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Replacing your Proposal Team with ChatGPT

September 9, 2025September 9, 2025Scott S NelsonLeave a comment

I’ve heard of some businesses that have completely automated their RFP response process using Agentic AI. To reach that level of automation, you either need a very narrow set of services or a very generous budget to address all the quirks and exceptions.

I have neither of those.

Before I go on, I want to point out that while I will definitely continue to use Generative AI with all of my documentation as tool to improve quality, I much prefer working with a human team that is AI-augmented rather than just AI. It is a strain being the only one managing the human factor of work that is meant to drive decisions. The title is not a suggestion; it is a description of how to cope when it is necessary.

What I do have is access to a few Generative AI tools. For various reasons I won’t get into here, ChatGPT Projects is the best fit for the workflow I have adopted (and still refining). Projects are ChatGPT’s (poor) answer to NotebookLM and Perplexity Spaces

(see my earlier post about Organizing AI Augmentation with Notebooks).

Projects are useful in that they keep related prompts and files in one place, but they don’t really cross-reference or allow for collaboration. It does come with that fine print at the bottom of the screen stating:

“OpenAI doesn’t use [NAME OF COMPANY PAYING SUBSCRIPTION FEE] workspace data to train its models.”

Which is the main one of those reasons I said I wouldn’t get into (oops!).

I recently worked on a proposal at a time when most of the people who would usually help were busy with other things, so I settled into working mostly with ChatGPT like an eager-but-green proposal teammate (the AI being the green one, not me…no matter what that LLM wrapper says).

Setting the Stage

For this particular proposal, the prep work didn’t look all that different from the old manual process. It starts with a short document to capture the proposal’s guiding themes: my company’s strengths, differentiators, and the ideas that needed to shine through in both tone and substance. The document was mostly drafted by practice leadership and refined with a few folks familiar with client, project types, or both.

Next came the outline. Depending on the RFP structure, I sometimes let ChatGPT take the first crack at building an outline from the document, then refine it interactively. Other times, the RFP format or flow is not friendly to automate parsing, even for a well-trained AI (or so I assume, as I haven’t attempted to train one that deeply yet). In this case I build the first draft of the outline myself, then hand it to ChatGPT to check against the original RFP. That combination of back-and-forth has become standard practice.

Draft One: Enter the AI Intern

Once the outline was in good shape, ChatGPT proactively offered to populate the template once it was refined, which fits with the persona I have of it as an eager, educated, and inexperienced intern or junior associate. And given the quality of its suggestions, it is tempting to respond with a “Yes” and let ‘er rip. But tempered experience had me opt for prompting it to do so one section at a time, and waiting for feedback or confirmation before moving on to the next section. In this manner, I was able to put together a pretty decent first draft much faster than doing it entirely on my own (or even with a “real” eager, educated, and inexperienced intern or junior associate, whom I also would not want to do a full draft before getting some feedback).

I would say it was about 50/50 of accepting the first draft of a section versus a revision. As with any Generative AI augmented content generation, most of the issues stemmed from missing levels of details in my prompts versus ChatGPT misunderstanding the intent. Speaking of understanding the intent, I attached the entire proposal (again, because, like I said, I know notebooks and spaces and projects ain’t those), the outline, and the context document after it asked to write the proposal for me, and tempering the response to its offer with “Yes, but…” and then instructions to do it a section at a time and refer to the files.

Staying Sane (a.k.a. Breaks Matter)

As many proponents of utilizing Flow will tell you, it can be very beneficial to take breaks every 60 to 120 minutes (while most of the gurus on the topic seem to gravitate to the 90 minute mark, I hold fast that it varies by person and context, mangling Bruce Lee’s advice to “be like water”, in this case by seeking your own level). Without breaks, your ability to be objective about the quality of GenAI outputs will start to degrade and tilt where your bias is, i.e., past one’s threshold of real focus, some will start accepting every output while others will either keep refining the prompts for sections over and over or just re-write it by hand.

