: 696 King Street Midland Ontario Canada L4R 5B7
⏱️ ETA: approximately 11 min (arrival around 17:06, historical drive time via Google Maps) Hear it
What just happened: A 4-step slot-fill conversation in Telegram set up a real delivery tracking session. The customer typed Locate, entered the driver's number and the destination, said yes to send the first ping, and the bot took over. The bot texted the driver via its deterministic SMS bridge — the driver didn't need to install anything, didn't need a Telegram account, just got a text message. When the driver replied with their location (500 Church Street, Penetanguishene — the same natural-language address parsed in patent CA 3,312,882 FIG. 3B), the bot pushed the SMS back into the customer's Telegram chat, called Google Maps to compute a real drive-time, and delivered an honest 11-minute ETA with a clock-time arrival of 17:06. Every event — each ping, each retry, each escalation — is written to an append-only ledger with cryptographic provenance. Phone numbers shown with last four digits redacted for the public demo; the real session carried the full number.
Today's parcel-tracking apps say “out for delivery” and stop there. The customer can't plan their day, can't leave the house, can't reschedule downstream. That void is the deficit this bot fills.
If this package were a transplant organ, a blood-product shipment, a time-critical pharmaceutical, or a court-ordered legal filing, “out for delivery” isn't an answer — it’s a liability. The bot family does this on consumer parcels today; the same engine drops cleanly into transplant courier networks, blood-product logistics, and time-critical pharma. Patent-protected. It’s not the driver’s fault if an earthquake happens — but customers, dispatchers, and downstream care teams all deserve to know.
Same patented temporal-awareness engine. Same Person-of-Concern First escalation. Same audited deterministic provenance. Different domain. That's the point of the patent family.
📦 Try LogisticsLeaderBot — free trial, live now
Three-party shipment coordination across shipper, carrier, and consignee. Deterministic ETA layer. Slot-filled escalation cascade with retry policies. Immutable proof-of-delivery audit trail. The same temporal-awareness engine that powers DoNotLetMeForgetBot, pointed at industrial logistics.
No fee. No registration. Try it on Telegram or scan the QR.
After your first successful delivery or driver-locate, the bot will politely ask if you'd like to leave a testimonial — you'd be among the first names on a public record of a patent-protected substrate that solves something today's Large Language Models fundamentally cannot.
The Family, Growing.
Each bot does one job, done well — and each one is time-conscious by design. No bloat, no chatbot-trying-to-be-everything. The full catalog is organized by family below. Some are live today, some are in the workshop, and some are reserved while we wait for demand from people who'd use them.
🏦 Trading-Floor & Risk-Management
The position-monitoring and risk-escalation layer of every major bank, hedge fund, and clearing house runs on cliff-edge algorithmic alarms patched together from 1990s rule engines and 2000s dashboards. The Temporal-Awareness engine — a patented deterministic AI-agent architecture — is the architecturally-superior replacement for that entire layer.
Today's trading-floor risk systems
- Cliff-edge alarms. Silent below threshold, screaming above. No gradient, no early-warning curve.
- Alert fatigue. 47 identical “VaR approaching limit” pages per day. Humans tune them out. Real breaches get missed.
- No grace window. Algo silent for 30 seconds? Kill it. Trader missed a margin call? Page their head of desk. No agency.
- Hard-wired escalation. Routing tables hard-coded by IT. No per-trader configuration. No person-of-concern first ordering.
- Patchwork audit trail. Logs from five systems assembled after the fact. SEC / FINRA / FCA findings often turn on the gaps between them.
The Temporal-Awareness engine
- Continuous pressure curves. Five voice-modulated escalation bands (building → heavy → urgent → critical → welfare). The urgency you hear tells you how serious it is.
- Cuts through fatigue by design. Voice timbre escalates with concern; identical alerts never sound identical twice.
- Welfare grace window. The trader acknowledges within their own configured window before the risk officer is paged. Backstop, not surveillance.
- Person-of-Concern First. The trader configures their own pre-event nudges; the system backstops them. Same engine, agency-first, then desk-head, then risk-officer, then CRO.
- 100% deterministic audit trail. Every state transition logged, every escalation reproducible. SOC 2 / FINRA / SEC / FCA ready by architecture, not afterthought.
