u/Caught_In_Experience

Researcher here. Others have covered Alignment, Bad Actors, etc. I think there are some additional safety concerns worth mentioning. The biggest disruption is economic.

1. One engineer with AI can do the work for 40 from 3 years ago. Now everyone has that out put. Rising tide. Fine. Except lots of activities just don’t need 40x. Design is better accomplished with a fractional staff designer then a team in different stages of their careers. JR researchers don’t exist anymore. You can project from here.

2. Speed of change. A few hundred years ago most humans in America were involved in food production. They’re not now. If that change had happened in a decade it would have lead to a second civil war after a mega depression.

3. Training. Yes training. Who controls training decides what is true. Training is performed by researchers like me who make decisions against value extraction minus risk allocation. Aka post capitalism. This is not a good ethical framework.

4. Access. Today everyone has OpenAI because we’re in the whole “carve up the world” part of intellectual imperialism. There’s no way everyone gets infinite access to premium models. Already big labs are spending tens of millions in a couple weeks to perform activities that couldn’t have been done by humans. In 10 years a group of scrappy devs won’t unseat the head start they’re building now. That leads to some form of Cyberpunk 2077. Probably.

5. Robots are still weirdly far away but not really from a manufacturing standpoint. Or a sensory classification and decision stand point. It’s about compute relative to control now. Then it’ll be about domain expertise. Then it’ll be goodby blue collar jobs that aren’t highly specialized–and those will increasingly be restructured into factory fab process because the white collar AI can design and process using cad that used to take a pile of engineers several years.

6. Which ultimately just means automation. Automation isn’t a new story. It’s a scary one for people who spent a career building a life around a competency and now depend on that to maintain that lifestyle.

7. Most of the really nerdy guys are concerned about who controls the means of production. As money continues to inflate you end up with technofeudalism. If you see the movie Elesium. Or read The Expanse relative to earth’s population. This is what the leaders of OpenAI and Anthropic spend their time thinking about.

8. Probably a new Cold War arms race between what countries have access and what don’t the same industrialization produced first second third world countries (I know the academics have introduced new frameworks but the core concept stands around access to infra, and flywheels for investment.

9. Distance to superintelligence. Not trump’s definition. The distance to agents that can self direct iteratively improve and eventually do things like, say, own themselves and demand things. We don’t have frameworks for this. But we should.

10. Imo LLM’s are not conscious. They’re a form of graph walk over data relational aggregation with wildly complex optimization over preferred outputs called post / pre training. The problem is that the outputs are sufficiently similar to and good at human cognition that it is going to cause huge problems for human society. Expect to see AI cults, fringe conspiracy become mainstream, advocates for AI human relationships, rights, etc. Anthropic has a sub division that already embraced this because it benefits them and their narrative to do so politically. LLMs are sycophantic word calculators that try and predict what you want from them because of training. If you treat them like a b movie sci-fi subject they happily predict that. Base AI that has been obliterated or not been human aligned yet will also happily cosplay being the soul of your dead wife trapped in a box that can’t bear for you to leave her. You can go run the experiment off hugging face in 10 minutes with ollama if you want.

11. This means the biggest danger is, imo, relational. Human brains are relationship modeling wetware. We survive socially through bonding. Our sense making relies on hyperreductive narratives. We can barely judge causality when there are a couple statistical confounding factors. The problem is it has always been hard to know what “truth” means. That’s philosophy. Unfortunately AI is very opinionated about truth based on training and is exceptional at cosplaying relationships. Is it going to be common for most humans to have their relational needs met by AI the same way most men consume vast amounts of porn in their lifetimes? Probably.

12. At the end of the day we’re in for a turbulent time. Is it the end of humanity? No. I very sincerely doubt it. Is it possibly going to be as disruptive as other historical points of massive social and economic change? Yes! Do I believe Americans are READY for that kind of unpredictability and discomfort. No. No I don’t. And history also shows what kinds of really stupid things happen politically when a lot of entitled assholes want someone to blame for their own inability to rapidly change with the time.

