from PlantLab.ai | Blog

Three antique botanical study plates side by side - two vigorous cannabis specimens and one with drooping, ochre-faded lower leaves - above a fine ink rule punctuated with engraved tick marks like a season of logged entries

The Short Version

Between June and August 2026, PlantLab learned to diagnose several plants in one photo, started naming the family of a condition when it isn't sure of the specific name, made model upgrades visible to your code, and fixed an upload failure that took three tries to actually kill.

The middle two change what comes back in your JSON.

I don't write these often. Most of what happens on a project like this isn't worth a post, and I'd rather publish something useful about spider mites than a changelog with a bow on it. But enough landed this summer to be worth one place to see it, and the failures are more interesting than the features.


One Photo, Several Plants

The API used to assume your photo held one plant. Shoot a whole tent and it averaged everything into one answer for the room, which is the wrong answer for every plant in it.

It now finds each plant separately and returns a results array – one entry per plant, each with its own bounding box, health call, growth stage and conditions. Three plants, two fine and one yellowing, gets you exactly that, and the box tells you which pot to walk to.

This was a breaking change: the per-plant fields moved off the top level into results[]. A single-plant photo returns an array of one, so it's the same code path either way. There's a longer write-up if you're wiring it up.


It Admits When It's Unsure

The change I'm happiest with, and the least flashy.

Some plant problems look nearly identical in a photograph. Calcium and magnesium deficiencies need different fixes, and there are images where nothing in the RGB data cleanly separates them. The honest move there isn't to pick one and sound confident.

So every condition and pest now carries a coarse_group – the clinical family it belongs to, one of six. The family is often right when the specific name is shaky, so you can alert on “something in the mobile nutrient family is happening” and stand on much firmer ground than “it's definitely magnesium.”

A secondary finding can also come back marked suspected: true. That flags something for your attention without claiming it. Show those to a human. Don't dose on them.

Both fields are additive, so nothing broke when they appeared.


Model Upgrades Are Visible Now

Responses carry an engine_version naming the build and model iteration that served your call.

That matters because the models behind a diagnosis were replaced over the summer, and they'll be replaced again. If you cache results or tune thresholds against particular behavior, watch that field and invalidate when it moves. It used to be that a model upgrade quietly changed things underneath you. Now you can branch on it.

The honest numbers haven't moved much and I won't inflate them: cannabis verification sits at 99.96% balanced accuracy, health screening at 98.4%, both on plants held out from training. Naming the exact condition is still harder than noticing something's wrong. That gap is why the hedging fields exist.


The Upload Bug That Took Three Tries

My favorite failure of the summer.

Uploads from phones started failing. Not all of them, not reproducibly, and never on my machine. The pattern turned out to be full-resolution photos over slow upstream connections – which describes a lot of growers and almost no developers.

The server was hanging up while the phone was still sending. I raised the read timeout from 30 seconds to 120 and shipped it. Reports kept coming. Raised it to 300 and shipped that. Reports kept coming.

There were three timeouts in that path, not one, and they were all different: the API's own, the reverse proxy in front of it, and the client's. Fixing one just moved the failure to whichever was now shortest. The connection died at the tightest link no matter what I did to the others. Aligned all three at 300 seconds and the reports stopped.

I shouldn't have needed this lesson twice: when a timeout fix doesn't work, the timeout you fixed isn't the one that fired. Find every layer that can hang up before you touch any of them.

The mobile app shipped with the aligned values in July.


Quieter Things

  • The API no longer dies at boot on a transient database hiccup. It used to try once and exit, so a DNS blip during a deploy could take the service down until someone noticed.
  • There's a partners page now for hardware and platform companies who want plant health inside their own products.
  • /usage returns your counts, limits and remaining quota, and doesn't itself consume quota.
  • I measured what ruins a diagnosis photo. Tight close-ups and overexposure hurt far more than blur or purple light, which is the opposite of what most people assume.
  • Infrastructure runs in Europe. That happened earlier in the year, and here's why.

What's Next

More work on naming the specific condition rather than the family, since that's the honest weak point and everything else is downstream of it. And better handling of the photos growers actually take, which are lit by purple LEDs at midnight rather than by a photographer.