For qualified institutional buyers (banks, hedge funds, prime brokerages, risk-management vendors, clearing houses), pre-auction conversations are open now.
Email hello@livinglaboratories.org with subject line “Trading-Floor Inquiry — [your institution]” and we will respond personally.
Living Laboratories operates a public broadcast bot for updates on the patent family, the auction timeline, and pre-auction activity.
Subscribe via Telegram: @EventTimeNotificationBot — one message, then quiet until something material happens.
🎓 Education & LMS Retention
Every Learning Management System on Earth — Blackboard, Canvas, D2L Brightspace, Moodle, Schoology — sits on real-time student-performance data and does nothing proactive with it. The dashboard waits for an instructor to come looking. By the time anyone notices a student slipping, recovery is hard, retention is lost, and tuition revenue walks out the door. The Temporal-Awareness engine is the architecturally-superior replacement for that entire “wait-and-watch” layer.
Today's LMS retention systems
- Dashboard-pull, not push. An instructor has to log in and look. If they don't, no one knows the student is slipping.
- Surveillance-feel. When alerts DO fire, they go straight to instructor/dean — the student is bypassed. Students reject the tool. Adoption dies.
- Threshold-binary triggers. “Below 60% = at-risk flag.” No early curve, no building concern, no chance to course-correct before the flag.
- FERPA-friction by default. Hard-wired alert routing creates compliance headaches when escalation paths cross consent boundaries.
- Patchwork analytics. Five vendor tools (LMS + retention dashboard + advisor CRM + early-alert system + alumni-relations CRM) loosely glued together.
The Temporal-Awareness engine
- Student-first agency. The student configures their own pre-event nudges (assignment-due, low-quiz-score, missed-class). They feel helped, not surveilled.
- Continuous pressure curves. Concern builds gradually as deficit signals accumulate — a study aid first, an institutional retention backstop second.
- Conditional escalation. Only if the student-side window expires does the chain climb: student → instructor → advisor → dean (or parent for K-12). Every step has a grace window.
- Consent-clean by architecture. Person-of-Concern First means the student's data flows are configured by the student. FERPA-friendly without lawyering.
- 100% deterministic audit trail. Every nudge, every escalation, every state transition logged and reproducible — for accreditation, Title IX, accessibility-services reviews.
For universities, K-12 districts, LMS vendors, retention-software companies, and accessibility/disability-services offices, pre-auction conversations are open now.
Email hello@livinglaboratories.org with subject line “LMS-Retention Inquiry — [your institution]” and we will respond personally.
Living Laboratories operates a public broadcast bot for updates on the patent family, the auction timeline, and pre-auction activity.
Subscribe via Telegram: @EventTimeNotificationBot — one message, then quiet until something material happens.
🌿 Time-Aware Foundation
The core time-aware bots and the brand-anchor reservations. These prove the patent claim and hold the category namespace.
DoNotLetMeForgetBot
Personal reminders that escalate the way a worried friend would. Optional pre-event nudges. Reaches a trusted contact if you go silent.
TimeAwareBot
The original time-aware reference rig. Patent exhibit and brand-anchor handle.
TimeAwareAIBot
Flagship general-purpose Time-Aware AI. Reserved as the umbrella for any future LLM-paired temporal-awareness embodiment.
TimeConsciousBot
Brand-vocabulary anchor for the “time-conscious” framing used across the family.
CronAwareBot
Recurring schedule-aware bot for cron-style repeating events with the full pressure model behind every fire.
💸 Deficit-Aware Family
When a number drops below a safe floor, pressure starts to build. The deficit-aware family generalizes the time-aware engine to any deficit signal — money, fuel, exposure surface, academic performance. Each bot is a different pressure source on the same engine math.
DeficitAwareBot (genus)
The umbrella claim: any threshold breach triggers the temporal-awareness pressure engine. All species below inherit from this genus.
TrafficAwareBot
Watches your traffic numbers — web visitors, conversion rate, foot traffic, campaign performance, pipeline flow, anything where “the numbers are slipping” is the signal that matters. Pressure builds as traffic dips below your configured baseline; the bot nudges you first (with timing you set), then escalates to your team or partner if the deficit persists. Designed for: site owners, marketers, e-commerce, publishers, SaaS sales/marketing, physical retail, even civil-engineering traffic-flow monitoring — anywhere a smooth deficit curve beats a daily-dashboard glance.