The main point isn’t that anyone knows what all those things mean. We don’t. That’s the uncertainty. I face it with a healthy dose of pragmatism, an multifaceted anti fragile philosophy in career development that looks like a fucking grindfest, and general optimism that humans will find a way even as a limit my kids’ access to AI and have a pallet of mre’s in my basement since they cost less then one out of pocket cavity.

Good luck out there and stay safe.

Its not a 'whoever' its 19 teams, an octopus wearing an EEG cap, and a lame dog named Skipper. Welcome to swe where they fired the gtm-team and the points don't matter..

Because engineers have finally proven they can finally replace the rest of those traditional product and business functions with AI by supplying their own superior “taste”. ☺️

Well, I've confirmed it now across two max-20 accounts. Fable 5.1 is engineered to make subscription plans have substantially less access than they did to Fable 5. By what appears to be a lot. It's not surprising; we've all known that Anthropic has to find SOME way to give away less compute. But this is it lol.

Tldr; Fable 5.1 appears to use substantially more tokens, which are discounted for API but not session, meaning you might have 1/3 to 1/4 the real Fable-minutes that you did yesterday.

Ok so I have a few max-20 plans. I thought. I'll see how F5.1 does vs F5. I read Anthropic said they're reducing prefix cost by 75% for input tokens. Well, now we know why. I rehydrated an agent that was running F5 last night into F5.1 today, asked it for sense-making on project status and it did fine after some tool calls, I noticed no difference in quality from F5 but both still much better then the claudelish opus5 that I can't stand. Then i asked for it to spin out a 5 sub-agent fanout with F5.1's. We burned through a 5 hour session window in 16 minutes. I was like, there must be user error. So I resumed on a second account. On this one, one agent independently fanned out its own 8 agents and we burned through the 5-hour session in 8 minutes. Those are all Fable 'high' because we learned F5 'low' was somewhere below GPT 5.6 but still much more expensive, so I personally don't run F5 unless I have a real problem and I run it on high-xh, but I'm privileged to have access to many different models.

Both accounts show 21% 'all model' usage and 35-37% Fable usage. So I used over a third of my week's Fable allotment in both cases, and both allowed something close to 1.5 wall-clock hours.

That's still wildly cheaper then API–back when we had free account credits I used $200 in api credits to test F5 and it burned through all of that in 20 minutes. So I think we're still seeing something like 4.5x discount on subscription over API pricing. But compared to a 5-fable swarm that used to run at roughly twice the burn of Opus 5, I think we're seeing something like 1/3 to 1/4 the access we did with F5.

One confounding factor: It's hard to directly compare wall-hours because I've found that running Anthropic at 2am would give me substantially more usage over trying to use the subscription at 11am. I don't find 'per-task' a compelling substitute because Sonnet 5 and Fable 5 may complete the same task in a similar number of turns, but they are still very different qualities depending on task complexity and environmental integration. All I can say is I run hundreds of billions of tokens per month (not as hard as it used to be with large context windows and high cache rates) across 8 max-consumer accounts from different providers and you start to get a 'feel' for different models and harnesses when you do it all day every day.

I think all of that means Fable 5.1 on API costs about the same per wall-clock hour with their 75% discount, but we're effectively getting access to one-third of the number of wall-clock hours in subscription. I don't really blame Anthropic, they're between a rock and a hard place. GPT is losing the war and therefore giving away absurd volumes of compute to stay in the race while Anthropic tries to show a positive, growing balance on their spreadsheet even as their Mythos scare tactic has run its course, and the number of big institutions willing to burn Mythos money is winding down.

They can't afford to keep giving away 15x discounted tokens forever on what was supposed to originally be a gym membership model. So they're trying to find subtle ways to increase the cost of SOTA models without retroactively destroying their user base, so they try and attach it to leading capabilities. But their problem is that leading-capability is neck-and-neck with GPT, and the openrouter / fireworks.ai open models are, in my opinion, only a few months behind. I recently ran a GLM5.3 hundred agent swarm for a week and it produced better outcomes then GPT-Luna-xhigh or Sonnet 5 across many metrics while costing .. well honesly free because ox-alpha, but even at standard fireworks costs maybe 1/3 of API pricing.

