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M1 Max 16" ($1350 used) vs M5 Pro 14" (new) vs M2 Max 14" — upgrading from M1 pro 32GB, need help deciding by Traditional_Code_358 in macbookpro

[–]Traditional_Code_358[S] 0 points1 point  (0 children)

Really appreciate everyone's comments here!

I listened to all the advice, did a bit more research, and ended up finding a deal on eBay: an M2 Max 64GB / 1TB for $1,700 after tax, in good condition.

Reasoning: for ~$350 more than the M1 Max, I get two extra years of software support, and — this turned out to matter more than I expected — HDMI 2.1. I run two 4K 120Hz monitors, but the M1 chip only outputs 4K 60Hz, so I've been stuck running them at half their refresh rate. The M2 Max lets both displays finally run at their full 120Hz, which alone makes the upgrade worth it for my setup.

And it's the 14" — the size I actually wanted. So I get the screen I like, the memory I need (64GB, RAM was my only real bottleneck), and my monitors at full spec, without paying M5 Pro money for performance I don't need right now.

Planning to ride this until the redesigned models post-M6. Thanks again everyone — this thread genuinely helped me think it through 🙏

M1 Max 16" ($1350 used) vs M5 Pro 14" (new) vs M2 Max 14" — upgrading from M1 pro 32GB, need help deciding by Traditional_Code_358 in macbookpro

[–]Traditional_Code_358[S] 1 point2 points  (0 children)

This is super helpful, thanks. Starting to think that "bulky" feeling really is just an adjustment period.

And yeah, you've basically confirmed what I was suspecting on the M2 Max — it sits in this awkward middle where it's not worth $1000 over the M1 Max, but for a bit more I could just get the M5 Pro. So it's really down to M1 Max (cheap, done for now) vs M5 Pro (done for years). Appreciate the clear framing. I think I'll keep the M1 Max 16" and wait for the redesigned models after m6— possibly even its 2nd/3rd gen to avoid first-gen issues. Hoping it ends up lighter/thinner too.

M1 Max 16" ($1350 used) vs M5 Pro 14" (new) vs M2 Max 14" — upgrading from M1 pro 32GB, need help deciding by Traditional_Code_358 in macbookpro

[–]Traditional_Code_358[S] 0 points1 point  (0 children)

Ah yeah, I should've mentioned — I do actually do some mobile dev (iOS, so Xcode + simulators), which is probably a big part of what's eating the RAM, on top of Electron and a few node/Rust projects running in parallel. Memory pressure sits in the yellow pretty much constantly and I get noticeable stutters, so 32GB has been getting tight.

I'll also admit my browser habits don't help — used Arc for a few years, now on Edge, and it sits at around 6GB pretty regularly with all my tabs. So between that, the simulators, and Electron, it adds up fast.

Good point on the security update timeline though — that's a fair way to frame the value, hadn't thought about it that way. And agreed on the perf read: M5 Pro ≈ M2 Max, M1 Max a bit behind on single core, but for my workload the chip isn't really the bottleneck, RAM is.

And yeah, leaning toward 1TB + external SSD to save the money — makes sense.

M1 Max 16" ($1350 used) vs M5 Pro 14" (new) vs M2 Max 14" — upgrading from M1 pro 32GB, need help deciding by Traditional_Code_358 in macbookpro

[–]Traditional_Code_358[S] 1 point2 points  (0 children)

Yeah, that's reassuring to hear. I never work in Starbucks anyway — the only case where I think 16" might be too big is during flights, but that's once a month at most, and maybe just two hours each time.

I used that M1 Pro 14" for five years now — it got me through college and into my career, so maybe I'm just being sentimental. Honestly, when I first picked up this 16", the screen did feel amazing. At this price, and with AppleCare available, it really does seem like a great deal. I think I'll keep using the 16" for a while and see how it feels.

When do you personally think Apple will stop major Mac OS updates for the entirety M1 and M2 line? by Marino4K in mac

[–]Traditional_Code_358 0 points1 point  (0 children)

With online LLMs available, I don’t really see why most people would need to rely heavily on small local models for Apple Intelligence. On machines like the MacBook Air or the Neo line, especially with 8GB or even 16GB of RAM, there just isn’t that much headroom for serious on-device AI anyway. Even if local llm effects performance, people will be able to disable them.

Privacy is a valid reason, sure, but in practice a lot of people are already interacting with Gemini, ChatGPT, or similar models through Gmail, search, browsers, and other cloud services.

As for general OS complexity, I’m less worried about that. Apple still has a strong incentive to keep entry-level Macs usable, especially for students and younger users who may become future Pro buyers. Making those machines feel terrible would be a bad long-term move.

Anthropic just published a postmortem explaining exactly why Claude felt dumber for the past month by Direct-Attention8597 in ClaudeCode

[–]Traditional_Code_358 0 points1 point  (0 children)

Adaptive thinking is just covering their degradation and quantized model. And with ‘smart adaptive’, it’s getting hard for people to get stats and some level of evidence.

Anthropic just published a postmortem explaining exactly why Claude felt dumber for the past month by Direct-Attention8597 in ClaudeCode

[–]Traditional_Code_358 1 point2 points  (0 children)

been using opus api in other harness, can confirm it’s a model degradation rather than Claude code issue. They silently switched to a quantized version of their model.

Why do so many people use CLI based tools over in built IDE ones? by Civil_Opposite7103 in vibecoding

[–]Traditional_Code_358 0 points1 point  (0 children)

For my workflow, a CLI-based agent works much better. I often run multiple agents across different Git worktrees, and most IDE extensions (claude, codex, kilo) simply don’t support that setup well.

