Show HN: Dlog – Journaling and AI coach that learns what drives wellbeing (Mac) (dlog.pro)

Thanks so much for the feedback! Below are my responses.

- Is it a project management tool? If so, how do I share everything with my team? Project management tools are defined by their collaboration and workflow features.

Dlog is not meant to be shared with a team; I will look at enterprise versions later on; but for now, a Blog is public, a Dlog is private. So, the project management definition here has been relaxed to mean a journal with a reminder list(or lists) organised by goals; the timeline view allows you to track these.

- Is it a journaling tool? If so I absolutely don't want my team in the tool, and so can't use it for project management. How does it encourage me to do better journaling and build the habit?

It absolutely is a journaling tool, and so your team can never view these; I am working on a feature for you to tag whether a journal is for work; this will impact the coach responses; and could be used later on for the enterprise version (targeting this for next year at some point). In terms of encouraging you to do better journaling, when you start a New Dlog there at the top left is a toggle called “Journal Coach”, there you can get prompts on the 4-rings (i.e. the Dlog Model at the heart of the app that trains your Dlog Coach is based around the 4 main constructs, Personality, Character, Resources and Well-Being); or ask it for feedback on whatever you are journaling about.

- Is it a wellbeing tool? How well does that work if I don't put my project management in there? If I can't use it for half the stuff it's intended that I will, then it might be of limited use.

Dlog is based on the 4 constructs of Personality, Character, Resources and Well-Being. The Coach will give advice from day 1 after you have taken the baseline survey. It doesn’t matter if you do not use the project tool and just use it for journaling. Projects work in tandem with goals as well. I am keen to hear what features you’d like in the project management side or any other area you would like to see improvements in. I do recommend that you watch the youtube video (if you haven’t already) I made for Show HN in the original post. That should (I hope) explain how this works, but it is unvarnished and 15 minutes long, so I need to get a clearer explainer about the main story here.

- Is it a coaching tool? Why would I want to use an AI coach over a mentor or human coach?

The AI coach is deeply informed by the in-built SEM model; the model I developed during my PhD; based on sentiment analysis scoring of your journals (including projects, but again, it’s not required). There are many buttons available in the coach, check out the video for an example of the output, for example, it can say how to “Strengthen Relationships” (that’s the example given in the video), by looking at which important people in your life over time have impacted your well-being positively or negatively over time, and provide a quantitative and qualitative analysis of this; giving advice in terms of how to improve these relationships and protect your mood and affect. Any responses you ask it the Coach will always try to improve your resources and well-being, focusing on the 4 rings and the Dlog model.

- Is the AI required? I have no idea how many tokens I'd need to use something like this? Do I need a million a day or a million a year? (When coding I tend to use ~10-50m input tokens per session, will this cost $500 per day to use?)

Unless you’ve written over 10 million words its highly unlikely that you’ll use a million tokens in one day. 1 million tokens costs 5.99. But if you dm me your email address that you’ve used to sign up with Dlog I’ll give you 1 million and a free perpetual license so you can use Dlog for free forever (excluding the tokens). I’m doing this for all Show HN readers who write me directly.

- If the AI features are optional, what is the product without it? Without the AI, Dlog is still a useful journaling and projects too. You can actually use another website I made cal...

FYI: The new dlog.pro website is now live:

https://dlog.pro/

Responding to concerns regarding "long and rambling".

J.

Thanks for the positive feedback! The LLM aspect is using enterprise API from openAI, their policy is to not train on user data; I've used it extensively for the last year with my own personal diary Dlog data; pretty dry stuff to be sure. However, I will be working on allowing the user to use their own on device models; at the moment running local models is too memory intensive for most users so I need to do this once the models are more compact. Apple have recently allowed developers to integrate AI through their foundation model LLM but the token window is too short, 8K only if I recall correctly; and the responses just aren't that useful. The technology will improve and trust in openAI's systems should increase; we're early days here, but for now the main mechanisms for LLM we are has to be the enterprise openAI; there's nothing better IMO. Another thing I am working on in the short term is mechanisms to anonymise content and approve the prompt before it is sent; as well as a simple toggle that when switched on removes that journal from being included in Coach analysis. Thanks again. If you DM or email me and let me know the email you used to sign up with Dlog then I'll send you a free perpetual license so DLog is free to use forever, excluding the AI tokens; and I'll give you 1 million free tokens. Have a wonderful day. Dr J.

Thanks for the feedback. I love Obsidian. All your data is stored on device i.e., in calendar entries (a Dlog is saved in your default calendar, that's why you don't need to sign in to use Dlog; the title and text of a calendar event are repurposed in Dlog to be a journal; much like the reminders have been repurposed to comprise projects) and on the in app on device Rag database, it is not stored in the cloud etc., so you do own all the data; and it is not shared to the Dlog server which is only used to track token usage. GPT 5 is necessary for the moment; Dlog uses the enterprise API, so it doesn't train on your data. However, I know this is a major concern for many, so, in the short term I will be adding an anonymiser; and the ability to approve and edit prompts sent. If you do decide to sign up to use Dlog send me a DM with the email used to register and I'll send you a free perpetual license so Dlog will always be free (excluding tokens for AI use) and 1 million free tokens. Thanks again!

Thanks so much for your detailed feedback and for watching my rather unvarnished intro video with too many ums and ahs!