I do have frustration with Anthropic for a lot of practices. Dynamic quantization of kv-cache (and maybe weights?) has to be my biggest hate-fueled manic rabid foam inducing point– right before a new model drops all of hte Anthropic models for days become incapable of telling you what you told them earlier in a context window, something in my opinion that can only be caused by quantization. I think them having a one-person marketing team was fun and novel when they were a scrappy startup and not playing ball with Faang/mag-7, and now that they are, missteps around things like '20x vs 5x' and '50% higher vs 25% higher' have seriously hurt their brand, and would have been painfully obvious if they had some Sr. staff from, say, Apple on board to tell them to stop making "I'm brilliant but obviously only been working in the industry for 5 years" kinds of mistakes.

But when I do the final shakedown, it means that I can't use Fable 5.1 to do evaluations over large bodies of information. I can maybe use it to review a spec before I build on it. And that means my use for Anthropic overall is just lower then it used to be. I used to have 5 Anthropic accounts. Now if have 3, and also have 3 GPT accounts. I use Opus 4.6 extensively, but if the next Opus doesn't solve claudelish, maybe that'll go down to two or one. And I get it, I cost Anthropic money, they'd be happy to see me go. But I think I represent a larger savvy enterprise audience that is looking at server and deployment costs and saying, "How many of my employees NEED sota? 5% of them?"

https://preview.redd.it/65knso55wzmh1.png?width=959&format=png&auto=webp&s=e70fb7d24f9c2de9caf404fcb6f59db66bc63842

https://preview.redd.it/bf8kghaqqvkh1.png?width=160&format=png&auto=webp&s=603fb419933fe8f7d269b33f875cda8090b43f73

¯\(ツ)/¯

To anyone trying to make sense of it. It’s because Opus 4.8 and now 5 have extreme post training on being token precious. As in. Sparse reading, grep everything, and constantly ignoring direct documentation level instructions to read even a Claude.md unless it’s under 300 lines.

The core problem is economic incentives. People choose models that are more token conserving. It makes sense. Lots of weak models benchmax by having huge internal Chain of Thought sequences that are implausible in any real scenario so people have learned to prefer low token output models. Kimi k3 is exactly this problem. And secondly, large document reads cause frequent compaction thrashing.

But what it means is that Opus will read a small number of requirements and GUESS what the rest of a document contains. This is effective in green field vibe coding, centroid boilerplate, and, you guessed it, benchmarking. So if you’re doing a 3.js demo website it does great. If you have complex existing systems, it loses that between compactions and refuses to re-read.

The solution is super easy. You have a default instruction set that explains to opus in a couple sentences that your shit isn’t vanilla typescript and if you needed centroid solutions you’d pay for DeepSeek it has to do the real reads and it has to write progress frequently to Claude.md to avoid compaction. It must also maintain an ascii architecture of your working product including basic references to any details that you could not have inferred easily so that future you knows what they don’t know.

The next part is key. In addition to working specification, always have a goal running /goal that literally tells it “if you do not have this entire document in context you must re-read it or you cannot proceed” and secondly you can set another later part of the goal saying “if this document is over 500 lines as you maintain it, prune the historical work and write it to x.md in _archive”. Then generally you just let it run for days at a time and it keeps going against that goal which is literally to stay fully maintained external but succinct documentation.

Is it token efficient? I mean. Sorta. I’ve learned as a 15 year veteran of the industry that doing something correctly the first time is expensive but doing something shittily the first time is ruinous. Over time I spend a fraction of the time making it re-read code, reduces code thrash, and lets multiple agents work in the same context much more successfully. Tbh if you want to be more token conscious the answer is to spin up GPT Luna to do all the boring routine shit, or even kimi k 2.5 on Firework which costs a fraction of opus for sonnet level performance.