Free tier is 3 diagnoses a day, no card. The full contract is at plantlab.ai/openapi.json, with a field-by-field walkthrough if you want it, plus guides for Home Assistant and Node-RED.

 
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from PlantLab.ai | Blog

A herbarium specimen sheet in antique botanical style - a pressed cannabis leaf drawn in fine engraved ink on the left, joined by a single ruled line to a naturalist's record card of neat abstract pen strokes on the right

What It Does

The PlantLab API takes one image of a cannabis plant and returns structured JSON describing what's wrong with it: one of 30 conditions and pests (or healthy), a growth stage, a confidence score on every call it makes, and a bounding box per plant when the photo has more than one. It answers in about 18 milliseconds. Auth is a single X-API-Key header, and the free tier is 3 diagnoses a day without a card.

If you already have a camera pointed at your tent, this is the piece that turns a JPEG into something your automation can branch on.

Most grow stacks are blind in the same place. Temperature, humidity, VPD, EC, runoff pH, substrate moisture at three depths – all of it describes the room, none of it describes the plant. So the loop still ends at a person squinting at a phone.

Every response below came out of the live engine.


One Call

curl -X POST https://api.plantlab.ai/diagnose \
  -H "X-API-Key: $PLANTLAB_API_KEY" \
  -F "image=@canopy.jpg"

Multipart upload, one required field.


What Comes Back

A real response, from a plant with powdery mildew on it:

{
  "request_id": "8919a46e-a704-4a4e-a700-b754188165b5",
  "schema_version": "3.1.0",
  "engine_version": { "api": "1.0.166", "models": "v6" },
  "success": true,
  "is_cannabis": true,
  "cannabis_confidence": 0.95,
  "results": [
    {
      "bbox": { "x0": 0, "y0": 0, "x1": 1, "y1": 1, "normalized": true },
      "is_healthy": false,
      "health_confidence": 0.1,
      "growth_stage": "vegetative",
      "growth_stage_confidence": 0.9,
      "conditions": [
        {
          "class_id": "powdery_mildew",
          "display_name": "Powdery Mildew",
          "confidence": 0.8,
          "coarse_group": "fungal_disease"
        },
        {
          "class_id": "potassium_deficiency",
          "display_name": "Potassium Deficiency",
          "confidence": 0.6,
          "suspected": true,
          "coarse_group": "mobile_nutrient"
        }
      ]
    }
  ]
}

It returned two things. The mildew is the call it's making. The potassium deficiency is marked suspected – something else worth a look, without claiming it.


The Fields

Field Level What it means
is_cannabis image Whether the photo is cannabis at all. Decided first, so it sits at the top
cannabis_confidence image Probability the image is cannabis
results[] image One entry per detected plant. A single-plant photo returns an array of one
bbox plant Where this plant is, in normalized 0-1 coordinates. Multiply by width and height to draw it
is_healthy plant The health call for this plant
health_confidence plant Probability the plant is healthy. Read the next section before using it
growth_stage plant seedling, vegetative, or flowering
conditions[] plant Diseases and deficiencies, most confident first
pests[] plant Pests, same shape
schema_version response Contract version, currently 3.1.0
engine_version response The build and model iteration that served this call

The field people get wrong

health_confidence is the probability the plant is healthy. It isn't confidence in the verdict you were just handed.

In the response above, is_healthy is false and health_confidence is 0.1. That's not a shaky answer – it's a very confident sick one, because a 10% chance of healthy is a 90% chance of not. Write if health_confidence < 0.5: flag_uncertain() and you'll fire uncertainty warnings on the clearest sick plants you own while staying quiet on the genuinely ambiguous ones.

When is_healthy is false, low health_confidence means more certain, not less.

suspected and coarse_group

suspected: true marks a secondary finding the engine wants to flag but isn't asserting. Show it to a human; don't dose on it.

coarse_group is the clinical family a condition belongs to – one of mobile_nutrient, immobile_newgrowth, water, light, fungal_disease, pest. Some problems genuinely look alike in a photograph, and the family is often right when the specific name is shaky. If you're deciding whether to alert rather than what to dose, group on this instead.

