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AI is ushering in a “tiny team” era

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Re: AI is ushering in a “tiny team” era

#21

Post by apical_dendrite »

ldjkfkdsjnv wrote: post #10
apical_dendrite wrote: post #3

When I worked at a startup that tried to maximize revenue per employee, it was an absolute disaster for the customer. There was zero investment in quality - no dedicated QA and everyone was way too busy to worry about quality until something became a crisis. Code reviews were actively discouraged because it took people off of their assigned work to review other people's work. Automated testing and tooling were minima…

Theres two types of software, the ones no one uses, and the ones people complain about

I've worked at a number of companies - the frequency and seriousness of customer issues was way beyond anything I've experienced anywhere else.

Re: AI is ushering in a “tiny team” era

#22

Post by jprokay13 »

charliebwrites wrote: post #16
WXLCKNO wrote: post #8

I'm working on a bunch of different projects trying out new stuff all the time for the past six months. Every time I do something I add another layer of AI automation/enhancement to my personal dev setup with the goal of trying to see how much I can extend my own ability to produce while delivering high quality projects. I definitely wouldn't say I'm 10x of what I could do before across the board but a solid 2-3x ave…

> Every time I do something I add another layer of AI automation/enhancement to my personal dev setup with the goal of trying to see how much I can extend my own ability to produce while delivering high quality projects Can you give some examples? What’s worked well?

If you haven’t, adding in strict(er) linting rules is an easy win. Enforcing documentation for public methods is a great one imo.

The more you can do to tell the AI what you want via a “code-lint-test” loop, the better the results.

Re: AI is ushering in a “tiny team” era

#23

Post by JaggerFoo »

Some excellent ideas presented in the article. It doesn't matter if they all pan out, just that they expand our thinking into the realm of AI and its role in the future of business startups and operations.

Revenue per employee, to me, is an aside that distracts from the ideas presented.

Re: AI is ushering in a “tiny team” era

#24

Post by lmeyerov »

ldjkfkdsjnv wrote: post #9

I think this is the beginning of the end of early stage venture capital in b2b saas. Growth capital will still be there, but increasingly there will be no reason to raise. It will empower individuals with actual skill sets, rather than those with fancy schools on their resume

I think bar for b2c, prosumer, SMB, yes.. folks want to see fast revenue growth (vs eyeballs & ideas)... but enterprise... not as much, and that's half the b2b market

Reverse there afaict, enterprise + defense tech are booming. AI means get to do a redo + extension of the code automation era. It's fairly obvious to buyers + investors this time around so don't even need to educate. Likewise, in gov/defense tech, palantir broke the dam, and most of our users there have an instinctive allergic reaction to palantir+xai, so pretty friendly.

Re: AI is ushering in a “tiny team” era

#25

Post by jordanb »

simonw wrote: post #20
nemothekid wrote: post #12

I'm not entirely convinced this trend is because AI is letting people "manage fleets of agents". I do think the trend of the tiny team is growing though and I think the real driver were the laysoffs and downsizings of 2023. People were skeptical if Twitter would survive Elon's massive staff cuts and technically the site has survived. I think the era of the 2016-2020 empire building is coming to an end. Valuing a mana…

I think the productivity improvement you can get just from having a decent LLM available to answer technical questions is significant enough already even without the whole Agent-based tool-in-a-loop thing. This morning I used Claude 4 Sonnet to figure out how to build, package and ship a Docker container to GitHub Container Registry in 25 minutes start to finish. Without Claude's help I would expect that to take me a…

Eh I felt that way about the internet in 2010s. Seemed like virtually any question could be answered by a google query. People were making jokes that a programmer's job mostly consisted of looking things up on stack overflow. But then google started sucking and SO turned into another expertsexchange (which was itself good in the 2000s).

So far from what I've experienced AI coding agents automate away the looking things up on SO part (mostly by violating OSS licenses on Github). But that part is only bad because the existing tools for doing that were intentionally enshitified.