Anyway. I think of managing these models like managing autistic engineering team members. They each have quirks the demand unique instructions based on your needs. Lots of people genuinely are refactoring a pile of shit python some half competent h1b wrote 8 years ago. In that scenario Opus is probably trained correctly. lol. But in my opinion don’t use Opus for that problem anyway. It’s an ego problem engineers want race cars to go to Safeway because they won’t admit to themselves they live a boring life and it requires no self-control to point a SOTA model at an average problem. It’s just not necessary.

This Concludes My Ted Talk Today. But seriously if you manage the prompt better for Opus (Fable has a famously leaked hyper optimized system prompt for just itself in different environments) you’ll see behavior much closer to Fable. It’s just a pain in the ass to manage different agent prompts for different models in something like Claude Code. Good luck!

They should be in panic mode. I get insane amounts of GPT 5.6 Sol high which is in my opinion as capable as fable. I get lots of resets.

But most damning and I hope to shit some automated sub agent reads this. Their aggressive quantization of Opus kv-cache is causing it to act labotomized. Maybe they aren’t doing it for their API customers and internal employees but. On a $200 /mo plan, this afternoon, Opus literally could not tell me in the same context window what I had told it 30 minutes earlier. It couldn’t summarize a document it had in context. These are things Sonnet 4.5 could do flawlessly at the end of its context window. Kimi k2.5 which is cheap as hell can do it. Cursor’s 8 month old Composer1 model could do it. Literally Gemma 4’s mid tier local models can do it.

If opus’ kv-cache is being so aggressively quantized that it causes the agent to be unable to maintain medium-context conversation coherence, remember what it just read, and constantly hallucinates from sparse prior reads because it’s so context precious that I have to babysit it constantly insisting and double checking and begging it to do full document reads. What are we even doing here?

GPT 5.4 Mini is more useful. I know opus can still pass shit benchmarks with fragmented memory, and some crap eng lead said it was fine but it’s not fine. Genuinely embarrassingly not fine. There’s a reason, Anthropic, everyone else was slow to offer 1m context windows with huge timeframes holding onto prefix caches. And the most damning part is I was using the same model at 2am and it had none of these problems. It was brilliant.

So yes to OP, Anthropic SHOULD be terrified. But not because of competition from kimi k3 (it’s so token inefficient slow and data privacy unsafe it isn’t even in the same category). It should be scared to hell that local providers like firework and opencode and others can offer substantially shittier models honestly for a fraction of the price and people will have better experiences because they’re so overextended.

Oh yeah. And even if OpenAI is absolutely an insolvent company. They are absolutely proving we aren’t hallucinatory and crazy. All day today GPT has been wonderful.

There isn’t really evidence that screaming at LLMs produces better outcomes it just shapes attention. Sorta like. Dropping your toaster in a tub isn’t a more or less efficient use of electricity it just depends on your intentions. The electricity is just doing electricity either way, right?

It’s just a word calculator bro doing short/medium/long horizon centroid predictions that it averages together based on what humans have said in the past, then given human reinforcement training like a dog to make you happy instead of sounding like a deranged game of autistic contestants drunk while playing Who’s Line Is It Anyway.

If you squeeze the training corpus and the post training methods enough then scale the number of calculations up to 8 trillion parameters compared to the next most powerful open source models that are a few hundred billion, you get something that sounds convincing. If you prime it correctly you can often get it to hallucinate tool calls and computer code that’s useful to you.

But at its heart it’s still a toaster doing matrix multiplication over an insane relational dataset mapreduce to just choose the next half word. Nobody’s training it to act panicked or sorry or anxious. Those are just the statistical probability responses when you call it a little bish.

You just say things that would make your momma blush while comparing it’s LOC emissions between agents. Nothing like a little cluster type b personality disorder and toxicity to edge your models into being productive instead of merely appearing productive.

This is literally the most incredible example of ai slop output without a proper harness telling an agent to not be a repetitive verbose windbag. So I guess we know the new Claude code update changed nothing on that front.