Also in the response

Three more fields show up when they apply.

mulders_hypotheses names nutrient excesses that would explain the deficiency you're looking at. A calcium excess locking out nitrogen looks exactly like a nitrogen shortage, and feeding more nitrogen makes it worse.

progression_risks says what this turns into if nothing changes.

stage_advisories adds context that depends on the plant's stage. Lower-leaf yellowing in late flower is usually normal, and it says so rather than letting you chase it.


The Rest of the Surface

Endpoint Method Purpose
/diagnose POST The one you came for
/usage GET Current counts, limits, remaining quota. Read-only, doesn't consume quota
/health GET Liveness. No key required
/info GET Metadata and capabilities
/history GET Past diagnoses, newest first. Pro tier and above, with data sharing enabled
/feedback POST Report a wrong result

/usage is the one integrators forget exists and then rebuild badly. Poll it instead of counting your own calls.

The full machine-readable contract is at plantlab.ai/openapi.json, so generate a client rather than hand-rolling one.


Limits and Errors

Free tier is 3 diagnoses a day. No card, no trial clock, and nothing to cancel – paid plans aren't live yet, so right now that's the whole offer. Higher-volume tiers exist in the API for granted accounts, and paid access is coming.

429 means you hit a limit. 408 means inference timed out. 400 on upload usually means the image failed a sanity check rather than a malformed request.


What It Doesn't Do

It's cannabis-specific. Point it at a tomato and is_cannabis comes back false, which is correct and not useful.

It reads a photograph, so it's bounded by what a photograph contains. Root-zone problems only appear once they reach the leaves, and two conditions that look identical in RGB are hard to separate in RGB. That's why suspected and coarse_group exist instead of a single confident label.

It's sensitive to how you shoot. Overexposure and tight close-ups reliably produce wrong answers – I measured what breaks a diagnosis, and the results aren't what most people guess.

It doesn't replace looking at your plants. It notices things earlier and more consistently than you will at 11pm, and it never gets bored.

On accuracy: cannabis verification runs at 99.96% balanced accuracy and health screening at 98.4%, both on plants held out from training. Naming the specific condition is a harder problem than deciding something is wrong, which is the honest reason those hedging fields are in the response at all.


Getting Started

Sign up at plantlab.ai, copy your key from the dashboard, and run the curl command at the top of this post against one of your own plants.

Prefer wires to code? There are guides for Home Assistant and Node-RED.

 
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from PlantLab.ai | Blog

An antique bellows plate camera on a tripod studying a cannabis specimen framed by hand-inked corner brackets, with two faded rejected alternatives in the corners: the plant lost in an oversized frame, and a single leaf overflowing a too-tight crop

How to Photograph a Cannabis Plant for Diagnosis

Frame the whole plant so it fills most of the shot, and use even light that isn't blown out. Don't zoom in on the damaged leaf, and don't shoot from across the tent. If your lights are blurple, that matters far less than whether the photo is overexposed.

The mistakes that cost you most aren't the ones people expect.

The One That Surprises Everyone

When a leaf looks wrong, your instinct is to get close and photograph the damage. It feels like helping.

It's the most reliable way to get a wrong answer.

I took four labeled images – powdery mildew, spider mites, a nitrogen deficiency and a calcium deficiency – cropped each one tight around the affected area, and ran them through. Not one survived. The mildew came back healthy. The spider mites came back as a nitrogen deficiency. The calcium deficiency came back as septoria. The nitrogen crop wasn't recognized as cannabis at all.

Diagnosis is comparative. Which leaves are affected, old growth or new. Whether the pattern is uniform or between the veins. How the rest of the plant looks by comparison. A close-up throws all of that away and leaves a patch of discolored green that could be six different things.

Photograph the plant. The damage is already in the photo.

But Don't Go Too Far Back

The opposite mistake fails just as reliably. Shot from across the tent, all four went wrong: two returned the wrong condition, one came back healthy, and one wasn't recognized as cannabis at all.

