Mircea

🤖 Enthusiastic agentic engineer. Software / data engineer, iOS specialist. Available for freelance and consulting in Amsterdam.

[Mircea @mirceagr]

@aporia9n He talked about why he follows 0 people on some podcast. He doesn’t use the follow feature, but does use private lists instead to follow people by topic. He gave some reasons but can’t remember. I think the algorithm was one, but can’t remember.

[Mircea @mirceagr]

@handotdev I think you’re miss reading the athelte situation though. Atheltes go in the pain cave during racing, not when they’re training. It’s too much damage to do it in training, and not productive.
Also, quite the opposite, ultra endurance athletes encourage a positive state of mind

[Mircea @mirceagr]

@avlok International not supported yet right? It’s not clear from the signup form on the website. It accepted all international details (address, phone number) but I saw at the end the W9 mention in the terms - which is for US citizens only I think, and for internationals is W8.

[Aaron Levie @levie]

Another week on the road meeting with a couple dozen IT and AI leaders from large enterprises across banking, media, retail, healthcare, consulting, tech, and sports, to discuss agents in the enterprise.

Some quick takeaways:

* Clear that we’re moving from chat era of AI to agents that use tools, process data, and start to execute real work in the enterprise. Complementing this, enterprises are often evolving from “let a thousand flowers bloom” approach to adoption to targeted automation efforts applied to specific areas of work and workflow.

* Change management still will remain one of the biggest topics for enterprises. Most workflows aren’t setup to just drop agents directly in, and enterprises will need a ton of help to drive these efforts (both internally and from partners). One company has a head of AI in every business unit that roles up to a central team, just to keep all the functions coordinated.

* Tokenmaxxing! Most companies operate with very strict OpEx budgets get locked in for the year ahead, so they’re going through very real trade-off discussions right now on how to budget for tokens. One company recently had an idea for a “shark tank” style way of pitching for compute budget. Others are trying to figure out how to ration compute to the best use-cases internally through some hierarchy of needs (my words not theirs).

* Fixing fragmented and legacy systems remain a huge priority right now. Most enterprises are dealing with decades of either on-prem systems or systems they moved to the cloud but that still haven’t been modernized in any meaningful way. This means agents can’t easily tap into these data sources in a unified way yet, so companies are focused on how they modernize these.

* Most companies are *not* talking about replacing jobs due to agents. The major use-cases for agents are things that the company wasn’t able to do before or couldn’t prioritize. Software upgrades, automating back office processes that were constraining other workflows, processing large amounts of documents to get new business or client insights, and so on. More emphasis on ways to make money vs. cut costs.

* Headless software dominated my conversations. Enterprises need to be able to ensure all of their software works across any set of agents they choose. They will kick out vendors that don’t make this technically or economically easy.

* Clear sense that it can be hard to standardize on anything right now given how fast things are moving. Blessing and a curse of the innovation curve right now - no one wants to get stuck in a paradigm that locks them into the wrong architecture. One other result of this is that companies realize they’re in a multi-agent world, which means that interoperability becomes paramount across systems.

* Unanimous sense that everyone is working more than ever before. AI is not causing anyone to do less work right now, and similar to Silicon Valley people feel their teams are the busiest they’ve ever been.

One final meta observation not called out explicitly. It seems that despite Silicon Valley’s sense that AI has made hard things easy, the most powerful ways to use agents is more “technical” than prior eras of software. Skills, MCP, CLIs, etc. may be simple concepts for tech, but in the real world these are all esoteric concepts that will require technical people to help bring to life in the enterprise.

This both means diffusion will take real work and time, but also everyone’s estimation of engineering jobs is totally off. Engineers may not be “writing” software, but they will certainly be the ones to setup and operate the systems that actually automate most work in the enterprise.

[Mircea @mirceagr]

@levelsio @vytisbareika What did the doctors say about your LDL cholesterol? Isn’t your range considered high? I had similarly high and taking medication.