The Human Touch

After ChatGPT’s draft, it was time for the what passes as human intelligence (I used to call coffee my “artificial intelligence” until the term started being used by everyone to refer to what we currently call AI). I have enough experience (and ego) around writing proposals, and made some minor edits of the first AI generated draft. Once that first draft was completed, I dove in to give it a serious human touch, reading through the entire draft and making notes of changes I thought it needed. That read through without editing may seem counterintuitive, but it is necessary because something that jumps out at me as being incomplete, inaccurate, or just plain wrong may be clarified later in the document. After a top to bottom read and making notes of changes, I then work through the notes to actually make the changes, skipping or revising those changes with the full context of the document.

Then it’s ChatGPT’s turn again. I have it go through the document, essentially repeating what I had just done. This is a process I have worked on in other forms of writing as well, and I have a general prompt that I tweak as needed:

Check the attached [PROPOSAL FILENAME] for spelling errors, grammar issues, overall cohesiveness, and that it covers all points expected as a response to [RFP FILENAME].

Only provide detailed descriptions of any corrections or recommended changes so that I can select the changes I agree with. Think hard about this (thanks to Jeff Su‘s YouTube channel for this addition!)

And then I work my way through the response. This same prompt is re-run with updated versions of the proposal until I am satisfied that this stage has yielded as much benefit as it can.

Tightening the Screws

Finally, (or almost so) I have ChatGPT draft the executive summary. In the case of a really big RFP response, I will first have it draft the section summaries. These summaries are necessary to any proposal. In fact, they often make or break the proposal, possibly because they are the only parts the decision makers read, sometimes along with reviews done by others. If the summaries don’t come easy, or don’t sound right based on that original context document, I will go through and collaboratively revise the relevant sections until the summaries flow.

The Final Check

Finally, I try my best to find another human to check the whole of the result. If I’m lucky, I get additional input. If I’m really lucky, they’ve brought their own GenAI-assisted reviews into the mix.

GenAI has had a major impact on my writing output. The flow I use for proposals isn’t all that different from the flow I use to write blog posts or other content. I do a number of stream-of-consciousness sessions (the number varying on the complexity and length of the content), and then start refining it. I used that approach before GenAI, and the key difference that GenAI has made in my process is that I have learned to do less self-editing during those initial brain dumps, because I know that I have a tireless editor to review and give me feedback during the editing phase. Plus, the editor can be coached in both my intent and style to help me improve beyond just the level of “not clear”, and “i before e except after c or when the dictionary says otherwise”.

A Biased Review of an Unbiased Study on Developer Productivity with AI

August 18, 2025Scott S NelsonLeave a comment

A long time friend sent me a link to Does AI Actually Boost Developer Productivity? (100k Devs Study). While writing my response, I realized my reaction was a bit more than a chat reply, so I’m sending him a link to this post and hope he forgives me for the delay…

After watching this video of Yegor Denisov-Blanch, my inner critic wants to jump straight to:
He referred to mid-range engineers at the outset, in the context of who Meta said they were cutting. It wasn’t clear if the study participants were mid-range.That out of the way, I’ve seen similar studies, though this is the best so far, based on number of participants, approach, and level of detail. Those other studies had the boost at 0 or less, and I didn’t trust the data but did recognize the premise. The premise being that AI is a multiplier, and if a developer tends to go down rabbit holes rather than focusing on the business goals, they will go deeper down rabbit the hole and become even less productive.

I think another aspect that is lost in these studies is that it is a paradigm shift, which means even the most experienced are still figuring out how to be productive in their use of AI. Since everyone is finding it so easy, no one admits that it takes some getting used to. That will account for some of the productivity hit.

One aspect Denisov-Blanch spends a good amount of time on where the mass media usually skims or skips entirely, is the difference between greenfield and brownfield projects. The difference is huge, where brownfield productivity gains are much lower. This information is critical to businesses that are planning on reducing their development teams based on published gains, since, for most enterprises, the majority of work is decidedly brownfield.

We also haven’t yet seen the impact of greenfield applications built primarily with GenAI when it comes to long-term maintenance. Yes, we have seen some anecdotal results where they are disastrous, from both a security and CX perspective, but we haven’t seen anything at scale yet. As an architect I am probably biased, but I don’t have much confidence in GenAI to create a reliable and flexible solution for no other reason than most people don’t think to ask for one at the start (except maybe architects😊).