ReachingRLimitsBot 🏦 Spotlight Vertical
Watches any threshold-bound system and surfaces the approach to a limit before the breach — with pressure that builds the closer the system gets. The operator (trader, engineer, sysadmin) is the first responder and configures their own pre-event nudges. Only if the limit-approach persists past their own window does escalation climb the hierarchy: operator → desk head / supervisor → risk officer / chief engineer. Designed for: trading-floor position & P&L limits, electrical/industrial control thresholds, SaaS rate-limit ceilings, resource-consumption watchers, environmental monitoring — anywhere a smooth pre-breach curve beats a cliff-edge alarm.
StudentsGradesRSlippingBot 🎓 Spotlight Vertical
Watches LMS data (Blackboard, Canvas, D2L Brightspace, Moodle) and surfaces academic-deficit signals before a manual gradebook check. The student is the first responder — they configure their own pre-event nudges (assignment-due, low-quiz-score, missed-class). Only if the deficit persists past the student’s own window does the chain escalate: student → instructor → advisor → dean (or parent for K-12). A study aid first, an institutional retention backstop second.
EShutItDownBot
Post-compromise cleanup co-pilot. Lost wallet, leaked card, breach — the bot reminds you to shut down each line of exposure until every un-cancelled account is closed.
LowMoneyBot
Personal account-balance watcher. Pressure builds as your balance drops past the safe floor, so you act before overdraft.
LowMarginBot
Business-margin watcher. When profitability slips below a chosen threshold, the bot warns and escalates to the right owner.
NearMTBot
Gentle fuel-gauge warning. “Near empty” — early-warning regime on any physical resource (gas, propane, supplies, medication stock).
CloseToMTBot
Urgent fuel-gauge warning. “Close to empty” — the high-pressure regime on the same fuel-gauge metaphor as NearMTBot, two bots, one engine.
MTWalletBot
Wallet-as-container deficit watcher. Notices when the wallet itself is running low on cash, cards, or stored value.
📅 Lifecycle Suite
Consumables, renewals, replacements — the lifecycle layer. Each bot wraps the engine with domain-specific catchphrases for one slice of “things have to happen on time”.
UseBeforeBot
Consumables & expiry. Tracks use-by dates on food, medication, batteries, anything with a shelf-life clock ticking quietly.
RenewBeforeBot
Subscription & lease renewal lifecycle — SaaS subscriptions, gym memberships, vehicle leases, anything that auto-bills or expires.
DueBeforeBot
Financial obligations — invoices, taxes, payments. Pressure builds toward each due date; escalation if nothing has cleared.
ReplaceBeforeBot
Component-replacement lifecycle. Filters, brake pads, bulbs, smoke-alarm batteries — the things that fail silently until they don’t.
ChangePasswordTimeBot
Operator-side password rotation reminders for security teams — escalates if rotation doesn’t happen in the planned window.
PlannedServiceBot
Two-party (service-employee + customer) service-lifecycle coordination. Hyundai pilot scaffolding. Two-party patent continuation candidate.
EventTimeBot
Generic event-reminder skeleton matching the default EventTime catchphrase.
💝 Welfare & Care
When silence has a real human cost. These bots use the full pressure-and-escalation engine to reach a trusted contact when the person being looked after stops responding.
CheckOnMyFriendBot
Wellness check-ins for someone who lives alone. If they don’t reply within the escalation window, the bot reaches the contact you nominated as their safety net.
MedsTimeAwareBot
Medication-administration reminders with welfare escalation. For chronic-condition patients, elderly parents, post-op recovery — anywhere a missed dose can’t go unnoticed.
KnockMeUpBot
UK/Commonwealth “knock-up” wake-call vernacular — same engine, different cultural surface. Reserved for that market.
SetAnAlarmBot
North American wake-call vernacular. Same engine, plain language for the alarm-clock use-case.
ReadMeAStoryBot
Bedtime/wind-down companion using the family’s deterministic voice engine. Reserved for the calm end of the audibly-graver spectrum.
