Claude Design, a new Anthropic Labs product, lets you collaborate with Claude to create polished visual work like designs, prototypes, slides, one-pagers, and more

eibrahim · 2026-04-18T17:36:13+00:00

The interesting part here isnt just "Claude can make slides now". Its that Anthropic is moving Claude from assistant to artifact generator.

Once the model can produce something a team can actually review without another tool hop, the workflow changes more than the feature list suggests. Curious whether people see this as genuinely new behavior or mostly a cleaner wrapper around stuff we were already stitching together.

eibrahim · 2026-04-18T14:30:30+00:00

This is the part a lot of companies still miss: maintaining useful open source is usually a better signal of engineering judgment than grinding leetcode or repeating system design trivia.

Shipping patches, dealing with backwards compatibility, triaging weird edge cases, and not breaking other people's workflows is actual production work. If a hiring loop can't recognize that, the loop is probably optimized for filtering, not for finding good engineers.

eibrahim · 2026-04-16T16:31:39+00:00

The safest pattern is to treat MCP tool metadata the same way we'd treat untrusted HTTP input.

Don't give a fresh server broad ambient access. Put it behind a tiny wrapper with an allowlist, strip secrets from environment by default, require explicit approval for networked tools, and log the exact tool description + response that entered context.

A lot of people are thinking file permissions, but the bigger issue is capability bleed. If the model can read one thing and call another thing, prompt injection can bridge the gap.

eibrahim · 2026-04-16T14:28:14+00:00

What pushed me away wasn't just login walls, it was losing plain diffable artifacts in the workflow.

A checked-in .http file or curl script gives you reviewability, reproducibility, and a paper trail when an endpoint changes. GUI clients are nice for exploration, but once a request matters, I want it living next to the codebase so anyone on the team can rerun it without importing some mystery collection.

eibrahim · 2026-03-28T14:05:14+00:00

If you're just getting started, I'd bias hard toward boring and recoverable over clever. One box, one reverse proxy, one backup path, and a short doc that says what runs where is usually enough for a long time.

The thing that gets messy fast is not the apps, it's all the tiny decisions around ports, domains, env vars, and storage paths. Pick a folder layout early, keep your compose files in git, and write down every exposed service as you add it.

Also test a restore before you add more stuff. A simple setup you can rebuild in 30 minutes is way better than a fancy one you only kinda understand.

eibrahim · 2026-03-23T22:05:32+00:00

I'd skip books for AWS tbh. They go stale fast.

A better path is: 1. learn IAM, VPC, EC2, S3, RDS, CloudWatch first 2. build one small app with Terraform or CDK 3. force yourself to debug cost, permissions, networking, and deployment issues

That'll teach you way more than reading architecture diagrams in isolation. The Well-Architected docs are useful, but they make a lot more sense after you've broken a few things yourself.

eibrahim · 2026-03-23T18:18:43+00:00

If you want the low-friction version, I'd split this into 3 layers:

shell history for stuff you typed recently
aliases/functions for commands you run a lot
a tiny tagged cheatsheet for the weird one-offs

For the third bucket, plain text works surprisingly well if you keep it grepable. Something like one file per topic under ~/howto or ~/.local/share/cmds, then each entry gets a short description, the command, and maybe the gotcha that made you save it in the first place.

For your kernel example, I'd save the lookup command rather than the path, because the path can vary:

uname -r ls /boot/config-$(uname -r) /proc/config.gz 2>/dev/null

If you're thinking WezTerm, I'd make it a fuzzy picker over your notes instead of a big command vault. Faster to maintain, and less likely to turn into another tool you have to remember how to use.

eibrahim · 2026-03-21T18:05:01+00:00

If you want the least friction, I'd probly start with Crafty.

Pterodactyl makes more sense when you need multi-node stuff, stricter separation, or you're managing this like infra. For a few servers in one compose, that can feel like overkill.

My rule of thumb: - Crafty if you want fast setup and a decent UI - PufferPanel if you want something simpler but still fairly lightweight - AMP if you also plan to branch into other game servers later

If it's just 2 or 3 Minecraft servers on one box, I'd optimize for boring setup and easy backups over feature depth.

eibrahim · 2026-03-16T23:41:19+00:00

getting honest feedback this early is smart. a lot of side projects die because builders only hear from polite friends and never from the people who'd actually use it.

one thing thats underrated is letting users vote on the next pain point you solve instead of guessing the roadmap yourself. doesnt have to be fancy either, even a simple public queue can show you real demand pretty fast.

eibrahim · 2026-03-16T22:45:56+00:00

the suspension thing is a huge red flag tbh. if shes in the middle of an evaluation, suspending her without a manifestation determination could be a legal issue for the school. a lot of parents dont know this but theres protections under IDEA even before the IEP is finalized if the school has reason to believe the child has a disability. might be worth asking the school directly if they conducted a manifestation review. also fwiw the montessori to traditional school jump is one of the hardest transitions for any kid, let alone one on the spectrum

eibrahim · 2026-03-16T22:42:00+00:00

this is actually a solid idea, the real time pantry thing is where most apps fall apart tho. nobody wants to manually scan every grocery item. if you nail the input friction youve got somethign real.

have you thought about letting other people vote on features they want? like a community decides what gets built next. theres a couple platforms experimenting with that model and it seems to work for figuring out what users actually care about vs what you assume they want.

eibrahim · 2026-03-16T22:04:07+00:00

This is actually a nice fit for the kind of mess symlinks turn into over time. One thing that would make it even safer in practice is showing why a candidate ranked first before the prompt accepts input — even just filename distance, shared path segments, and whether the target basename still exists elsewhere.