The tools are improving (this based on anecdotal evidence from people who have both a high degree of skill as a developer and demonstrated critical thinking about tools and processes in the past). The people using the tools are becoming more skilled. So the gains in productivity will likely either climb across the board, or those below mid-range may crawl up from the less-than-zero productivity zone.

Meanwhile, anyone looking to cut their developer workforce in the next couple of years should watch this video, draw their own conclusions, and then revise their estimates.

Boost Your GenAI Results with One Simple (and Free) Tool

August 12, 2025Scott S NelsonLeave a comment

AI is great at summarizing a document or a small collection of documents. When you get to larger collections, the complexity begins to grow rapidly. More complex prompts are the least of it. You need to set up RAG (retrieval-augmented generation) and the accompanying vector stores. For really large stores, this is going to be necessary regardless. Most of us work in a realm that is between massive content repositories and a manageable set of documents.

One handy helping application for this is Pandoc (https://pandoc.org/), aptly self-described as “your Swiss Army knife” for converting files between formats (without having to do “File > Open > Save As” to the point of carpal tunnel damage). Most of our files are in people-friendly formats like Word and PDF. To an LLM, these files contain mostly useless formatting instructions and metadata (yes, some metadata is useful, but most of it in these files is not going to be helpful as inputs to GenAI models). Pandoc will take those files and convert them to Markdown, which is highly readable for GenAI purposes (and humans can still parse it — and some even prefer it) and use 1/10000000th of the markup for format (confession: I pulled that number out of thin air to get your attention, but the real number is still big enough to matter).

The conversion may not be perfect, especially as the formatting of most documents is not perfect. You can see this for yourself by using the Outline view in Word. With a random document pulled from SharePoint, odds are you will find empty headings between the real ones, entire paragraphs that are marked as headings, or no headings at all because someone manually formatted text using the Normal style to make it look like a heading.

If you are only converting a few documents, you can use a text editor with regex (provided by your favorite GenAI) to do find and replace. Otherwise, leave them as is — it is already in a much more efficient format for prompting against, and the LLM will likely figure it out anyway.

You can get fancier with this by incorporating a call to Pandoc as a tool in an agentic workflow, converting the files at runtime before passing them to an LLM for analysis (and if you are a developer, managing the conversions so that they aren’t wastefully repeated). So long as you are being fancy, you can have it try to fix the minor formatting errors too, but you have already made a huge leap forward just by dumping all the formatting (that is just noise to an LLM) so that the neural network is processing what really matters: the content that is going to make you look like a prompting genius.

Google and Microsoft battle of the AI Notebooks

Organize AI Augmentation with Notebooks

June 30, 2025June 30, 2025Scott S NelsonLeave a comment

I threw up a quick post about vibe writing a couple of months ago that did not go viral (similar to my other work). For that session I bounced between the free version of Perplexity.ai, Microsoft Copilot, and Google’s NotebookLM (both with a business license provided by my employer). It was very productive, with the results easily stored in NotebookLM for later reference.

Last week, I noticed a Notebook feature added to the Copilot screen and thought I would give it a whirl.

The two products have a lot in common. You can load sources to the notebooks, you can chat with the GenAI to analyze or reference the content, and they will both generate an audio summary formatted like a podcast. In that last part, NotebookLM has a maturity advantage both in how long the offering has been available and the capability to control the output.

Both provide easy access to their associated cloud storage. Again, NotebookLM shows the advantage of experience, having incorporated web search discovery for external references.

Copilot Notebook is part of the full Copilot suite of functionality, making it easier to incorporate AI work done earlier and shared functionality within your organization, where Google has its regular menu which is a lesser UX IMHO.

The AI space has a lot in common with New England weather. If you don’t like how it is right now, just wait a bit, it will change fairly soon. I’m pretty sure the Copilot Notebook UI changed just in the week from when I discovered it and today, but I can’t say for sure. Today, if I have my choice (and I do), I would go with NotebookLM for research where I don’t need any sensitive files from Microsoft Office as input, and Copilot Notebook for things where keeping the secret sauce secret is important. That is very much predicated on Office 365 being the collaborative standard in my organization, so YMMV if you don’t.

