Like Tears in the Rain: When an AI Tool Took My To-Dos With It

I opened Bee AI that morning—thumb still smudged with coffee—and saw nothing.

For months, this $40 app had been my second brain. Every doctor's visit for my mom. Every offhand reminder. Every "don't forget this" moment had a home there.

Bee wasn't part of my advisory practice — it was a personal tool that made an overwhelming caregiving role more manageable. Keeping her care organized isn't just a productivity challenge — it's a way of making sure she feels supported and heard. This wasn't about 'productivity' in the abstract—it was about making sure my mom's care stayed coherent, and that she felt seen instead of shuffled.

My 200-item task list was gone. Wiped away like it had never existed.

The first wave was disbelief. Maybe it was a glitch. Maybe I hit the wrong button. Then came the sinking realization: After Amazon acquired Bee, support for my Android device ended, and the app disappeared from Google Play. That's when I lost access to my data.

What went through my head? Frustration mixed with irony.

I'd been writing about data sovereignty in my Digital Kaizen work, warning about exactly this kind of thing. Now I was living it.

It was my Blade Runner moment: "All those tasks, lost... like tears in the rain."

The Sting of My Own Medicine

Here's what stung most. I had been preaching the importance of data sovereignty to clients and readers for months.

Own your information instead of renting it from a platform.

When you hand over critical workflows to a startup, you're building on borrowed land. They can sell, pivot, or shut down. When they do, your work disappears overnight.

I called it "vendor risk baked into the pudding."

But I wasn't practicing what I preached. I had no redundant backup strategy for Bee AI. No regular exports. No mirror in something I controlled.

I should have treated Bee as an interface layer, not as the vault itself.

When it vanished, I felt firsthand exactly what I'd been warning about. The tuition you pay for the lesson. I even reached out to Bee directly, multiple times, to ask about the Android app. I told them I was writing about my experience and gave them a chance to respond. I never got an answer. That reinforced for me that sovereignty can't depend on someone else's inbox.

Financial Planning Meets Digital Planning

In my financial advisory work, I see this pattern constantly. We just call it something else.

When clients have most retirement assets tied up in a single employer pension or one big block of company stock, I point out the risk. You're not just betting on the market. You're betting on one institution's solvency and decisions.

If that company changes rules, freezes benefits, or underperforms, your whole retirement plan wobbles.

That's vendor risk. It's baked into the pudding because you're relying on one entity you don't control.

Bee AI was the same principle in a tech wrapper. I leaned too heavily on a single app without backup. After Amazon's acquisition, when Android support ended, I lost my entire productivity stack overnight.

The parallel is clear: diversification and sovereignty. With money, it's spreading assets across tax buckets and account types so no single rule change derails you. With AI tools, it's ensuring your data can be exported so no single startup has life-or-death control.

If you don't design for resilience, you're designing for disappointment.

The Consolidation Reality

AI tools get bought, folded in, or sunset. That's part of the cycle. As users, it means we design for change rather than assume permanence.

When Amazon acquired Bee, I was initially happy for the founders. Two people who worked hard deserved success. I thought Amazon's resources would stabilize and improve the app.

Then I watched the user group on Reddit. Customer service stopped replying. Updates were teased but never came. The Android app disappeared.

When startups get acquired, founders often can't say much due to NDAs. From the outside, it looks like they ghosted users.

I only paid $40 for Bee. No subscription. But I learned something crucial: if you pay very little for a product, you're essentially part of the beta test. You get convenience early, but you take on the risk.

The Hidden Cost of Convenience

Digital Kaizen taught me to see this clearly. The tuition I paid wasn't just about losing data. It was seeing the real cost of convenience when you don't design for resilience.

Here's how I now evaluate the trade-off:

Acknowledge the Exchange If you're paying little or nothing, you're often part of a beta test. Upside: convenience, speed, innovation. Downside: volatility.

Weigh Criticality vs. Fragility Is this workflow mission-critical or nice-to-have? Mission-critical tools (caregiving notes, compliance tracking) can't afford fragility. That's where you need sovereign storage and redundant exports.

Iterate the System Digital Kaizen means small, meaningful improvements. Each experiment that fails forward gets you closer to the resilient system you actually want.

Convenience is seductive. Resilience lasts.

"Convenience is rented space. Resilience is owned land."

Building Second Brain 2.0

When I explored alternatives like Omi AI , I filtered everything through fresh scar tissue from losing Bee AI.

I wasn't hunting for another shiny app. I was designing for resilience.

The biggest shift wasn't about features. It was about where data lives.

Now the centerpiece is my NAS (network-attached storage). Everything flows through hardware I control, not locked in someone else's cloud.