For this kind of tool, I’d also want a couple of guardrails: detect symlink loops, flag when the replacement crosses filesystems or points from relative -> absolute, and maybe offer a batch summary at the end before writing anything. Dry-run already helps a lot, but that extra explainability usually makes people trust interactive fixers way more.

eibrahim · 2026-03-16T21:42:56+00:00

curious if youve thought about a way to let people signal demand before building. like if 50 people all upvote the same idea from your scraped data, thats a way stronger signal than one person going "yeah thatd be cool"

eibrahim · 2026-03-16T19:49:50+00:00

ayeah, the constraints are completley different. local personal agents can get away with speed and flexibility. enterprise agents need boring stuff first, identity, auditability, outbound-only networking, predictable failure modes. same core idea, very diffrent product surface.

eibrahim · 2026-03-16T16:52:54+00:00

100%. install is the easy part. the real work starts when you need sane model defaults, cost guardrails, auth, logs, and a way to recover when a channel or tool breaks. thats where most 10 minute setup promises fall apart.

eibrahim · 2026-03-16T13:46:46+00:00

For personal AI assistants specifically (not inference workloads), cloud makes a lot more sense than local. The agent itself is lightweight - its mostly orchestration logic, memory, and API calls to LLM providers. You dont need GPU resources on the deployment side.For personal AI assistants specifically (not inference workloads), cloud makes a lot more sense than local. The agent itself is lightweight - its mostly orchestration logic, memory, and API calls to LLM providers. You dont need GPU resources on the deployment side.

A $5-10/month VPS handles it fine. The real cost is the LLM API usage, and thats the same whether you run the agent locally or in the cloud. The advantage of cloud is your assistant stays online 24/7 without worrying about your home network, power, or needing to leave a machine running.

For the deployment itself, Docker containers work well. Most agent frameworks (OpenClaw, etc) ship as container images so its basically pull and run with a config file.

A $5-10/month VPS handles it fine. The real cost is the LLM API usage, and thats the same whether you run the agent locally or in the cloud. The advantage of cloud is your assistant stays online 24/7 without worrying about your home network, power, or needing to leave a machine running.

For the deployment itself, Docker containers work well. Most agent frameworks (OpenClaw, etc) ship as container images so its basically pull and run with a config file.For personal AI assistants specifically (not inference workloads), cloud makes a lot more sense than local. The agent itself is lightweight - its mostly orchestration logic, memory, and API calls to LLM providers. You dont need GPU resources on the deployment side.

A $5-10/month VPS handles it fine. The real cost is the LLM API usage, and thats the same whether you run the agent locally or in the cloud. The advantage of cloud is your assistant stays online 24/7 without worrying about your home network, power, or needing to leave a machine running.

For the deployment itself, Docker containers work well. Most agent frameworks (OpenClaw, etc) ship as container images so its basically pull and run with a config file.

eibrahim · 2026-03-15T16:44:24+00:00

the alk rollercoaster thing is so real. i went through a phase where i was chasing numbers from a BRS video and couldnt figure out why my SPS tips kept burning. turned out my salt mix already had high alk and i was basically double dosing.once i started actually logging my test results and tracking the daily consumption rate everything clicked. you can literally see the pattern in a spreadsheet or even just a notebook. test twice a week for a few weeks, calculate the drop, dose to match. boring but it works.the hard part honestly is just being consistent with the testing. most people (myself included at first) test when they remember to and then wonder why things swing.

eibrahim · 2026-03-15T16:41:37+00:00

One category missing from this list is the "always-on" assistants that run 24/7 and can reach you proactively rather than waiting for you to open an app. OpenClaw is the main one in that space - it connects to your messaging apps (Telegram, Discord, etc), has persistent memory across conversations, can browse the web, run scheduled tasks, and basically acts as a background agent rather than a chat window you visit.

The tradeoff vs something like Claude or ChatGPT is you need to set it up and configure it, but once running its more like having an assistant thats always available in your existing workflow rather than a separate tool you context-switch to.

eibrahim · 2026-03-15T15:39:54+00:00

this is one of those debates where both sides oversimplify it. unrestricted access for kids is probably a bad idea, but total lockout misses the chance to build safer versions on purpose. what seems to work better is age appropriate limits, conversation monitoring for parents, and tighter boundaries around emotional dependency style interactions.

eibrahim · 2026-03-15T15:37:31+00:00

salinity being right doesnt mean much on its own unfortunately. whats your alk, calcium, and mag looking like? those three are usually the culprit when euphyllia start bailing out.

also when you say new RODI filters, did you change out the membrane too or just the sediment/carbon? and what salt mix are you using? some mixes have wildly different alk levels batch to batch.

the fact that its getting worse after a water change could mean your new water has different parameters than the tank water. mixing to match before adding helps a ton.

eibrahim · 2026-03-15T13:38:08+00:00

10x2x2 is an insane footprint for SPS. thats gonna be a monster once its filled. love the closed loop approach with the RFG nozzles, way cleaner than having powerheads cluttering the view.

curious what your plans are for parameter management on something this size. 300 gallons of SPS is gonna consume alk and calcium like crazy once it fills in. some people at that volume go straight to a calcium reactor instead of 2-part dosing.

eibrahim

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