Not to leave the third participant of my original vibe writing post out, I acquired a Perplexity Pro license since that earlier post and have begun to use their Spaces functionality to have contexts similar to the Notebook offerings. It doesn’t have an audio summary option that I’m aware of, but otherwise I like how it will incorporate references from the internet with attributions for verification. It’s my personal pro account, so I don’t load any work files into it. I do find it useful writing and research. While it does not hallucinate, it is limited to the majority of what is posted online (unless I have time to prompt it along). I originally wanted to have it write the majority of this post, but the content it came back with was not entirely accurate in the areas of capabilities, so I wrote the first part the old fashioned way.

I’m including the final draft that Perplexity came up with, as it has some good info that bears sharing, but doesn’t bear retyping to claim it as my own. Any discrepancies between what I have already written and the following, my opinions and observations are contained in the former.

Microsoft Copilot Notebooks vs Google NotebookLM

Both platforms promise to make knowledge work more efficient, but their philosophies and user experiences diverge in meaningful ways. Microsoft Copilot Notebooks leverages the deep integration and security of the Microsoft 365 ecosystem, offering a persistent, project-based workspace where AI is grounded in your organization’s documents and conversations. Google NotebookLM, by contrast, is built for flexibility and collaboration, allowing users to aggregate a wide variety of sources, query them conversationally, and generate structured outputs like summaries and study guides.

The stakes for choosing the right tool are high: the right architecture can amplify an organization’s collective intelligence, streamline workflows, and unlock new levels of productivity. Below, I explore how each platform approaches the core challenges of knowledge work—aggregation, synthesis, collaboration, and control—before distilling the comparison into focused tables for quick reference.

The Modern Knowledge Workspace: Context and Control

Microsoft Copilot Notebooks is designed for those who want a unified, persistent workspace where every piece of project context—chats, files, meeting notes, and links—lives alongside AI-powered analysis. The AI here is not a generic assistant; it is tightly constrained to the content you provide, ensuring that responses are both relevant and secure. This approach is a natural extension of Microsoft’s enterprise-first philosophy, emphasizing compliance, data privacy, and seamless integration with tools like Teams, Outlook, and SharePoint.

Google NotebookLM, meanwhile, takes a more open-ended approach. Users can upload PDFs, Google Docs, Slides, and even web content or YouTube URLs, then interact with the AI in a conversational manner. The platform excels at generating structured outputs—summaries, FAQs, timelines—grounded in the uploaded sources, with every answer backed by citations. Collaboration is a first-class feature, with advanced sharing controls and analytics available for power users.

AI as a Creative and Analytical Partner

Both platforms position AI as more than a search tool: it’s a creative and analytical partner. In Copilot Notebooks, the AI can identify themes, answer questions, and draft new content, all within the boundaries of your project’s data. NotebookLM, on the other hand, is optimized for rapid synthesis across disparate formats, making it ideal for research-heavy workflows or teams that need to generate insights from a broad array of materials.

The distinction is subtle but important: Copilot Notebooks is about depth—drilling into your organization’s knowledge base—while NotebookLM is about breadth—pulling together insights from a wide range of sources.

Licensing and Ecosystem Considerations

Choosing between these platforms is not just about features; it’s about fit. Copilot Notebooks is available only as part of a Microsoft 365 Copilot license, targeting organizations already invested in the Microsoft stack. NotebookLM offers a more accessible entry point, with free and paid tiers, and is available to most Google Workspace users. Both offer enterprise-grade privacy, but their licensing models reflect their intended audiences and integration philosophies.

Feature Comparison

Feature	Microsoft Copilot Notebooks	Google NotebookLM
Content Aggregation	Aggregate chats, Microsoft 365 files, meeting notes, links, and more in one place.	Upload PDFs, Google Docs, Slides, websites, YouTube URLs; manage all sources in a unified panel.
AI-Powered Insights	Copilot analyzes notebook content to answer questions, identify themes, and draft new content grounded in your data.	Conversational AI provides answers with citations, generates summaries, FAQs, timelines, and briefing docs, all grounded in your sources.
Audio Overviews	Generate audio summaries with two hosts walking through key points.	Audio Overviews with interactive AI hosts, listen on the go, higher limits in premium tiers.
Collaboration	Currently lacks real-time sharing or collaborative editing.	Advanced sharing, including “chat-only” mode and notebook analytics in Pro tier.
Integration	Deep integration with Microsoft 365 apps (Teams, Outlook, Word, PowerPoint, etc.), seamless import/export.	Integrates with Google Workspace; supports a wide range of file types and sources.
Customization	AI responses based on notebook content; less customizable chat settings.	Chat customization, adjustable response styles, and analytics in Pro tier.
Limits	Governed by Microsoft 365 subscription and license tier.	Free and Pro tiers: Pro offers 5x more notebooks, sources, queries, and audio overviews.

