

The Swyx Mixtape
Swyx
swyx's personal picks pod.
Weekdays: the best audio clips from podcasts I listen to, in 10 minutes or less!
Fridays: Music picks!
Weekends: long form talks and conversations!
This is a passion project; never any ads, 100% just recs from me to people who like the stuff I like.
Share and give feedback: tag @swyx on Twitter or email audio questions to swyx @ swyx.io
Weekdays: the best audio clips from podcasts I listen to, in 10 minutes or less!
Fridays: Music picks!
Weekends: long form talks and conversations!
This is a passion project; never any ads, 100% just recs from me to people who like the stuff I like.
Share and give feedback: tag @swyx on Twitter or email audio questions to swyx @ swyx.io
Episodes
Mentioned books

Aug 20, 2021 • 9min
Unity [Robert Cialdini]
From the Psychology Podcast again: https://www.listennotes.com/podcasts/the-psychology-podcast-with-scott-barry-10LF_aSGfEg/#search

Aug 19, 2021 • 9min
Commitment and Consistency [Robert Cialdini]
Source: https://www.listennotes.com/podcasts/the-psychology-podcast-with-scott-barry-10LF_aSGfEg/#searchSource: https://freakonomics.com/podcast/frbc-robert-cialdini/

Aug 18, 2021 • 10min
Social Proof and Scarcity [Robert Cialdini]
Listen to the Pyschology Podcast: https://scottbarrykaufman.com/podcast/robert-cialdini-the-new-psychology-of-persuasion/Steph Smith's book: Announcement Tweet: https://twitter.com/stephsmithio/status/1418320255429062661Launch Tweet: https://twitter.com/stephsmithio/status/1411047949094637569Doing Content Right: https://stephsmithio.gumroad.com/l/doing-time-right## Social ProofThe next principle is what we call social proof. The idea that one way we decide what we should do in a situation is not proof that comes from some empirical or logic. Uh, information that we've received, it comes from social information. What are the people around us like us doing in this situation that allows me to reduce my uncertainty about what I should.In this situation. Uh, so, uh, for example, uh, a study done in Beijing shows you the cross-cultural reach of this, uh, restaurant managers at one string of restaurants, uh, in, in, in China, put a little asterisk next to certain items on their menu. Uh, and each one immediately became, um, 13 to 20%, depending on the idea.More likely to be purchased. So what did the asterick stand for it? Wasn't what we normally see, which is, this is a specialty of the house, or this is the chef's selection for this evening. It was, this is one of our most popular items and each became 13 to 20% more popular for its popularity. And so. One way as a communicator of genuine information that we can give to other people is to say, we have a lot of popularity for what we are doing and give them examples of that or percentages or market share or this sort of thing.And that always is, uh, an easy way for people. To take the shortcut to yes. Oh, okay. Then I don't have to continue to calibrate it. Yeah. And, and, and, and, uh, thinking about the pros and cons of this, the majority of people like me like it. So that's a shortcut. Yes. But there's some new research. Now, my team is responsible for some of it that takes the principle of social proof to a nother level. And. It is that suppose you have a startup or you have a new product or service or an idea, a new initiative, you would like people to, to join you in. But because it's new, you can't point to social proof. The social proof is minimal. I mean, it's actually negative that a lot of people are doing it.Is there anything you can do under those circumstances? It turns out it is. Even if you don't have, even if you only have a minority or a small minority of people who have adopted it, because it's a good idea, you have to have a good idea. But if it's a good idea, you get the show, a trim who that minority position, if it's only 20% of the market, that's interested in the, if you just say 20%, that's a statistic. If six months ago, it was 10%. That's a difference and that's much better. But if you say six months ago, what was 10%? Three months ago, it was 15% this month. It's 20%. The same 20% is the end point of a trend. And people project the function of a trend into the future. So that for the first time you have the leverage of something, we didn't know the label of before future social proof in the research that we did that showed that if you give people a trend to 20%, They are more likely to say yes to it, right?Because they expect in the future, it will be more than 20%. If you've got a good idea with that kind of ability to move people upward in a trend, you'd be a fool of the influence process. Not the honestly, give them three. Data points. One data point is a statistic, two data points, a difference, three data points, a trend.## ScarcityPeople want more of those things they can have less of. And, uh, w one reason that is the case, I think applies to, uh, what Daniel condoms. It has won the Nobel prize for demonstrating. And that is the power of loss aversion, uh, as opposed to, so that we are more in his prospect theory, says the prospects of losing something are more motivating to us than the prospects of gaining that same thing under conditions of risk and uncertainty.Yeah. You know, I was on a, uh, at a conference where, um, I was in a program to be interviewed, uh, with, uh, Richard Thaler and Daniel Kahneman. And me. Right. And I said to the interviewer, you know, I feel like I'm in a Nobel Laureate sandwich.I'm the lettuce. That's hilarious. I mean, those are big hitters. Those are, those are big hitters. Uh, anyway. Yeah. Yeah, so, Hey, thank you. But, uh, what Kahneman says is this loss aversion, well, that's what scarcity, the basis of scarcity is your F if something is scarce or rare or dwindling and available availability, you're afraid that it will be lost to you.And so, yeah. That's the reason people want those things, uh, that have those characteristics. And, uh, there was a study done of, um, 6,700 E commerce websites. And they looked at AB tests within them to see, which were the factors that if they included it or withdrew, it had the made the biggest difference.In, uh, conversion from, uh, prospect to customer, it was scarcity. Here's the thing. If you could honestly say that the, we have a limited number of these at this price or with these features or with this payment plan or whatever it was, um, you got significantly more, um, uh, Conversions than any other feature they looked at at 29 of them, by the way, the next five where the other principles of influence nice that scarcity was at the top of those principles provided that it was scarcity of number, not scarcity of not limited time. So it was a limited number of items. Rather than, oh, you can only get this for a one week. If you can get it for one week, that means you can decide to get it any time in that week. If it's a limited number and there's competition for it, therefore you better move now. And that's the reason limited number is more successful in limited time off.