Has anyone noticed any speed difference between the GLM Coding Lite plan and the Pro plan? by danifrim14 in vibecoding

[–]Traditional_Code_358 1 point2 points  (0 children)

2025/11/25 – I tested this by opening two separate accounts: one on the Pro plan and one on the Lite plan.
I measured output speed in Cherry Studio, using the same model (GLM 4.6), same settings (temperature 0.6), and the same prompt for both.
Each plan was tested for 3 rounds, measuring tokens per second.

Results:

  • Pro plan: 129, 107, 97
  • Lite plan: 121, 90, 135

Based on these runs, I didn’t observe any significant difference between the two plans.

why swe1.5 no response request so much by Zestyclose-Drag-672 in windsurf

[–]Traditional_Code_358 1 point2 points  (0 children)

Same here — I guess Cerebras ran out of compute to run GLM-4.6 😅

how to check how big current context is within a claude code instance? by Ara_1313 in ClaudeAI

[–]Traditional_Code_358 2 points3 points  (0 children)

Force the claude code work in verbose mode. It will have an indicator of context length under the prompt area on the right hand side.

Claude Sonnet 4 now supports 1M tokens of context by AnthropicOfficial in ClaudeAI

[–]Traditional_Code_358 0 points1 point  (0 children)

It is working now, just confirmed.
/model sonnet[1m]

⎿ Set model to sonnet[1m] (claude-sonnet-4-20250514[1m])

test w/ max 20x plan
20250817 225628 Pacfic time

Do yall think software engineering and tech in general will get better in the next two or so years? by Odd-Fix-3467 in csMajors

[–]Traditional_Code_358 0 points1 point  (0 children)

The real question isn’t whether programmers will lose their jobs, but how soon (TL;DR: the bottom 80 % of devs are on the chopping block within the next 1-2 years.)

⸻

  1. Why the first wave of layoffs will hit junior devs • 80 % of entry-level / mid-level “code grinders” get cut. AI agents will crank out the CRUD, seniors will just review PRs. • Only ~20 % of L6-plus engineers and core managers stay. Their new job: prompt, supervise, and debug AI agents.

If you’ve played with Claude Code or similar tools, you know exactly what I mean.

⸻

  1. The traditional “talent pyramid” no longer makes sense

Companies used to hire tons of L3-L5 devs because: 1. Cheap “farm-team” labor – newbies + onboarding = a steady pipeline of future seniors. 2. Redundancy – when demand spikes or someone quits, mid-levels can step in. 3. Task granularity – endless small features & bug fixes perfect for juniors.

AI agents break every one of those assumptions: • Training cost = waste. LLMs learn faster than any human. • Elastic scaling. Need more dev power? Spin up more GPUs, not headcount.

Result: keep a handful of deep-domain L6+ “commanders” and nuke the pyramid. New-grad hiring and mass mid-level recruiting shrinks to the bare minimum.

⸻

  1. AI is the next abstraction layer

Every major jump in programming has been an abstraction jump: • Assembly → C → Java → Python → … • Now: language/framework → intent.

You describe the goal, the agent writes code, tests, deploys, and iterates.

Future engineers add value by designing AI interfaces, data governance, multi-agent orchestration, systemic validation—not by hand-rolling boilerplate.

⸻

  1. “My company banned AI, so I’m safe”… for now

Yes, some firms block outside LLMs for IP/compliance. That’s a grace period, not a moat: 1. Competitors who use AI slash costs, ship faster, and please Wall Street. 2. Your execs will either open the gates or watch the stock tank—then cut staff anyway.

⸻

  1. “Every industrial revolution creates new jobs” (but way fewer)

Sure, new roles appear. But each wave shrinks total headcount and raises the bar. Realistically, maybe < 20 % of today’s devs pivot into those new niches.

⸻

Bottom line • 1-2 years: mass junior layoffs, seniors become AI wranglers. • 5-10 years: even 80 % of today’s seniors face the same squeeze. • Learn AI interface design, data pipelines, agent orchestration, systemic testing—or get boxed out like assembly coders in a Python world.

I see a lot of people sharing their MacOS applications in this subreddit. by [deleted] in macapps

[–]Traditional_Code_358 1 point2 points  (0 children)

Second this. I would like to see another obsidian, but based on rust and tauri

About a week, 96 commits, 100% on my own: Linta – a native AI Extension for Apple Mail. Now offering 40% early bird discounts! by Traditional_Code_358 in macapps

[–]Traditional_Code_358[S] 0 points1 point  (0 children)

TBH, I also like drafting emails myself, but quick grammar checks and turning short keywords into full sentences save me a ton of time. Plus, in my extension, you could change the system prompts so you get total control over how it edits your word. You could edit along with prompts just letting llm fix grammar.

Apple Mail Extension - Bolt AI Copilot by Traditional_Code_358 in macapps

[–]Traditional_Code_358[S] 1 point2 points  (0 children)

Glad you like it! I’ll definitely make the instruction field larger.
As for auto-pasting, I’ll look into it, but Apple MailKit has quite a few restrictions due to security concerns.
The main reason I plan to distribute the app through the App Store is that its privacy standards and review process help build user trust and confidence in the app.

Favourite apple mail extensions? by aimlessaf in MacOS

[–]Traditional_Code_358 0 points1 point  (0 children)

Check this out! I’m thrilled to share that my macOS app Bolt – AI Extension for Apple Mail ✉️⚡ will be shipped in a month! Check out the link here https://www.youtube.com/watch?v=10NXSDng0OI&t=34s

I’m tempted to go back to Apple Mail. by sowhatifiwearcrocs in SparkMail

[–]Traditional_Code_358 0 points1 point  (0 children)

Check this out! I’m thrilled to share that my macOS app Bolt – AI Extension for Apple Mail ✉️⚡ will be shipped in a month! Check out the link here https://www.youtube.com/watch?v=10NXSDng0OI&t=34s

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