License Model Comparison

Aspect	Microsoft Copilot Notebooks	Google NotebookLM
Eligibility	Requires Microsoft 365 Copilot license; only for business/edu accounts, not for personal/family use.	Available to most Google Workspace and education accounts; Pro/Enterprise tiers for advanced features.
Pricing	$30/user/month (annual subscription), as an add-on to qualifying Microsoft 365 plans.	Free basic tier; Pro and Enterprise tiers offer higher limits and premium features, pricing varies by region and subscription.
Trial Availability	No trial for Copilot; must have a qualifying Microsoft 365 plan.	14-day full-featured trial for up to 5,000 licenses in Enterprise.
Data Residency/Compliance	Built on Microsoft 365’s compliance and security standards.	Multi-region support, including EU and US, with enterprise-grade privacy controls.

Perplexity Sources:

UpNote or Evernote? The Journey and Decision

May 17, 2025Scott S NelsonLeave a comment

This is a sequel to Will UpNote replace Evernote?

I don’t make new year resolutions, and if I did, I wouldn’t pick procrastination as something to work on because I know I would end up putting it off. Like this post, that would have been great to finish right when I thought of it and even better to push out with the flood of New Year’s resolution posts like how to get organized and reduce unnecessary spending, both of which UpNote has helped me with. So, here we go (and I guarantee I will also procrastinate editing before posting).

First off, rather than a big conclusion, that would be much shorter for you and much harder for me (one of my favorite quotes is “I would have written a shorter letter, but did not have the time.”), I am going to share my (mostly) raw notes that I posted on my original blog post as comments to track the journey.

And here is the TL;DR – I made the switch from Evernote to UpNote driven more by my annoyance with Evernote (specifically, Evernote under Bending Spoons) and less by being enamored with UpNote. But, while there are a few features I miss from Evernote, now that UpNote has become part of my daily (almost hourly) life, I do find that most of the user experience is happier (especially now that I have added many keyboard shortcuts to muscle memory), and the support is so incredibly superior as to be no comparison.

June 25, 2024 / 5:50 am

Since no one ever comments here, I feel free to do my addendums in the comments for now (until I break this up into a series?).

While the cheaper side of me really wanted to use a monthly subscription to try out the Evernote to UpNote migration and only commit to the lifetime after trying it out, the time management side of me won out because

“You can switch from a monthly subscription to a lifetime upgrade from the Premium screen (go to Settings ? Premium). The app will first ask you to cancel your existing subscription to avoid being charged twice, and then let you purchase a lifetime upgrade.”

(https://getupnote.com/support.html).

The migration is fairly easy, (though not so much if you want to experiment like I did).

I first imported with the option to turn tags into notebooks. The resulting layout was a flattened hierarchy, which means I have to recreate (and finally reorganize) my tag hierarchy.

I was curious if using tags instead of folders would be more suitable, so I deleted all of the notes to re-import again. This is when I discovered there is no mass delete for notebooks, only their contents. Well, I would use them again anyway, so I wasn’t too annoyed.

After re-importing with the tag-to-tag option, I realized that since I couldn’t bulk delete notebooks, this would leave me with the too-tedious-to-consider process of moving notes to notebooks individually (in Evernote, across 3 notebooks, I currently have ~3k notes).

I thought I would be clever and try re-importing the same notes with the tags-to-notebooks option with the hope that it would recognize that everything was a duplicate and just put them in notebooks. Alas, I just wound up with duplicates of every note, half with tags and half in notebooks.

UpNote, if you are reading this, you should offer an option to create both tags and notebooks (at the same time) when importing!

