[adamtaylor_13]

Are there any battle-tested strategies for hiring that are generally known to be good, but aren't often used because it's hard or doesn't scale?

Asking because my business is growing and we've gotten lucky with our hires so far, but I'd like to add my discipline to hiring well.

[addaon]

Ask the best people you’ve ever worked with who the best people they’ve worked with are. Recurse. When names start repeating through different graph paths, make those people an offer they can’t refuse. Once they join, ask them to do the same, and give them the budget and role to make it happen.

[sanderjd]

The best people I've ever worked with and the best people they've worked with all have good jobs at all times. You have to have a mechanism for matching with people who are actually interested in a new job.

[addaon]

Yes, making people an offer they can't refuse isn't scalable. It generally requires both deep pockets and the time investment to understand what would motivate them to leave a good job for one that they think can be great.

[thih9]

Is this really battle-tested, as in: did you see this work in practice or do you have a reliable source?

Or is this something you came up with?

[jppope]

No, this is 100% battle tested. I can't drop numbers but we just did a study at work comparing referrals to non-referrals... its night and day. Referrals are out performing across the board. the only problem is that eventually you run out of referrals

[itronitron]

>> Referrals are out performing across the board

I expect a lot of that is due to the referral being familiar with an already ensconced employee, as well as the referrer being incentivized to ensure the referral's success.

[addaon]

I am aware of several startups that started this way, and have been involved in some. The quality of the results depends on who you seed the graph with, of course; but I’ve seen it work well.

As requested by the original poster, it doesn’t scale.

[vanuatu]

+1, referred candidates at my company perform way better in interviews and on the job compared to cold applicants

[cloche]

Unless you're hiring for rare roles that require niche skills, it's unlikely that you'll get people that are in overlapping networks. If you do, you might be encountering the problem where Company A has a bunch of people that used to work at Company B. Now Company A is just an "old boys club" from Company B and is biased towards their old colleagues.

If you ask for single referrals, how do you combat the problem of people just recommended people based on friendships and not actually work quality?

[addaon]

> it's unlikely that you'll get people that are in overlapping networks

Networks all overlap if you search deep enough, ask Kevin Bacon. For good-enough talent and starting with random nodes, yeah, you'll probably not overlap. But there's a few dozen people of top talent for any particular role you're looking for, so by the time you iterate to the top of the tree, you really do get a lot of repeats.

[alexpotato]

Recommendation from a trusted 3rd party.

Bill Gurley has a great line about this:

"I use LinkedIn like this:

If Person A reaches out to me and there is a Person B that is a common connection between A and myself, I want to be able to call Person B and have 100% confidence in their evaluation. That's the bar I set to connect with someone on LinkedIn."

From:

https://www.youtube.com/watch?v=xmYekD6-PZ8

[Bjartr]

Apprenticeship? Actually spend time working with them on real work.

It's both hard and doesn't scale.

[vkou]

The problem is that you have 100 applicants and one apprentice slot.

[maccard]

You don’t have 100 candidates though - you likely have 90 applicants that just fail to meet the basic criteria. I hire for games and every single job posting we make for programmers we get about 10% of applicants who have literally never programmed before, even for lead level roles .

[vkou]

Well, these days you'll have 1000 candidates, you drop the 900 that fail to meet the basic criteria, and you're left with 100 that you can't immediately tell are frauds.

[maccard]

I’ve been hiring for remote game programmer jobs. We got 300 applicants in 6 weeks for the last one.

[dan-robertson]

I think various ‘longer interview’ processes can be good by reducing the chance of particularly regretted hires. This could be internships (but note this goes two ways and you want interns to accept offers and recommend the programme to their friends even if they are not hired) or work sample tests. Both have the downside that they are more work for the candidate (especially internships or some other short-term-to-possibly-long-term position) and so experienced candidates who feel they have better options and less need to prove themselves typically won’t take part (this depends a bit on how much they want to work at your specific company of course). Potentially this isn’t so bad – competing to hire the same people as everyone else is going to be more expensive – or potentially it is bad – maybe there’s a reason those candidates are in high demand and you will suffer from only getting a look at people who didn’t fit the typical pattern. I think it’s going to depend a bunch on how good you are at sourcing candidates and how hot your firm is.