- Calendar is central, but I use a Google calendar which is important to me. Connect it? Dlog will use the default apple calendar which, if is your Google calendar, will display automatically. - Seems like a "dlog" is a calendar entry. So is my "journal" broken up into separate pages, not a sequential document or blog?

Not quite, a calendar event has a title and notes. The title of the dlog will be whatever you call it, the default is (if your name is anon) Anon’s Dlog. The notes of the event are where the journal entry is stored; along with Dlog tags such as goals, journal type, and sentiment scoring. - 2:30 ff, strongly suggest that for your next video you pre-script it to avoid fumbling and mumbling.

Yes, agreed, I made that very quickly yesterday. I’ll re-record it today. I still want to keep it quite unvarnished though as the HN mods told me that this is what Show HN community prefers

- 5:10 side note, interesting that your personality(?) model was from 2018, well before LLMs.

Yes, I never dreamed this would be possible until the introduction of ChatGPT. - 7:50 for an app to produce such output (impact of a friend on mood) you surely must do a copious amount of extremely frank journaling. When, and in what format? As scattered calendar entries? I'm confused how I fuel the app.

Yes, you’d just journal normally, as you have various important experiences you can journal about this in free form, stream of consciousness etc.; or use the guided four rings prompts in the Journal Coach at the top left of the Dlog entry area. It doesn’t have to be copious, or systematic, because the model is time series, it doesn’t require fixed repeated entries. If you use Dlog for a few days or weeks I’d be very interested to see if you found the responses useful. And again, if you send me a DM I’ll provide a free perpetual license so Dlog is always free for you to use.

- 10:40 relating diary entries (reported activities and attitudes) to one's stated goals -- this is what I would expect an AI to do, and tell me about them rather than the reverse.

The feature at 10:40 relates to just summarizing the entries that have been added to that goal; it is not related to the AI coach (which does what you’ve stated that you expect i.e. relates diary entries to activities and attitudes to ones goals) - I'm sorry, I just don't see how I could use or adapt to something like this when I have a well-established diary/blog and calendar, it would mean changing many daily habits and adding what looks like a lot of detail work.

Apologies, I do think the technical intro video is giving a lot of behind the scenes background information which may be overwhelming if you’re simply looking to journal and improve well-being.

I would gently recommend that you try it out for a few days and see that it’s fairly intuitive to use and well worth the process once you start seeing the insights from the coach (which get better over time).

Warm regards, Dr J.

Thanks for sharing that story, great cautionary tale about apps that drift from “helpful” into prescriptive/social enforcement.

Dlog takes the opposite approach: • Agency first: The Coach proposes; you decide. No phone trees, no task assignments, no social mechanics. You can ignore, not use or set a low-cadence to the guidance. • Explainability over prescriptions: Suggestions come with a brief “why” based on your SEM reports (which factors moved and by how much) plus charts so you can sanity-check against lived experience. • Local-first privacy: Journals live on-device (EventKit). Scoring + SEM run locally. By default no raw text leaves the device unless you use the coach, this is optional, but there is a bit of a leap of faith here with OpenAI; until I enable on device LLMs in due course. • No hidden incentives: No affiliate nudges, upsells, or growth hacks. It doesn’t decide what you wear/eat or route calls to you; it surfaces patterns (e.g., “energy dips after external calls”) so you can choose actions that fit your constraints.

If that story raised a specific worry: loss of autonomy, privacy creep, or community spam, then does the above address it? I’m especially interested in whether the “why” behind recommendations is clear enough or needs to be tighter.

Fair enough. But, you may not have noticed this edit that was added to the original post which explains I am giving a perpetual license and 1 million tokens to all Show HN readers; i.e,. so no subscription.

For general users it's free for 14 days with 10K free tokens; then its 1.99 per month at the moment. However, for HN readers that DM me or email me (johan@dlog.pro) with the email they register with, I'll give a free perpetual license so there's no monthly fee; and add 1 million tokens.

The only thing I hate more than the idea of a life coach is an AI Life Coach.

It takes all kinds to make the world go round, of course, but the entire vibe of this part of contemporary culture grosses me out and depresses me.

Thanks for this; that parable lands. Dlog’s goal is the opposite: surface your personal patterns so you can deliberately stop, rest, and protect downtime.

Short answer: Dlog’s SEM is built for single-user, explainable, actionable inference. It estimates stable latent factors from many indicators, re-fits regularly to track changing effects, and ties coefficients back to your journal quotes so recommendations are grounded in lived data. SEM is computed on-device.

Why that matters? multiple indicators per construct (the 61 baseline items) reduce overfitting and let the model recover latent traits (Personality, Character, Resources, Well-Being) rather than relying on noisy single measures. AND, its not just the SEM, its mixed methods: dlog model's coefficients are linked to narrative evidence from your entries, giving both quantitative explanation and concrete journal quotes you can inspect.

I’m planning on adding a technical appendix and a white paper when I launch the Dlog Research edition for universities at some point next year. Meanwhile you can read the model summary here:: https://dlog.pro/#dlogModel and download an example mixed-methods report you can make in the Dlog Labs https://updates.dlog.pro/AnonDoe.pdf.

Thanks again for the interest; if you do register with Dlog email me at johan@dlog.pro and I'll give you a free perpetual license and 1 million tokens to test out Dlog.