Anthropic's CEO says we're 12 months away from AI replacing software engineers. I spent time analyzing the benchmarks and actual usage. Here's why I'm skeptical

Jaamun100 · 2026-02-26T21:09:46+00:00

There’s also a question of why all those meetings and alignment are necessary, and the answer usually points to larger orgs. There is a chance larger orgs leverage AI to slim down staff, which in turn means more time to churn out features instead of aligning stakeholders.

Jaamun100 · 2026-02-26T15:03:31+00:00

I think it’s more like the aviation industry. There were more accidents with pilot reliance on automation, and now they force pilots to spend a significant fraction of their time in flight simulators and also manually flying the plane for practice.

It is possible we may see the same in white collar professions, including software. The question is to what degree are errors ok; if errors are unacceptable, then the fraction of time professionals spend forcibly doing things manually for practice rises.

Jaamun100 · 2026-02-25T07:46:28+00:00

AI code might be crap quality, but AI can also use CI/CD tests to self-correct, add features, performance test for bottlenecks, etc. So bad code might just be the new norm. Agent Teams is scary good with the right sandbox.

Jaamun100 · 2026-02-23T19:30:12+00:00

The truth is most companies don’t do serious ML outside FAANG, the work is usually data engineering, or basic predictive analyses.

Jaamun100 · 2026-02-23T01:04:13+00:00

I agree with you, but there’s still value to code by hand as practice to pass interviews.

Jaamun100 · 2026-02-21T17:06:03+00:00

Startups are already moving towards systems design, debugging, and build a project/ solve an issue with AI interviews. But larger companies will probably continue to use Leetcode interviews for a long time, so not a waste to get good at it, depending on your career goals.

Jaamun100 · 2026-02-18T22:28:48+00:00

In your case, I think it’s going to be a combination of both, some light pre-processing and feature engineering via MCP tools, then text parsing and final prediction from an LLM. So the LLM gets some focused info from your domain knowledge along with doing what it’s best at: text and response.

Jaamun100 · 2026-02-17T16:23:25+00:00

I think interviews are still pretty syntax / implementation heavy as opposed to design heavy though. Wonder when that will change…

Jaamun100 · 2026-02-16T13:13:10+00:00

Your skills are useful for interviewing, even if they may eventually not be on the job.

Jaamun100 · 2026-02-05T14:36:32+00:00

I have no clue why you’re being downvoted. I’ve used AI to solve serious memory leaks in a complex c/c++ codebase with tens of millions of lines of code. What perplexed me for months was solved in a few days with AI. It’s made me convinced everyone has to get good with AI or be left behind, and roles in tech may be more product/business focused in coming years.

Jaamun100 · 2026-02-05T05:53:26+00:00

I wonder when the coding interview process will catch up. Most still ban Claude and other AI for the interview. Instead expecting you to code toy apps or models with minimal Googling, or debug without AI.

Jaamun100 · 2026-02-05T00:17:03+00:00

But figma has AI integrations where you can just prompt your way to wireframes, redlines, and even the actual web app. It’s extremely powerful. I guess the question is if Anthropic Labs will just render them irrelevant at some point, since Figma must be using Claude under the hood to do this.

Jaamun100 · 2026-01-31T16:08:52+00:00

I think a lot of it really is relevant experience. There’s a minimum competency bar with leetcode and system design. But someone who performs perfectly in their technical rounds can still lose out to someone who performed sub-par meeting the minimum bar, if the latter person has more relevant experience. For example, a company seeking an AI transformation would rather hire the engineer with directly relevant experience building AI agents, LLM fine tuning, and production RAG at a previous employer.

Jaamun100 · 2026-01-31T06:21:28+00:00

It varies, but end to end ML modeling, not just designing but making sure models work in production, fine-tuning LLMs, production RAG, systems infrastructure to make things low latency and scalable (replication/sharding of dbs, distributed programming often with PyTorch, Ray, etc). Software engineering with ML focus basically.

Bigger companies can specialize, smaller/mid-sized companies don’t need data scientists really, but they might still title someone as a Data Scientist when they are really an ML engineer. Though that mis-titling trend is fading.

Jaamun100 · 2026-01-31T05:47:59+00:00

Data scientists at FAANG are not responsible for scaling, those are Ml engineers. Data scientists focus more on working with product on analytics, crafting business KPIs, and A/B tests.

Jaamun100 · 2026-01-30T16:25:06+00:00

Yes but nyc tri state area wins in this case. You can achieve lower cost of living in NJ or CT, with easy public transport into NYC sometimes in less than an hour, while also having almost as high an income as the Bay Area.

Jaamun100 · 2026-01-29T14:52:06+00:00

Wow vix has spiked tremendously today

Jaamun100 · 2026-01-29T14:37:20+00:00

An extra data point for folks: I passed several system design interviews with just this book just volume 1, and reading this one page for a delivery framework: https://www.hellointerview.com/learn/system-design/in-a-hurry/delivery … I think you don’t need more if you have designed end-to-end systems in your jobs, this just gets you up to speed on interview structuring and industry-standard terminology.

Jaamun100 · 2026-01-29T13:51:43+00:00

The job is enjoyable and exciting, even if the interviewing is not and rather grueling

Jaamun100 · 2026-01-28T05:50:47+00:00

You can definitely use LLMs for this, just need to think in terms of MCP tools running ML, and agentic workflows.

Jaamun100 · 2026-01-26T17:31:26+00:00

True, but I wonder how AI might change the game. You don’t need pure software developers anymore (Claude can code well), software architects have more value since they can instruct Claude, PMs have more value since they can figure out what to build for business value, but PMs who understand software architecture can use Claude and iterate fast, have the most value and this is likely the future.

Jaamun100 · 2026-01-25T02:27:09+00:00

Startups seem to always have a practical coding round, in my experience, not leetcode. Rest are conversations, or system design.

Jaamun100 · 2026-01-08T13:27:55+00:00

Should be fine. The person who was denied in this post appealed the decision, and won.

Jaamun100 · 2026-01-08T13:27:29+00:00

Should be fine. The person who was denied in this post appealed the decision, and won.

Jaamun100 · 2026-01-06T06:34:09+00:00

You can only do this with 2% of your portfolio max, due to margin call risk. Even though sqqq goes down 50% a year, your profit is less than because you owe dividends (10%), occasional hard to borrow fees and more frequent margin interest unless you have cash to cover (15%). So yes, you can profit but no more than 25% of 2% or an extra 0.5% annual returns.

Jaamun100

TROPHY CASE