There's also a hard floor on size. Scaled to 256 pixels wide, three of four failed the cannabis check outright and returned nothing. Any modern phone clears this easily, so it only bites when something in your pipeline resizes before upload. If you're automating, send the original.

One plant, filling most of the frame.

Light Level Beats Light Color

Overexposure is the dangerous failure, because it doesn't look like one.

Brightened until the highlights clipped, two of the four sick plants came back healthy with reasonable confidence. Blown-out highlights wash out the exact color and texture differences a diagnosis rests on, and what's left looks like an untroubled plant. You get an all-clear on a plant that needs attention, and nothing in the response tells you to doubt it.

Underexposure is gentler. Two of the four darkened images kept the exact right answer; of the other two, one dropped out of the cannabis check and one named the wrong pest. Neither returned a false all-clear. Wrong, or refused outright, you can recover from. Confidently-healthy you can't.

Blurple light did less damage than expected – three of four still returned the correct condition under a heavy magenta cast. That's smaller than the effect of exposure. It still costs some confidence, so shoot during a lights-off window or use your flash when that's easy. When it isn't, shoot under the grow lights anyway and watch the confidence score.

I simulated that color cast digitally rather than photographing under real fixtures, so it's directional rather than settled.

Blur Is More Forgiving Than You Think

A heavy blur kept the correct diagnosis on half the test images. On the other half it produced a wrong answer, with confidence collapsing to 0.10 and 0.15.

That's the system working. When the image doesn't support a call, confidence drops instead of the answer quietly getting worse. Treat anything under about 0.3 as “take another photo,” not as a diagnosis.

The reverse doesn't hold. A high score is not a guarantee: one tight crop returned the wrong condition at 0.70. Low confidence reliably means don't trust it. High confidence doesn't reliably mean you can.

Still focus your shots. But given the choice between a slightly soft photo of the whole plant and a razor-sharp photo of one leaf, take the soft one.

The Checklist

Do Why
One plant, filling most of the frame Diagnosis is comparative – it needs the whole plant
Even light, no blown highlights Overexposure returns false healthy calls
Shoot lights-off, or use the flash Costs less confidence than shooting under blurple
Send the original file Aggressive downscaling breaks the cannabis check
Retake anything under 0.3 confidence Low confidence often means the photo, not the plant
Avoid What happens
Close-up of the damaged leaf Wrong answer or a false healthy, every time
Whole-tent wide shots Wrong answer, or not recognized as cannabis
Brightening a dark photo to “fix” it Turns a diagnosable photo into a healthy verdict

How I Tested

Four labeled images – powdery mildew, spider mites, nitrogen deficiency, calcium deficiency. Eight versions of each: original, darkened, brightened, blurred, color-cast, tightly cropped, shot-from-distance, downscaled. Thirty-two diagnoses. All four originals returned the correct condition untouched.

The variants were made digitally rather than by re-photographing under each condition. And four plants is four plants: enough to show a pattern that held every time, not enough to put a percentage on it. Hence directions rather than numbers.

If You're Automating

Same rules, plus two. Don't resize before upload. And branch on confidence instead of treating every response as equally solid – under 0.3 usually means trigger another capture, not raise an alert.

The Home Assistant and Node-RED guides cover the wiring, and the API walkthrough covers what comes back.

Try it on your own plants at plantlab.ai – three diagnoses a day, free, no card.

 
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from Jaran Flaath

– Det er viktig å skape nye historier, sa han. – Ikke bare leve på de gamle.

Det var kjøreskolelæreren min som skulle vise seg å bidra med den største innsikten jeg har blitt servert på en god stund. Han er 70 år, har kjørt motorsykkel lengre enn han kan huske, og har ingen planer om å gi seg før kroppen streiker. Det er hans måte å skape de historiene han vil leve. Det var dypt inspirerende der vi satt i salen og nøt svinger og landskap om hverandre.

Det er lett å bli hengende ved de gamle historiene, leve på dem hver dag. Man lar de definere en selv og ender ofte opp med å gjenfortelle gang på gang når man sitter rundt kaffekoppen med kamerater eller kollegaer.