So, I deleted all the notes again and imported as notebooks. I do like the ability to create my own notebook covers (on Windows 3.1, I had icons on folders because that’s the kind of childish nerd I am). And I really like the ease of finding notebooks to link to notes. It reminds me of how easy Evernote was to use when it was a note organizing app and not an investment vehicle.

June 26, 2024 / 6:13 am

Continuing my transition description, I have only migrated my personal notebook from Evernote, leaving my work notebook for later. The work notebook has more notes (~1400 vs ~850), which partly informed the choice. Another difference is I use my phone more often for personal notes than work notes, so this gives me more opportunities to note how it works across devices. My initial observations is that search is much faster in UpNote, which can be attributed to the smaller amount of content. But the key thing for me is how Evernote change the home screen from what used to be notes with links to other features to a list of the other features where I have to first select notes (the only function I use!) and only then can I start using the app for its primary purpose. In UpNote it opens directly to the notes, and that changes in notebooks and tags do not change the sorted order of last updated (as some recent changes in Evernote do).

June 28, 2024 / 6:28 am

If the visual representation of your current tag hierarchies in Evernote are numerous, complex, and important to you, migration is going to be disappointing. Even if you select for the imported tags to be converted to notebooks and to import into a notebook, the result is that all of the notes are imported in a flat list in the selected notebook and all of the tags become notebooks at the root level without their prior hierarchy.

If I were in a rush to move, this would be a deal breaker for me. Fortunately, I have a little over 3 months for this migration, and the re-creation of my hierarchies and cross tags (notebooks in UpNote) is interesting, even fun at times…so far. A couple thousand notes to go, so we’ll see…

June 29, 2024 / 8:41 am

One features from Evernote that UpNote could benefit from is drag-n-drop for the notebooks. Yes, they are tags in Evernote, but since UpNote doesn’t have a tag hierarchy, UpNote Notebooks are feature parity to Evernote Tags. I do like being able to customize the notebook covers in UpNote (used to do that to folders on a Windows 3.1 desktop), but drag-n-drop is a much more practical feature, especially for those of use migrating. The click, select, select, click process is fine if one doesn’t organize much but gets really tedious with 100’s of folders to re-organize after migrating.

July 7, 2024 / 10:46 am

It took 3 weeks to finish re-organizing my personal notebook and a notebook from a former job in UpNote after importing them from Evernote. I used UpNote for all personal notes during that time as well.

To summarize my thoughts and experiences so far:

UpNote notebooks are the equivalent of tags in Evernote based on Evernote tag features, so if you use the tag hierarchy in Evernote have UpNote convert them to notebooks on import.
The ability to customize the covers of Notebooks is nice.
Many will want to use the colors provided or the pre-loaded images.
I created my own, which suits my own way of sorting and provides a great source of procrastination activity.
UpNote doesn’t have the feature clutter of Evernote.
No calendar and no events.
Tasks are integrated into notes (if the note has a checklist it is categorized as a task in UpNote).
It is great to be able to go straight to notes again instead of having to click through the cluttered Evernote UI.
UpNote doesn’t change the edited date when changing metadata (a recent bug in Evernote that is driving me nuts!)

In the negative column for UpNote:

No reminders.
No feature to email the contents of a note from within the app.
No drag-n-drop for nesting notebooks

However…

UpNote lifetime pricing: $39.99
Evernote annual pricing: $129.99
Monthly options: $1.99 vs $14.99

I really will miss the reminders and being able to email notes to myself for follow up through my in-box, and I expect that UpNote will eventually add these features. And I am not looking forward to a month of re-sorting a decade of content when I bring my work notebook in. In fact, if Evernote had stuck to the $49.99 per year, I would have dealt with the mobile UX going down hill to keep the features and save the work. But Evernote went from supporting users to supporting investors, and Bending Spoons just wants users to bend over and pay even more for AI features that are available one window away for free, so I will not be renewing my subscription next year, ending almost 20 years of customer loyalty.