[antonymoose]

We source our intern-to-Junior pipeline from a good state school from which we have a few graduates. We have about an 80% placement rate for the interns. We’ve yet to have any abusive or bad hires, this being a fully remote company. For Senior hires, a prior employee founded a Java User Group and sourced several high quality engineers from the pool of visitors. So, build a pipeline and play the long game?

Previously we’ve sourced candidates via a reputable recruiter from an in-town firm that our manager can routinely sit down with and build a relationship over the years. This had a good rate with only one bad placement. We ultimately traded time cost for money cost in that one, but I liked it.

The worst outcomes we’ve had were via LinkedIn jobs posts. By the time our in-house full-time recruiter would give us resumes half would be obvious frauds with most of the remainder being subtle frauds. I blame this in good part to having non-technical staff as the first filter in our pipeline.

Unfortunately the firm makes money hand over fist year on year so we are no longer a lean mean operation but a burgeoning beauracracy with room to hide, rest, and vest.

[edoceo]

I do quick interviews, then hire hourly for a single scoped task. Then see how they play, communication skills, code exploring all that happens on the task. Only works when candidate is not otherwise engaged, has never worked for non-coding/sysadmin roles.

[jgafni]

I like the other comment regarding asking people you know or have hired for referrals. But there's a separate question about what to do when you don't have any referrals to rely on.

In the past, the answer was to rely on recruiting experts and your own experience to analyze resumes, and to hope that some fraction of your time interviewing was well spent. But as others in this thread have pointed out, the quality of resumes as a signal is rapidly decreasing with AI. So now the question is what the new signal should be.

The purpose of hiring is really just to understand three things: (1) can the person do the job, (2) will I and the rest of the team want to work with them for the foreseeable future, and (3) are there any red flags. The latter two are assessed in interviews or backchanneling. But the first, "can this person do the job," is the one that has gotten much harder to tell from the resume alone.

What does "can the person do the job" even mean in the era of AI? For SWE, a lot of teams are still leaning on outdated coding challenges that test the ability to write code by hand (quality, organization, efficiency, speed) and the direct knowledge held in someone's head (vocabulary, concepts, tools). But what we actually need to test for is much more nebulous: thought process, judgment, knowing what questions to ask, taste, context switching, and how the candidate does all of this with AI effectively. Traditional coding challenges (where you prohibit cheating as much as possible) get at some of this, but they're no longer the optimal solution. They're an old comfortable solution being applied to a more modern, complicated problem.

I said this in another comment in this thread, but the best thing to do is offer an open-ended question. One that doesn't have a concrete answer, and one they're free to answer however they wish. Like a Turing test, 5 minutes at most is enough. Want to use AI? Great. Want to curate your answer? Great. Ask them to architect something. Describe a bug and ask if it should be fixed. If they think it should, ask how they'd approach debugging. Or ask about a technical decision they've made that they're not sure was right, and have them make the case for the other choice.

The same approach works in other domains. For sales, have them sell to someone in a specific scenario. For marketing, ask about a campaign they didn't like and what they would have done differently. For accounting, ask about the most common problems they've run into with clients and internal stakeholders, and how they handled those situations.

The goal is to get them talking on video for 2 to 5 minutes about something real that matters to the role. And whenever they put in the effort to do this, give them transparency. Let them know you've personally received it and will watch it. Follow up with an actual response out of respect for their time, even if the answer is no.

To anyone worried about the time this takes: (1) it immediately weeds out low-interest candidates, (2) I'd rather watch a few-minute video than do a 30-minute phone screen based on a resume alone for someone who's obviously not a fit, and (3) multiple stakeholders can watch the same video and form a baseline for their own follow-up interviews. It makes the rest of the process better, not worse.

[jppope]

Yes. Figure out who your top performers are ask them for referrals. Some people will recommend "meh" people, but more often than not your top performers hang out with other top performers because they appreciate the same things.