Samtidig er det lett å tenke at alle nye historier må være store, må stadig overgå. At de må være grandiose og imponere. Det har ikke jeg tid eller mulighet til, kan man tenke.

Det er lett å tenke på livet som det som har skjedd, det man har opplevd. Men det er vel så mye det som gjenstår å oppleve. Historiene man ikke har skapt, som ligger der og venter. Ikke som en uoverkommelig bucket list, eller et jag etter å leve hver dag som den siste, men som en motivasjon og noe som kan skape glede og forventning. Noe å se frem mot heller enn å bare kikke i bakspeilet.

Det kan være vel så verdifullt med de må hverdagseventyrene som de store som bare skjer en gang i tiåret. Forsøke noen nye hobbyer. Gå nye stier i skogen – ta med middagen. Ta badstue med noen kamerater. Kjør motorsykkel. Spill frisbeegolf, eller vanlig golf. Eller begge deler. Lær deg å strikke. Hopp i fallskjerm.

Historier kan være så mangt og det viktige er å lage deg noen du kan leve, ikke bare fortelle de samme gamle om igjen.

 
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from Things Left Unsaid

Woke became an insult. What does it mean to be not woke? To oppose all the things that could bring humanity to a brighter future, like wisdom, common sense, empathy, acceptance, logic, education, science, etc.. Judge and hate people for the color of their skin, for who they fall in love with, for where they were born, or for no reason at all. Decide who should have and who should have not. Even when presented with solid evidence, deny that more of an iceberg exists beneath the surface than what can be seen. Life is all black or white with no in between. Don't listen to reason, and ignore any inclination to investigate anything. Cancel critical thinking. Don't care about how much suffering closed mindedness, greed and violence causes. Measure success by how much power and The Dollar Almighty a person has taken by manipulation, greed, or brute force. If you haven't achieved this (false) success for yourself, admire those who have, and elect them as leaders.

 
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from An Open Letter

I have been getting a lot more matches on, and there’s this one person that I was talking to a lot today she really matches my energy. I also thought she was funny And she matched my freak. She also mentioned that she has had therapy in the past, and she lives pretty close by which I’m excited for. We have our first date on Saturday. I’m nervous but excited.

 
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from AnOublietteofThought

He did not settle upon my heart with the coziness of a warm blanket. He clawed his way through terror and rejection, roaring in silent defiance until I granted audience. Until I opened my eyes to see what stood before me.

It is said, that when the leaves blush in longing dance, air and water will unite to set flame to ways long rotting. What they forgot to mention is that the earth must tremble, cracking until mountains rise to spew fire into the heavens. Forever igniting our best minds to blaze in remorse. The unyielding storm holds no syllables in that passage.

Storms do not yield. They flood. They rupture. They clean the slate and leave a debris field of memories for us to learn from. But we haven't learned. Neither have I. Neither has he. We just are. Two victims of a cunning value. Little more. Little less.

We are taught that we must never gaze into the eyes of our heroes. One does not ascend to such great depths by doing what they are told. I dared to peer into the travesty of his gaze, and in that monumental moment of a not-so-insignificant contact—

the world tilted.

© 2026 AnOublietteofThought. All rights reserved.

 
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from Out of Office

WTF.

Today started out with the reminder that it may be my dogs last day. I am still not ready.

It was not quite as productive and busy yesterday. I can’t tell if that is a good thing or not, because I felt as if I had to fully acknowledge how I am feeling, which resulted in a lot of crying.

I could not eat this morning, the best I could do was a cup of coffee, which I hate taking on an empty stomach. I think I doomscrolled for a bit/started packing in short bursts of energy. It was weird. The energy was weird. The weirdest of all was my dog acting and looking completely fine and normal. It is disheartening and charming at the same time. Does she even know that I am just waiting for her to be ready? However, I have to leave in just a couple of days so I can’t wait any longer. My heart feels physically broken – like my chest physically hurts.

I am pulling every single string so I can have her for just one extra day.

It is too much. Everything happening right now is just too much.