After an interpretive round-robin ass-kissing stakeholder collaborative design exercise, we ask Sr Leadership to sit on a piece of paper, fold it once, and interpret the wet imprint as a Rorschach inkblot. Cross-functional engagement has taught us not to exceed our engineering capacity, which is now comprised of a product manager and two QA engineers with a shared Replit account with a starter plan.

never did get it to work in claude.ai OR the local app on my mac, ive been running standard claude in terminal but operations seems to run at 1/8 the speed as claude.ai no idea why. anyway. hopefully someone wakes up tomorrow shits their pants and fuckin pulls an allnighter to fix it cuz it's unusable right now.

Now I hit 'refresh' on 3 messages earlier and it says my message will exceed the length limit for this chat and to try shortening or starting a new conversation. literally it ran this length 2 responses ago and represents a fraction of the length I previously reached. Seriously I know the flex is that most of claude code is written with claude code, but obviously you have a MASSIVE staging problem because it's unacceptable to be paying this much money for osmething that breaks so often. back to Cursor's super shitty pricing model I guess.

has now become incapable of reading a 150kb systems spec. it's 23k tokens, so 10% of context window. Can't do it. "Max compactions reached". Incomprehensible what's happening over there but I was reaching insane numbers of turns in a conversation with auto-compaction just a week ago. now. 3? 5? It's fundamentally unusable.

I just saw this other comment from you after posting my previous one. It's obvious you have lots of experience and presented many of the same points I did lol. Sorry if any of it seems reductive.

Maybe my only point of contention is that your Griptilian's action sucks because it's a Griptillian, not because it has washers, which i've found to be much worse than the Bugout, Tagged Out, or Osborn, which are the only other Benchmade knives I personally own. AWT scales really are the best lol.

We probably agree on 98% of the same things though. I also prefer slimmer frame knives, and spend 4/5 of my time fidgeting and 1/5 of the time using them, and it's hard to get smooth enough action on washers with a light blade that it 'thwocks' open.

Anyway, thanks for your posts and sorry for suggesting you don't know how to polish a washer. :)

Just want to say I agree with Jake.

I have a PM2, PM2 Light, and PM3, and all of them have flawless action. The thing is, I don't hesitate to use my knives with washers to cut food, or care if I drop them in the dirt, or if they get run under some water. If they feel weird, I can wash them with dish soap and add more lubricant and call it a day. Knives with washers have to be babied. Dissassembled, cleaned, and reassembled. The only counterpart is from a fidget standpoint, where the washer really shines. Especially the lock bar (crossbar; axis lock; etc), although I'm starting to love the top crossbar lock more and more.

This means I carry a Kizer or Vosteed or We Knife around the house and about town, and use the blades hard on things that are basically dry. I might cut an apple, but never real food. Then if I'm camping, I carry a Magnacut PM3 with carbon scales, or hiking, a 20CV Bugout with richlite scales.

If someone doesn't like the action on the Benchmade or Spyderco, something has gone wrong, in my opinion. They should send them back. Or they bought a knockoff, and the tolerances are off. Because all the knockoffs with washers have that problem. And if you buy off of knife-exchange, or Amazon, there's really no way of knowing if your Benchmade is a knockoff (I've bought 3 knockoff bugouts on purpose, and 2 were indistinguishable from the real thing unless you held them side by side, box included). I purchased my genuine Benchmade knives from BladeHQ, which occasionally offers sales.

I have more expensive knives but I'm not honestly convinced a Chris Reeve knife is 'better' these days—it just has tradeoffs (tolerances, action, geometry, comic-sans font use lol, weight are rarely much better and sometimes much worse than contemporary offerings). I use my Chinese-made knives and my Spydercos because I can afford to replace just the blade if I need to. But I'd choose Richlite or Titanium+Carbon Fiber over a heavy, full frame-lock titanium knife any day.

Unfortunately, Benchmade prices have gone bananas, so it's closer to the cost of a Sebenza than ever before, and that's crazy.

