惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

S
SegmentFault 最新的问题
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
B
Blog RSS Feed
Y
Y Combinator Blog
T
Tailwind CSS Blog
博客园 - 三生石上(FineUI控件)
J
Java Code Geeks
Stack Overflow Blog
Stack Overflow Blog
aimingoo的专栏
aimingoo的专栏
Jina AI
Jina AI
The GitHub Blog
The GitHub Blog
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
A
About on SuperTechFans
H
Hackread – Cybersecurity News, Data Breaches, AI and More
D
Docker
酷 壳 – CoolShell
酷 壳 – CoolShell
C
Check Point Blog
M
MIT News - Artificial intelligence
Last Week in AI
Last Week in AI
V
V2EX
腾讯CDC
F
Fortinet All Blogs
博客园 - 叶小钗
T
The Blog of Author Tim Ferriss

Hacker News - Newest: "AI"

AI can't read an investor deck AI as an attorney? Student uses ChatGPT, Gemini to sue UW over alleged racial discrimination Hacking MCP Servers in AI Systems – The Rug Pull: Tool Changes After Approval GitHub - MeepCastana/KubeezCut: Free Web based video editor Can AI judge journalism? A Thiel-backed startup says yes, even if it risks chilling whistleblowers Coming soon: 10 Things That Matter in AI Right Now DARPA built an AI to fact-check enemy weapons claims What explains heterogeneity in AI adoption? When AI Meets Muscle: Context-Aware Electrical Stimulation Promises a New Way to Guide Human Movements - Department of Computer Science AI Changed How We Build. It Did Not Change What Matters. Linux rules on using AI-generated code - Copilot is OK, but humans must take 'full responsibility for the… Meta spins up AI version of Mark Zuckerberg to engage with employees Code Mode: Let Your AI Write Programs, Not Just Call Tools | TanStack Blog GitHub - Delavalom/graft: Go framework for building AI agents. Type-safe tools, multi-provider (OpenAI, Anthropic, Gemini, Bedrock), zero vendor SDKs. India's TCS tops estimates, says new AI models did not dent services demand Gen Z's fading AI hype Strong feeling: we are in a folded AI reality GitHub - machinarii/total-recall-catalog: A reference catalog of latest knowledge retrieval, memory & RAG systems GitHub - mensfeld/code-on-incus: Give each AI agent its own isolated machine with root, Docker, and systemd. Active defense detects and stops threats automatically.. Quantization, LoRA, and the 8% Problem: Benchmarking Local LLMs for Production AI Iran war: We spoke to the man making Lego-style AI videos that experts say are powerful propaganda Powell, Bessent discussed Anthropic's Mythos AI cyber threat with major U.S. banks GitHub - immartian/bellamem: Persistent belief-graph memory for AI agents. Retrieves decisive context by importance — not recency, not RAG, not /compact. recursive-mode: The Repo-Native Operating System for AI Engineering After the attack on Sam Altman's home, will AI CEO's go on the offensive? The biggest advance in AI since the LLM Opus 4.6 vs GPT 5.4 One Prompt Unity World Generation Test “AI polls” are fake polls Client Challenge Can AI be a 'child of God'? Inside Anthropic's meeting with Christian leaders
AI doesn't kill SaaS. It kills bad priorities
erdinc · 2026-04-30 · via Hacker News - Newest: "AI"
It's not as big a loss as it looks, because now I have leftover supplies, which will help me talk myself into doing this all over again with a new project!

A CTO showed me a dashboard last month. His team had built it. Developer metrics pulled from GitHub, looked clean, worked fine.

I asked the obvious questions:

Are you launching it to the org? Does it connect to Jira? You mentioned surveys, are those wired in?

“Yeah, the surveys would be easy to add. We’ll get to it.”

They didn’t get to it. They won’t.

And that’s the pattern I keep seeing right now, the same one I saw in the 2010s, just with a new soundtrack:

“We can build it ourselves. AI is killing SaaS anyway.”

Maybe some tools will disappear. But here’s what I think most people are missing:

Everyone’s measuring AI by how much it lets them build.

The real question is how much it lets them stop.

Cheaper code doesn’t make building the right thing matter less. It makes building the wrong thing more expensive, because now you’re maintaining it, improving it, defending it in roadmap meetings, explaining it to the next hire. Forever. For something that isn’t your business.

I sell engineering analytics, so yes, I have a stake in this argument. But that’s also why I notice the pattern earlier than most: the teams who build their own version almost never finish it. The dashboard ships. The integration doesn’t. The survey loop doesn’t. The thing that would have actually changed how the team works, that’s the part that gets deprioritized the moment a real customer problem shows up. As it should.

The best engineering leaders I work with don’t ask “can we build this?” anymore. The answer is almost always yes now.

They ask:

What am I going to stop building this quarter?

Here is a simple 3 questions to ask before you build the next one

1. Will this still get attention in six months?

Not “will we finish v1.” Will someone own it, improve it, defend its roadmap slot against the next shiny thing? If the honest answer is no, you’re not building a tool. You’re building a prototype that will quietly rot in production.

2. What’s the second integration?

Most internal tools work for one data source. The value shows up at the second. GitHub metrics alone are vanity. GitHub plus JIRA plus survey data tells you something. If your team can articulate the first integration but waves vaguely at the second (”we’ll get to it”), the project is already dead. They just don’t know it yet.

3. If a vendor solved this for the cost of one engineer-month, would you still build it?

“can we build it cheaper” (you probably can’t, once you count maintenance). The question is whether building it gives you a strategic advantage your competitors can’t buy. For 95% of internal tooling, the answer is no. It’s table stakes pretending to be differentiation.

If the answer is yes, build it. Own that capability. If the answer is no, you already know what to do.

No posts