Re: AI is ushering in a “tiny team” era

#27

Post by teaearlgraycold »

WXLCKNO wrote: post #8

I'm working on a bunch of different projects trying out new stuff all the time for the past six months. Every time I do something I add another layer of AI automation/enhancement to my personal dev setup with the goal of trying to see how much I can extend my own ability to produce while delivering high quality projects. I definitely wouldn't say I'm 10x of what I could do before across the board but a solid 2-3x ave…

Definitely agree small teams are the way to go. The bigger the company the more cognitive dissonance is imposed on the employees. I need to work where everyone is forced to engage with reality and those that don’t are fired.

Re: AI is ushering in a “tiny team” era

#28

Post by dyauspitr »

mikeocool wrote: post #17
rahimnathwani wrote: post #13

Earlier quoted context omitted.

If I'm buying soup, I'd prefer the manufacturer, the retailer, and any other part of the supply chain to be as efficient as possible, so they can compete in the market to offer me soup of a given quality at the lowest possible cost. An individual consumer doesn't derive any benefit from companies missing out on automation opportunities. Would you prefer to buy screws that are individually made on a lathe?

Personally, the best soups I’ve ever had were not made in kitchens that were optimized for efficiency or automation, they were optimized for quality. They weren’t cheap soups, but they sure were good.

Quality is a function of the ingredients used and the correct preparation. Neither of these things are something machines can’t do.

Re: AI is ushering in a “tiny team” era

#29

Post by malux85 »

charliebwrites wrote: post #16
WXLCKNO wrote: post #8

I'm working on a bunch of different projects trying out new stuff all the time for the past six months. Every time I do something I add another layer of AI automation/enhancement to my personal dev setup with the goal of trying to see how much I can extend my own ability to produce while delivering high quality projects. I definitely wouldn't say I'm 10x of what I could do before across the board but a solid 2-3x ave…

> Every time I do something I add another layer of AI automation/enhancement to my personal dev setup with the goal of trying to see how much I can extend my own ability to produce while delivering high quality projects Can you give some examples? What’s worked well?

For us it’s been auto-generating tests - we focus efforts on having the LLM write 1 test, manually verifying it. Then use this as context and tell the llm to extend to all space groups and crystal systems.

So we get code coverage without all the effort, it works well for well defined problems that can be verified with test.

Re: AI is ushering in a “tiny team” era

#30

Post by haiku2077 »

charliebwrites wrote: post #16
WXLCKNO wrote: post #8

I'm working on a bunch of different projects trying out new stuff all the time for the past six months. Every time I do something I add another layer of AI automation/enhancement to my personal dev setup with the goal of trying to see how much I can extend my own ability to produce while delivering high quality projects. I definitely wouldn't say I'm 10x of what I could do before across the board but a solid 2-3x ave…

> Every time I do something I add another layer of AI automation/enhancement to my personal dev setup with the goal of trying to see how much I can extend my own ability to produce while delivering high quality projects Can you give some examples? What’s worked well?

- Extremely strict linting and formatting rules for every language you use in a project. Including JSON, YAML, SQL.

- Using AI code gen to make your own dev tools to automate tasks. Everything from "I need a make target to automate updating my staging and production config files when I make certain types of changes" or "make an ETL to clean up this dirty database" to "make a codegen tool to automatically generate library functions from the types I have defined" and "generate a polished CLI for this API for me"

- Using Tilt (tilt.dev) to automatically rebuild and live-reload software on a running Kubernetes cluster within seconds. Essentially, deploy-on-save.

- Much more expansive and robust integration test suites with output such that an AI agent can automatically run integration tests, read the errors and use them to iterate. And with some guidance it can write more tests based on a small set of examples. It's also been great at adding formatted messages to every test assertion to make failed tests easier to understand

- Using an editor where an AI agent has access to the language server, linter, etc. via diagnostics to automatically understand when it makes severe mistakes and fix them

A lot of this is traditional programming but sped up so that things that took hours a few years ago now take literally minutes.

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