[dax @thdxr]

inference is very profitable and probably a good opportunity to understand some basic business math

1. companies buy long lived assets like GPUs. these are one time costs and the asset depreciates over time

2. once you own this asset, you can plug it in and produce tokens which you can sell. the cost of goods sold here can be very low and you might be making 90% margins at scale, this is why we say inference is profitable

3. then you also hire employees to do r&d work to improve your systems, come up with new models, expand the business

if you add these 3 up you end up with $0. you're not producing a profit because the business is growing and you're reinvesting it all buying assets or r&d to meet demand

if it's obvious to other people the business is working, you can raise money from them to accelerate all these numbers so they max out in 5 years instead of 25

so on paper you'll be "losing money" every year but that's because you want to make sure you lock down the opportunity before someone else

the bigger your market is the bigger this burn can be because it's a function of potential

so when you see these companies losing a lot of money it doesn't mean the whole concept of their business broken

it's possible they misjudge and overinvest on 1+3 and will suffer some consequences but fundamentally 2 does work

[Mircea @mirceagr]

@badlogicgames 2pi

[Mircea @mirceagr]

@levelsio I couldn’t

[Mircea @mirceagr]

Slop creep. I like the term. The planning phase deserves a lot more attention now, when coding agents are writing most of the code.

[boris @boristane]

slop creep is what happens when you turn your brain off and hand the thinking to coding agents

each individual change is fine, but all together, you have a pile of crap

we're witnessing this happen in real-time across everything

https://t.co/2hkDx8RAhE

[SMB Attorney @SMB_Attorney]

You guys don’t get it yet.

Everyone keeps saying AI is going to replace lawyers.

I don’t think people understand how this actually plays out.

Let’s say you use AI to draft a contract.

The contract misses something important. A year later it costs you two million dollars.

What do you do?

Right now, you sue your lawyer.

In the AI world, you’d sue the AI company.

Two things can happen.

Option 1: The AI company has liability for legal advice.

If that’s the case, every AI company will immediately stop letting consumers use AI for real legal work. The liability risk is massive.

Option 2: The AI company has no liability because of disclaimers.

If that happens, every state bar in the country will say consumers are being exposed to unregulated legal advice and call it the unauthorized practice of law.

And they’ll shut it down that way.

Either path leads to the same outcome.

Consumer AI will be limited to generic “Wikipedia-style” legal information and LegalZoom level document prep.

But the real AI tools?

Those will live inside law firms.

Lawyers will use them to move faster, analyze more data, and run way more matters at once.

The M&A lawyer doing 5 deals at a time will do 50.

Trial lawyers will run far more cases simultaneously.

The idea that AI replaces lawyers probably dies.

The more likely outcome is that AI supercharges the best lawyers and makes the profession even more profitable than ever.

[Mircea @mirceagr]

@DeanFiacco @levelsio Is it context rot? You can run the /statusline command to display info about context usage in the status bar. Highly recommended.

Did you have a context compaction in the session? I’ve found it doesn’t work so well for Claude models. It’s much better for Codex

[Mircea @mirceagr]

Very interesting. I hadn’t actually considered this. If some big companies don’t adopt AI, or heavily limit it, smaller teams could compete heads on with.

[dax @thdxr]

we spoke to a company today who's security team is so concerned by ai code they're considering banning ai tools

your first reaction might be "they're gonna get left behind" but if you are practical their concerns aren't invalid

if you are a huge multi national org with tens of thousands of employees and they just got a button that appears to do their work, it's gonna get pushed a lot

and the process around knowing what is making it to production is totally melting

being honest we're all getting a bit lazier

see that kiro related aws outage as a real life example

so they're genuinely arguing over how much this is going to be allowed esp since the net productivity gains for the average dev seem to be pretty low

[Mircea @mirceagr]

A way to feel dumber is to make smarter friends.

[Mario Zechner @badlogicgames]

recommended reading by @yobo. not signing everything 100% but many good observations and thoughts in there.

https://t.co/R7xC0WEBL3

[Drew Breunig @dbreunig]

Two beliefs about the agentic coding narrative:

1. Most devs underestimate what they bring to the agent. Agents amplify skills.

2. Most coding agent written software we see are personal tools, not capital-P products. Shipping remains hard.

https://t.co/NccmdesOIc

[Simon Willison @simonw]

I've published the first two chapters of a new guide to Agentic Engineering Patterns - coding practices and patterns to help get the best results out of coding agents like Claude Code and OpenAI Codex https://t.co/XIskcgeBFE

[Thorsten Ball @thorstenball]

"I am the bottleneck now"

Few more thoughts

[Mircea @mirceagr]

@danielesesta @SBF_FTX @solana AefiougujuPuqC6ZvP9GwbxyVJzHEEvpKrep8V2DqgMp

[Mircea @mirceagr]

@JaydenGomezzz Thanks. Giving it a try now. The desktop app is great, but looks like it doesn’t have the “trading” feature yet

[Mircea @mirceagr]

@cryptowat_ch Awesome! The app feels great. Thanks. Giving it a try now!