True Data Sovereignty Files, transcripts, and to-dos sit on my hardware. I can't get rug-pulled the same way again.

Privacy and Compliance Client notes and doctor visits for my mom are sensitive. Local storage keeps me in control of privacy without relying on third-party policies.

Future-Proofing with Local AI Having data on my NAS gives me options. I can spin up local LLMs that work directly on my dataset. Faster processing, no data exposure, freedom to experiment.

My redesign starts with a simple mantra: Capture → Structure → Secure. Capture anywhere (wrist/phone). Structure with AI summaries and tags. Secure by saving a master copy to my NAS—with a cloud mirror as redundancy, not dependency. The NAS gives me three key advantages:

Sovereignty:Files, transcripts, and to-dos live on hardware I control.

Privacy:Sensitive caregiver notes and client-adjacent admin live locally first. If you record health visits, follow local law and get consent—ethics first.

Local AI: Running models against my own dataset—fast, private, flexible.

Sovereignty Without Systems Administration

Not everyone wants to run their own NAS. The principle remains: know where your data lives and have the keys.

In my practice, I use tools like Wealthbox for CRM and PreciseFP for onboarding. What I value most is the ability to export—CSV/PDF—so I'm not locked in. Interfaces can change; my vault doesn't.

Simple steps for professionals:

Choose Export-Friendly Tools Even basic CSV downloads give you an escape hatch.

Mirror Critical Data Keep copies somewhere you control. Local folder, trusted cloud drive, or yes, a NAS.

Iterate Over Time You don't need perfect setup immediately. Small improvements compound.

Whether it's client notes in my CRM or AI summaries from meetings, the gold shouldn't be buried in someone else's vault.

Sovereign Quick-Start (10 minutes)

Export one thing (CSV/Markdown) you'd hate to lose.

Save it to a folder named Vault_2024 on your computer.

Sync that folder to a trusted cloud drive.

Calendar a monthly reminder: "Export & Mirror."

Small move, big safety.

"Interfaces are replaceable. Exports are forever."

The Data Sovereignty Imperative

Data sovereignty means your information is governed by laws where you store it, not corporate acquisition decisions. With data breach costs averaging $4.88 million in 2024, control matters more than ever.

The AI landscape is consolidating rapidly. Startups struggle to raise capital. An exit is often better than winding down.

For users, this creates a fundamental tension. We want cutting-edge AI capabilities, but many customers desire to "own" output data since it was created using input they provided. Meanwhile, vendors often provide services cheaply to generate training data for their models.

We become unwitting data contributors while believing we own our outputs.

Building Resilient AI Workflows

The future belongs to AI solutions that prioritize user data ownership as a core feature, not an afterthought.

When evaluating AI tools now, I ask:

Can I export my data easily? JSON, Markdown, CSV anything that gets me out if needed.

Does it work across platforms? Android support disappearing killed Bee for me.

Is there an active community keeping it alive, or does it depend on one corporate owner's whim?

Can I preserve context and memory if I migrate?

The goal isn't eliminating all risk. It's ensuring no single failure can take you down.

Same principle I use with retirement planning clients. Diversify dependencies. Build redundancy. Own what matters.

Data Is Gold

My Bee AI experience taught me something fundamental about our AI-driven future.

We're integrating these tools into critical personal and professional workflows. But we're often surrendering control over our own data in exchange for convenience.

If data is gold, why leave it in somebody else's vault where you can get locked out?

The Digital Kaizen approach means iterating toward systems that work for you, not against you. Small improvements. Thoughtful architecture. Sovereignty over convenience.

Every professional building AI workflows faces this choice. You can rent convenience from platforms that might disappear. Or you can build resilience into the foundation.

I learned the hard way. You don't have to.

It was my Blade Runner moment: "All those tasks, lost... like tears in the rain." I can't control the weather, but I can control the pipes. With sovereign exports, a NAS as my vault, and small Digital Kaizen improvements over time, the next storm won't take my work with it.

Chris Hensley is a financial advisor, podcast host, and creator of the upcoming book Digital Kaizen: Small Loops, Big Shifts in an AI World. With over two decades of experience guiding clients through complex financial decisions, Chris now blends his expertise in retirement planning with cutting-edge tools like AI, voice-first thinking, and behavioral science. Digital Kaizen is a philosophy for those who want to grow sustainably in a world that moves fast—combining human wisdom, technology, and tiny, honest loops of improvement. This article is a preview of the ideas explored in Digital Kaizen, due out later this year.👉 Want early access to tools and insights from Digital Kaizen? https://digital-kaizen-book.kit.com/6a16de43b8

Grab the free Digital Kaizen Starter Guide and explore how to build better systems for thinking, learning, and working in an AI world.