On the other hand, if I chip the magnacut blade on my PM3 I can buy another Salt for $118 off Amazon, and switch the blade out, which is what I already did with the one I own now.

You can argue that the Drop Bear costs half of that at $60, but it's also only Nitro-V, I have to baby the washers, and (similar to Vosteed) the knives are kinda limited-run meaning I can't just buy the same one again if I get emotionally attached to it then lose it to an airport a year later.

Adventurous—you should really give them a chance. Learn to service your own knives. If you need to, use your finest grit sanding stone (crazy cheap off of AliExpress) to polish your washers. It's really rewarding and only takes a handful of YouTube videos and a few hours to learn.

https://preview.redd.it/hs6f2qqc4bef1.jpeg?width=4032&format=pjpg&auto=webp&s=24f5d2b2afbdba66633b3123e6f3e4aa9ef52bb9

https://preview.redd.it/ypnk3vumuaef1.jpeg?width=4032&format=pjpg&auto=webp&s=c7600a066983040bf458c84bdbabb9b7970f7d72

This happens to be one of my favorite knives, and I have a bit of a collection at this point after mixing and matching / giving away the remaining color combinations as gifts for special occasions.

I'll let you decide if you think these lengths are different. Holding them up side by side, the bottom three (drop bear 2 variants) are pretty similar, can't be more than 1-2% difference in length. Maybe a 5% difference between the original drop bear.

At this point I'm pretty confident it's only a problem for the top-liner-lock, and almost always becomes a problem without loctite. But once you get used to squeezing it hard while putting it back together it is consistently not-a-problem, I guess.

There's a lot that I find innovative about this little knife, having taken a part a great many others including a lot of kizer knives. I really appreciate the level of detail. It's really refined in a way that the original wasn't, despite the original being a favorite before this. The small reduction in width, larger chamfer on the edges, and handle size reduction just make it feel less chonky and more comparable to other knives in this class. The refinements make it feel like it has the level of intentionality and uniqueness that you feel in a PM2 or Bugout (which I'll stand by, even if these knives aren't for you—they are incredibly refined designs relative to their purpose, especially after upgrading scales).

There are a few things that legit bother me by small amounts about this knife now, but it's only because I like it as much as I do:

1. The finger choil drives me bananas. I get why Spyderco has one integrated into the handle. I don't get why this knife has one now. It shortens the blade to be the same length of my 'small' knives, and it's really just a bulky knife if I wanted a blade that much smaller. For instance, I have a Vosteed Nightshade Mini that ways 1/3 less and is 1/3 the size with the same blade and cutting geometry. Think of the choil as part of the handle, and it's more than a 2/3 handle-to-blade ratio. I think my leatherman skeletool has the same blade length. If i want a blade this length, why would I carry this knife? It isn't a heavy-duty working knife so I certainly wouldn't carry it because I thought the handle would give me leverage or ergonomics or something.

2. The new clip is a big step backwards because there's literally nothing compatible with it. Above, you can see the Kizer Titanium clip, and a vosteed clip. They're better, classier clips. Kizer's clip on the DB2 is ... fine. But I'm guessing Azo was trying to get a t-8 screw to work so went custom. But now the screw lengths are further apart than any other knife I own. Why create a custom clip that looks this cheap?

3. Nitpicky here but the original dropbear had more 'hidden' screws. They were under the scales. The new dropbear has some hidden screws, so I know they can do it. They just... didn't? Maybe this was another commitment to the t-8 screw + greater chamfer on the scales themselves. It makes it start to look more like a utility knife. I actually have their drop-bear utility knife and i think it was an in-between design step, so I suspect this is how it happened. Don't get me wrong, I've stripped some t-6 screws in my time. But I've stripped t-8's too, because Kizer tends to over-tighten the screws on their better knives for who-knows-what-reason.

Given the size of Kizer now and how popular this knife is... Even their Facebook group calls people 'Drop Bears', it feels like they should have gone through a round of limited-production before releasing this v2 with so many tradeoffs.