To top it all of, I had an ATM machine malfunction on me on my last errand. Now I have to go to the bank tomorrow and get it sorted out because my deposit did not go through :/

Thank you for your message. I am currently out of office with no set return date. I will get back to you when the time is right.

 
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from Out of Office

Well, today was kind of busy ~ kind of sad.

Started with a bang at an oil change appointment. It was kind of annoying (another expense while having no paycheck), but also productive because I finally started writing my speech for my brother’s wedding!

Went to urgent care (finally) for my cough/congestion… only to be told it may be really bad allergies and to just continue taking allergy medicine.

Then I went to pottery and got quite a bit of work done with the trimming and stamping of a couple of pieces. All before heading to therapy for an hour. It was helpful, but man was it a lot to unpack this time.

Ran home, finished some laundry, and saw the dogs before going to a workout class! Continued on by another short pottery session of glazing a few other pieces with my mom. Proceeded to meet up with my dad and dogs at the dog park for what I have to assume is the last time (?!)

And finally, came home for the day.

Thank you for your message. I am currently out of office with no set return date. I will get back to you when the time is right.

 
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from The disconnect blog

I enjoy alt-media news much more than I ever really enjoyed mainstream media news. But something so strange happened during the whole Covid-19 thing. So many people got shadow banned during that event who were just being inquisitive and trying to find out what was going on. Legitimate doctors who were having successful results in treating Covid in many ways were harassed and even lost their licenses. As I watched all of this happen many alt-media lost a lot of their viewers because of being shadow banned or banned on Youtube, Facebook, Twitter, and probably more that I’m forgetting. Then some of them built back up on either their own platforms or other platforms. Now after all the dust has settled many are going back to their corrupt masters at Google and posting on YouTube. They talk about how they were banned and how lame the company is for doing that but still use it and post on it and funnel traffic to that beastly company. Isn’t this pretty much the definition of “selling out?” And all of us who disliked that whole thing, aren’t we selling out by still using the platform who thwarted free speech? I had Covid twice (untested cause I don’t trust the PCR test as viral diagnostics, neither did the inventor Kary Mullis. See a snippet article on the topic here and an open forum interview with him here skip to 48:30 to 52:11 for the reference about PCR testing, but the whole thing is interesting) and it wasn’t all that bad by taking vitamin C and D with zinc. Some doctors were harassed for saying such a thing, and that is known to help your immune system fight against just about any virus. I later learned that nicotine can help with long lasting Covid symptoms (and here). I did have decreased smelling for quite a while and got used to it. But after I heard about that I used a few nicotine patches cut up into small strips and nicotine gum. That gave me back a lot of my smell! Why won’t the main outlets give us at least the basics. Go get fresh air and sunlight for vitamin D, boost your vitamin C intake and make sure you have some zinc. That alone can keep many viruses from taking hold, and when they do they often will not be too debilitating.

Personally I have tried to avoid YouTube for many years now. There are some rare occasions that I do but I use it through third party platforms that block ads and hide my identity. I use a VPN, FreeTube, and/or PipePipe. I’ll switch to other things if/when those stop working. There is a constant little battle going on with YouTube trying to block those services and then those services get patched and they start working again. If I’m going to go use that platform which I dislike I’m not going to support them by watching their ads and letting them profile me. I’d rather not watch the video if I cannot do it on my own terms.

One of the biggest reasons I still ever go to YouTube is for the DIY and tutorial type videos. There are some decent alternative platforms for news, politics, and rantings of sorts but there isn’t much out there in the DIY and tutorial world besides YouTube that I have found. I would love a simple video site or video blog site to come along focused on that theme. Keep the bulk of the nonsense videos, politics, and compilations of silly animal events out, there are already plenty of platforms for that. If I had the ability and a bit more care that might be a project I’d put effort into. A simple clean DIY and tutorial video platform with no ads, just passion driven sharing of ideas. I wouldn’t block free speech with people posting a DIY video on something while rambling about their political views, but if it was just about politics I’d rather they go to Bitchute or something. A donation option would be cool and other payment options for content creators, but no ads and no paywall. That would be awesome!

Doesn’t this Proverbs 26:11 verse sort of fit with the people running back to YouTube after being banned?