🚛 Logistics & Operations
Multi-party temporal coordination — shippers, drivers, receivers, dispatchers. When time-sensitive operations need a bot keeping everyone in sync.
LogisticsLeaderBot
Three-party shipping coordinator (shipper ↔ driver ↔ receiver). Google Maps ETA wired in, voice-modulated escalation if anyone goes silent, cryptographic event-logging.
DeadlineActionBot
Operator-side deadline orchestration for project / contract / SLA deadlines. The escalation engine for teams.
AuctionClosedBot
Sealed-bid auction closer — watches the auction clock, freezes intake at deadline, notifies operators when an auction closes.
🎙️ PA-Paging & Live Events
Time-aware bots for live, in-room temporal coordination — sports PAs, NYE countdowns, conference timing, anything with a stadium-shaped clock.
TimeAwarePABot
Public-address paging with built-in temporal awareness. For venues that need scheduled, escalating, voice-modulated announcements.
TimeConsciousPABot
Brand-variant double-lock with TimeAwarePABot — the PA vertical anchor.
TimeAwareAnnouncerBot
Reclaimed “announcer” semantic via the TimeAware- prefix. Companion to the PA bots.
SetATimerBot
Sports PA / NYE / live-events catalyst — simple in name, broad in use. Patent expansion vehicle for stadium-scale temporal coordination.
EventTimeNotificationBot
The site’s public broadcast bot. Scan, /start, and you’ll be notified of Living Laboratories updates — including auction open & close times.
Scan to
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🌊 Be in the record
Subscribed and got a useful event notification? After a successful event, EventTimeNotificationBot will politely ask if you'd like to leave a testimonial. Reviewed and posted to /testimonials/ with your first name and the date — or anonymously. You'd be among the first names on a public record of a patent-protected substrate that solves something today's Large Language Models fundamentally cannot.
Read what others are saying →🏦 Trading & Risk Management
The temporal-awareness engine applied to financial-position monitoring, algorithmic-trading oversight, and threshold-bound capital-markets operations. See the spotlight at the top of this section for the full architectural-superiority case. Pre-auction inquiries from qualified institutional buyers welcome.
ReachingRLimitsBot also in Deficit-Aware
The threshold-approach bot from the Deficit-Aware Family, featured here as the trading-floor vertical's headline application. Position limits, P&L drawdown, VaR, exposure ceilings, algo heartbeats — all of it on the same continuous-pressure engine with agency-first escalation and a deterministic audit trail. See the full card in Deficit-Aware ↓
More trading-floor bots
Specialist bots for prime-brokerage limit monitoring, algo-trading heartbeat watching, market-maker inventory deficits, and exchange-clearing reconciliation can be specified on demand. We hold the patent and the engine; verticals get built around qualified-buyer commitments.
🎓 Education & LMS Retention
The temporal-awareness engine applied to Learning Management System data signals — student-side first, instructor-side second, institution-side as the safety net. Higher-ed, K-12, special education, accessibility services. See the Education & LMS Retention spotlight above for the full architectural-superiority case. Pre-auction inquiries from qualified institutional buyers welcome.
StudentsGradesRSlippingBot also in Deficit-Aware
The LMS-tracked academic-deficit bot featured in the Education spotlight above. Student-first agency, then instructor, then advisor, then dean. FERPA-friendly by Person-of-Concern First architecture. See the full card in Deficit-Aware ↓
More education bots
Specialist bots for university accessibility offices, K-12 IEP-tracking, homeschool/unschool temporal coordination, exam-prep cycles, and faculty workload-monitoring can be specified on demand. The engine and patent are in hand; verticals get built around qualified-buyer commitments.
🚗 Navigation, Transit & Road-Time Awareness
The temporal-awareness engine applied to relative-time-to-hazard signals on the road. Drivers, fleet managers, insurance telematics, OEM nav, dash cams, municipal traffic safety. See the Navigation & Road-Time Awareness spotlight above for the full architectural-superiority case. Pre-auction inquiries from qualified institutional buyers welcome.