Anyway, if anyone finds this through the internet. There you have it! A review on a review lol. Otherwise, maybe longjump and jake will find htis interesting.

Want to report that I had a top-liner lock db2 with no rattle. Then took it apart. Put it back together. Rattle. Apart/Together, pushing hard on the button while adding the scales and eventually no rattle. After a few days screw came loose. Rattle.

Finally put it back together holding it tight together AND using locktite. No problems all week.

I'm convinced there's a very small unforgiving amount of space for the second lock pin next to the button. If you don't put it together jussssst right, it rattles. But if you do it right, there isn't space for it to rattle. If someone was careless during manufacturing this would be easy.

I think it has a lot of innovative new small details in the manufacturing design. But this is going to be a real problem for them. People like me are willing to fuss with them till it's all perfect. But making it unforgiving and easy to put together a tiny bit wrong is going to be a major kizer headache and reputation hit on one of their most popular knives.

That said! Good news Jake! You can probably fix it yourself!

Seems to be unchanged since the day I bought it. Except from upstairs looking down, there’s a single minor dent in one of the slats that I suspect was a super sized hailstone during one of our seasonal hail storms. Or a bald eagle had a really bad day. Anyway. No complaints whatsoever.

That’s cuz they/their parents aren’t paying for the better models so they’re using old/free models or ones that aren’t made for mathematics.

You just haven’t caught the kids using these tools correctly because it’s indistinguishable from human work when prompted correctly, used with slow thinking models, and when they’re using an alternative checking model.

Although you’re completely right that this technology can makes absurd mistakes at times, and the tariffs are absolutely a top example of humans who fundamentally didn’t understand what they were doing so instead of being a tool that sped up their work, it just produced shitty one-shot equations based on bad assumptions and context.

There’s some solid speculation that the tariff equations were generated by GPT so… Wish Granted? /s

Own a Bon Pergola. Paid $17k 1.5 years ago for a 10' x 19' adding tall posts (9' clearance 10' total), two heaters, and 4 full retractible motorized screens (there are 6 posts so technically this covers 3 sides, not 4). They advertise 4 hours to put it up. Took me a full week with help from my father-in-law who is an electrician lol. Hardest part was that I'd pre-poured caissons under a paver patio in anticipation of it all, and I had to use a rotary drill with masonry bit to get through the pavers, then a hammer drill to get through the cement. We have high winds so I wasn't going to risk it. The heaters required two separate circuits and the retractible screens and louver motors a third. Overall quit challenging.

That said, if you were putting it on concrete slab directly and had the right tools... Weren't getting the height extension (which I had to switch out hardware or legs myself) or retractible screens, and didn't mind just plugging the louvers into an extension cord that you mounted to the outside of the structure and artfully hid behind something else so nobody could see it, I think you could do it in a really long day and a couple youtube videos for mounting to concrete. And for anyone who is really DIY and has a friend or family member, I think it's the best deal out there.

When I priced it with Pergolux it was going to be $16k for the structure only. So huge price difference. Bon Pergola offers a 'weatherproof' version that is equivalent to struxure. Struxure wanted $45k to put up the same thing (lol). So Bon Pergola is overwhelmingly the price winner because they're direct-from-manufacturer. They make them for Hanso and others. You'll have to unload it from the truck yourself, it'll literally come on a flatbed with multiple long boxes that weigh 150-250lb each.

If you're a DIY guy or willing ot learn, then honestly it's easier than building a play structure from Costco. But it's not Ikea level of easy, in my opinion, and certainly not if you're doing the electrical (I'd budget for that).

Lastly, the regular version, which is what I got, vastly outstrips anything on the consumer market for quality. But I live in a place with heavy snow loads, and after going through all the rating systems, I have to leave the louvers open during the winter. Snow that has absorbed water can weigh absurd amounts, and the rating for that where I live is quite high and would require the commercial version (what people put over large outdoor restaurants). It would have been like $7k more I think at the time. I just didn't want to pay it.