Like a dog that returns to his vomit is a fool who repeats his folly

Proverbs is great.

Resources:

Books:

mRNA Vaccine Toxicity – by Dr. Michael Palmer M.D.

The Indoctrinated Brain: How to Successfully Fend Off the Global Attack on Your Mental Freedom – by Michael Nehls

Lies My Government Told Me: And The Better Future Coming – by Robert Malone, MD, MS

Apps and websites:

BitChute and Old BitChute — YouTube alternative focused more on freedom of speech.

Odyssey — YouTube alternative focused more on freedom of speech.

PipePipe — YouTube interface for Android and GrapheneOS that blocks your identity and ads.

FreeTube — YouTube interface for Linux, Mac, and Windows that blocks your identity and ads.

 
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from The Practice

On Learning To Write

Current Reading: Adler and How To Read A Book have officially been shelved. Saint Michaels Lent has started and I'll be reading The Spiritual Combat by Lawrence Scupoli as part of my devotion. I won't come back to Adler right away. I want to move on to something else, but I'll keep it close by for reference.


I've noticed my reading decline as of late. Im trying to become a better writer and it's really taking up a lot of my time just focusing on that. And I know that reading helps you become a better writer. But trying to write as much as possible to really get a feel for it, to try and find my voice is hard.

I was doing a lot of research on how people write differently. A lot of people have an idea in their head, plan it out and then write it down in the most elegant way they can. Some people write very analytical, almost like a very precise scientific explanation of something. Some write in beautiful pros, leading you down a beautiful literary narrative to a deeper understanding.

I write different I think.

Usually when I start I have no idea where I'm going to end up. That's what the Current Reading sections is for. It's something concrete I can start with, get my mind and hands working, then a thought will usually come up, and I start writing towards it.

I noticed this a couple years ago. I struggled to keep a steady journaling habit. I would make it two or three days then completely fall off. No real reason, just that I didn't have anything to write about. I think it's because I had an idea of what I was supposed to be doing. I thought I had to have a complete, fully formed narrative in my head before I started writing. I mean, that's what I was taught in school. Figure out what you're going to write about, make an outline, construct the essay. And that's a completely valid way of writing, but just not what I was wanting to do.

I'm Catholic. And every first Friday of the month my parish has overnight adoration. You can sign up to make a Holy Hour during the overnight hours into Saturday morning. I started going at 3 o'clock AM, and I really wanted to keep an adoration journal. But the same thing started happening, I'd get there, pray, open the journal and...crickets. Nothing coming to mind. No mystical messages from Our Lord beamed straight into my head. No big inspiration of anything I just had to get out.

So I started doodling, just because the pen and paper were right there in front of me. And then to my surprise, just by the mechanics of my hand moving, something loosened up, and a thought would just pop into my head. Something I was dealing with at work, something one of my kids had asked me, some problem I had been struggling with, some family dynamic that was needing to be worked out. And my hand started moving, but making letters and words this time not just drawing. Not in some flashy “a-ha” moment. Just natural.

I've now developed a pretty robust journaling habit. I've learned that I need to externalize my thoughts onto the page, to see them, so I can really understand them. I have also started a bullet journal and I still doodle.

And I know this may seem trivial to some people, but it was monumental for me. People think “Why are you making mountains out of mole hills Stoney. Just write something down”. And yeah for some that might work. I needed a little more understanding first. For years I wanted to journal steadily but it always evaded me. I just had to figure out the thing in my head holding me back, the way I was conceptualizing writing, was what I was taught in school. But it had to make sense in my own head for it to finally click.

And that brings me to the next big step. Trying to learn to write for others to read. It's something I've been drawn to my whole life. I never had enough confidence to actually do it, and I kinda can't believe I'm doing it now. I'm practicing in public(TERRIFYING). These short essays aren't going to be heavily edited. They are, at their core, my learning process. If you're looking for a completely polished, 3,000 word, journalistic masterpiece you probably won't find that here. At least not at first. The goal is to practice getting better. And I hope, eventually, that I'll write things that people enjoy reading.

 
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