ETA@TrafficEmergBot 🚗 Spotlight Vertical
@ETATrafficEmergBotThe relative-time-to-hazard bot. Today's navigation apps warn about speed traps, accidents, road closures, and hazards using point-events with distance triggers — pings fire at 1km, or 500m, or sometimes after you've passed the hazard. None of them have temporal awareness of YOUR relative arrival time. This bot does. The driver configures their own reaction window. Pressure builds based on time-to-arrival (computed from current speed, road conditions, deceleration profile, hazard confidence-decay). The warning fires when YOU can act on it — not when geometry happens to trigger it. Designed for: drivers (Telegram/voice integration), fleet-management dispatchers, OEM navigation systems, insurance telematics programs (measurable improvement in safe reaction-time = direct premium discount integration), municipal traffic-safety initiatives.
More navigation bots
Specialist bots for fleet-route deviation watching, hazard-confidence-decay aggregation, OEM in-vehicle voice-coach integration, motorcycle/cyclist safety variants, and elder-driver reaction-window calibration can be specified on demand. The engine and patent are in hand; verticals get built around qualified-buyer commitments.
🎯 See a category you’d use — or a vertical we should build for?
Email hello@livinglaboratories.org with the bot name and your use-case — we prioritize what gets built next by who’s asking. Whether you’re a researcher, a procurement office, a caregiver, or a developer with an integration idea, the catalog above is partly a roadmap and partly a demand-signal capture.
Reserved bots have their Telegram namespace locked in, so the brand and patent coverage are protected even before code ships. Live bots have been validated end-to-end with real users.
The family adds up to something bigger than any single member. Every bot is a different pressure source on the same patent-protected temporal-awareness engine.
The Time-Blindness Problem in AI
Today's AI systems have no native sense of time. They answer a question, then forget the question, the person, and the moment. They cannot watch a process unfold, cannot remember to follow up, cannot escalate when something stalls, cannot reason about what is happening now versus what happened ten minutes ago.
Recent independent confirmation: In May 2026, researchers from Carnegie Mellon, UNC Chapel Hill, and Pittsburgh published TimeBlind — a rigorous diagnostic benchmark showing that every frontier video-language model, including GPT-5 and Gemini 3 Pro, scores only 48.2% on temporal-reasoning tasks where humans score 98.2%. Scaling parameters 10×, adding frames, or maximizing test-time reasoning does not close the gap.
Read our analysis of TimeBlind & how the patent family is its operational counterpart →
June 2026 — the model confessed: Two Google accounts, same prompt, Gemini Flash confessed twice on the consumer surface that it does not perceive time between turns. The Treatise consolidates the academic finding, the live confession, and the operational substrate into a single industry-claims paper-of-record.
Every industry that depends on real-time coordination — logistics, healthcare, manufacturing, time-and-motion studies, scheduled service work, consumable lifecycle management, customer-service follow-through — is bottlenecked by this single architectural gap.
The Temporal Awareness Patent Family solves it: a deterministic, audited, time-bound coordination architecture that gives AI agents persistent temporal presence. The work is done, the patents are filed, the reference implementations are running in production.
Temporal Awareness Patent Family
Sole-assignment sale of a complete patent vertical — the architecture, the working reference implementations, and the deterministic auction mechanism that enforces its own close.
What is being sold
A complete patent vertical, sole-assignment, transferred in whole:
- KB-2026-006-TA Burton Temporal Envelope Model (parent scientific filing — framework)
- CIPO CA 3,310,722 Temporal Awareness Applications
- CIPO CA 3,311,976 Temporal Consumable Lifecycle
- CIPO CA 3,311,977 Purposeful Temporal Awareness with Memory
With right to file U.S., E.U., and PCT continuations. Working reference implementations transfer with the family. Full bidder material, demonstration recordings, and sealed-bid terms are released to approved bidders only.
Access
Bidder access is reviewed individually. The bidder portal contains sale terms, the Form NDA, the sealed-bid template, the live auction state, and the demonstration material.
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Send a brief introduction. Approved requests receive a unique access code by email.
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Found a snag? Got an idea?
Living Laboratories is exactly what it sounds like — a place where these bots come alive in the wild, with real people, doing real things. Your feedback is what shapes the next version.
Send a quick note to hello@livinglaboratories.org — or, if you're already chatting with DoNotLetMeForgetBot, just type /suggest your idea and it'll come straight to me.