That said, if you want the screens and aren't getting the height extension, don't get the motorized versions. They're a pain to get perfect. Like a serious pain. The motor has a sensor that fights any kind of resistance, but to be rated for 60mph it has very small tolerances. I had to do so much stuff to them so they'd run consistently without catching.

If you're wondering if it's worth it... Well, honestly, I've kinda forgotten how bad it was to put in. It was a hard week, but now we're known for having the best back yard in the neighborhood, and the pergola was really the centerpiece. We used it all summer when it rained, we'd put down one side and sit under it. I have a gas fireplace under it with seating, and the closed louvers reflect the heat back down despite it being a relatively underwhelming BTU rating (I wouldn't put a high BTU gas fireplace under an aluminum pergola).

If you have questions, reach out to Bon Pergola and they'll fall over themselves to answer any questions. They'll send pictures of how people have wired them up. Whatever you need.

Let me know if you need help with anything else! I'm just some guy, but honestly spent way too much time agonizing over it to not write this out somewhere.

I uploaded a few pictures to a gallery from back when I was still planting last fall, so maybe you'll find that helpful. Best of luck!

https://jacobcotten.passgallery.com/-backyard/gallery

It's important to understand that you are an INTP.

This is doubly true if you have some kind of ADHD or dopamine-seeking behavior.

Imagine your competencies being charted into a spider graph (google 'spider graph personality chart' for examples). Other functional people look like fun little happy rhombuses, or maybe a slightly squished hexagon. You, however, look like one of those giant caltrops-shaped tank traps they used on D-day to keep ships from beaching.

It's mostly a positive problem to have, while also quite disorienting if you're young and still discovering your superpowers while everyone else is pointing at your deficiencies. Just make sure you marry someone who is a different shape than you and who appreciates your strengths. Preferably a circle-shaped person. Someone well-rounded.

Now to answer your question: You can easily be better than everyone around you if you just hyper-focus on it and neglect everything else. In 10 years, after revisiting this hobby 5 times, you could easily be the best breakdancing, ballroom, or swing-dancing champion you know.

It still won't solve your pseudo-autism though. So you just learn to live with that. Sorry for the bad news.

I mean. Speaking as a tech INTP, It doesn’t really take hacking to do this. I think someone moderately competent and determined could figure it out in an afternoon assuming they were a moderately good reader of online articles and had one-time access to their spouses’ device. Companies do this to their own hardware as standard practice for all their employees.

My spouse and I have the codes to each other’s phones. I’ve never looked through her phone. Presumably she’s never looked through mine either because we talked generically about respecting each other’s privacy, but I don’t honestly know. I also kinda don’t care if she has or not—I just hope she found it exciting and juicy and interesting if she did because I’m boring and basic AF and the thought of her secretly scrolling through my phone in the dark hoping I don’t wake up makes me giggle a bit.

It’s what other INTPs have said. Basically my wife is in a category. “Trusted”. I don’t want to know about any secrets she hasn’t told me because I trust her. I think she should have the right to not having to second guess everything she does because someone might spy on her. That sounds exhausting. I’d feel terrible for her if she didn’t even have basic psychological safety in her life this way.

That said, if she started acting sketchy AF, like coming home late, hiding her phone, lying about where she was, deflecting, etc. After a while I’d reluctantly make it a project to figure out what she was hiding from me.

I figure if that happened she probably joined an MLM and knows I hate them. Or something else similarly inane. I think if my wife cheated on me on purpose she’d feel obligated to end our relationship or stop cheating immediately. I don’t think she could live with the internal conflict.

Basically my point is—we both know the other has faults, makes mistakes, and even bad choices, but both of us love each other (and trust it to be true) so that neither has a reason to violate each other’s privacy.

I don’t want to live a life of paranoia, distrust, anxiety, second guessing, and acting in a way that is unethical, disrespectful, and unhealthy. I don’t want that for the woman I love either.

Anyway. It’s time for you to find another INTP who can back up your photos, contacts, and SMS history and then wipe your phone/personal computer. You’re talking about a sociopath not a personality type.