July 15, 2024 / 6:17 am

I still need to turn these comments into the Part of this post. Meanwhile, ran across an interesting read today that leads to the need for a note app, though for the use case given One Note would be sufficient: https://fev.al/posts/work-journal/?utm_source=tldrnewsletter

July 17, 2024 / 6:45 am

Forgot to mention: The idea of importing back into Evernote isn’t supported by either app. Reminds me of portal platforms back in the early 00’s when they were all proprietary to lock customers in, then later in that decade they all started using “open” standards, which resulted having proprietary formats that would fit in those standards. In this case, both will export to HTML or Markdown but the outputs drop all of the organization.

Crossing my fingers that UpNote gets the long ride Evernote has had.

July 20, 2024 / 9:17 am

I reviewed the FAQ page about security. For a non-technical person it can be very confusing. For a technical person it is still confusing. I truly don’t think this is intentional.

To summarize:
There are two key questions whose answers are relevant…
UpNote stores data on the Firebase server (which is a service provided by Google). The Firebase platform is certified to major privacy and security standards and fully supports the EU General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). Firebase encrypts your data in transit using HTTPS and encrypts your data at rest. You can learn more at https://firebase.google.com/support/privacy. We also take great care to ensure that your data is secure and only you can access it.

and
End-to-End Encryption (E2EE) is an advanced security method for encrypting and decrypting data and is designed to protect highly confidential information. Due to the complexity of implementation, UpNote currently has no plans to support E2EE. If you wish to store sensitive information such as passwords or credit card numbers, it is recommended that you use a password manager application specifically designed to encrypt sensitive information.

The gist of which is that the data is not encrypted on your devices. This is a bit of nit-picky difference but worthwhile to note that the weak link in the chain is how you manage security on your device. There is also the bit about UpNote developers being able to access your content. They are up front about that, and also up front about storing private data in secure manner, like a password manager.

July 28, 2024 / 10:08 am

In Evernote, tags exist as a flat hierarchy, with the nesting only being at a visual level. For example, if I have a tag Misc and then move it to be under Foo, I cannot create a tag under Bar named Misc. While UpNote also manages tag in a flat hierarchy, Notebooks are truly nested, so I can have a notebook named Misch under Foo and a different notebook under Bar also named Misc. I can then cross reference between notebooks using a tag such as #reference. This is much more how these things work in my head. Your mentalization may vary.

August 1, 2024 / 7:37 am

I love the Collapsible Section feature in UpNote. I often used Evernote for presentation notes. The first annoyance in Evernote was when they added wide margins, making it impossible to have both my notes and a presentation on my desktop at the same time. I would use a tablet or my phone to make up for this problem until I eventually got a 35″ monitor (not for that purpose, but a nice bonus point for the monitor upgrade).

Not only can I size the UpNote window to any width I want, I use the Collapsible Sections to make it easier to scroll through the content based on each slide. The keyboard shortcuts are nice touch, too.

August 24, 2024 / 10:50 am

Finally parting shot at Evernote: In preparation for closing my account I went to delete all of my notes. It would be useful if it gave some error message that the default notebook couldn’t be deleted. I eventually figured it out, created a new notebook, and set it as default. Still, 1000 notes wouldn’t delete when deleting the notebook. Finally I had to delete at the note level, which is limited to 100 at a time. Hey, Bending Spoons, it is all the friction to standard note management tasks that drove me away from 21 years of use. Making the final steps as difficult as possible helps to reinforce my decision.

Oh, and then when I actually cancelled the subscription I first had to confirm again (acceptable), then scroll through a huge list of features that I was losing (annoying but predictable), then give a reason from a list, but only ONE reason (ridiculous) and then was finally offered a discount of 40%, which if they had offered that in response to any of my complaints over the last two years I may have accepted, but having just spent two months migrating to UpNote, wasn’t going to happen.

Epilogue

UpNote has become a seamless part of my computing life. It took me so long to post this follow up to the original article partly because I am more productive with UpNote, and partly because it is so smooth to use that I don’t really think about it…except on those rare occasions when there is an issue with an update, the last of which inspired me to finally write this post because of the quick turn-around for the fix as a new update, without any of the “do [some really annoying work around] until we can get to the issue”, which is pretty much the response I get from most vendors, and extra annoying because I include the work around in my support request.

Oh, and after you get your own license, be sure to follow the great user community at https://www.reddit.com/r/UpNote_App/.