Aug 17, 2021 • 7min
The Power of Contrast [Robert Cialdini]
Listen to the Jordan Harbinger Show: https://www.jordanharbinger.com/robert-cialdini-a-new-look-at-the-science-of-influence/

Aug 14, 2021 • 12min
[Music Fridays] Alan Silvestri
Sources:- Back to the Future: https://www.youtube.com/watch?v=e8TZbze72Bc- Predator: https://www.youtube.com/watch?v=_Z4ll94hN_E- Death Becomes Her: https://www.youtube.com/watch?v=YsKDxRrscg4- Forrest Gump: https://www.youtube.com/watch?v=FcOt6mfjxeA- Captain America: https://www.youtube.com/watch?v=qrXwAeJ87Bk- Avengers: https://www.youtube.com/watch?v=J1VgF9ysbM8- Avengers Infinity War: https://www.youtube.com/watch?v=GY4mGgfc0Ag- Avengers Endgame (Portals): https://www.youtube.com/watch?v=F_mhWxOjxp4

Aug 13, 2021 • 9min
The Third Generation of Cryptocurrency [Charles Hoskinson]
Watch Charles' full talk: https://www.youtube.com/watch?v=Ja9D0kpksxwApologies for the bad sound, I moved house and lost my microphone for a while. I'll get it back.Response from a listener (DaveJ on our Discord):@swyx enjoyed the last mixtape about Cardano. You closed with the same thoughts that I had initially about academic peer review and how it could slow down progress and network building. I was looking at it through the lens of the usual startup advice "ship quickly and iterate to PMF". You might be coming from a different angle. Charles Hoskinson has talked about this before and here is a summary of his points that appealed to me. 1. Proof is in the pudding. Cardano's main competitors are Ethereum and Polkadot. Ethereum has been trying to do PoS a year longer than Cardano, Cardano shipped PoS first despite the fact that they did it through peer review. Polkadot copied Cardano's PoS protocol for their ecosystem. So Cardano's competitors either copied them or took longer to get to market despite the fact that they are following a startup-y "move fast and break things" mentality. 2. Code is law. Rigour is important in a way that you don't usually see in startup-land. Blockchain is immutable. Making unplanned changes is very difficult and recovering from mistakes is often not possible. For this reason, rigour is super important when designing protocols. Having hundreds/thousands of blockchain/math/CS academics read and peer review your paper provides some of that rigour. Also, because of the compositional nature of blockchain protocols, upfront investments tend to compound over time. I now think academic peer review is a net positive for Cardano (against my initial intuitions). Still though, Bitcoin and Eth were around first and have a head start in network building. Perhaps the inflection point has been hit and the winner(s) are already decided. It doesn't feel like that though. It feels like we're only getting started.Here is the source: https://www.youtube.com/watch?v=CuKhyz280zA&t=2795s

Aug 12, 2021 • 11min
Solving The Oracle Problem [Sergey Nazarov]
Listen to Software Engineering Daily: https://softwareengineeringdaily.com/2021/04/07/chainlink-connecting-smart-contracts-to-external-data-with-sergey-nazarov/TranscriptJM: Tell me a little bit more about the data sources for Chainlink. Like how do thosedata sources get vetted and how does the data make its way onto the chain?SN: Right, absolutely. So there're actually two approaches here and I think they'reboth important and the flexibility of how you acquire data is important. The first approach is thatyou have an oracle network and that oracle network is a collection of nodes that are incentivizedjust like blockchain miners and Bitcoin miners are incentivized. Those nodes are incentivized togo out and get accurate data in order to generate the most accurate, highly reliable resultpossible. In the first version of how data is put into a smart contract, this oracle network of anywhere fromseven to over 30 nodes basically goes to an API at a data provider that is considered a highquality data provider. Often that's determined by users. So users will say, “Hey, we want that data provider.” Chainlink also has a reputation system where we track how well each node, and even more and more now how each data provider is performing. And so better data providersget to continue selling their data to Chainlink networks, whereas worst data providers are kind ofnot as used by node operators because they're either not responsive or not returning the rightresults. And so there's actually a reputation system baked into Chainlink, and it's quitefascinating because the system inherently puts all of the data on chain and generates a lot ofproof about what's going on with the oracles.In any case, in the first variant of the system you can go to any data provider, you can go toreally any API in the world and you can request from it and you can come to consensus on thedata from that source assuming you can get other sources or you can come to some model ofconsensus that the user wants around that data. And that doesn't require the data provider to doanything, right? So the benefit of this system is that you have a layer of consensus and youhave a lot of proof that the data was acquired from a data provider and the data providers don'tneed to change anything about their infrastructure, right? So the data providers just continue toprovide their APIs, operate the way they have always operated and just do what they'resupposed to be doing. This is the system through which a good amount of the data is acquiredand then the data providers are more than happy to sell their data to Chainlink nodes becauseit's consumed into these applications which they're all excited about.The second version is when a data provider runs their own Chainlink node. And what thatbasically means is the data provider gets a lightweight signing appliance. They basically get alightweight signing application that allows them to connect their APIs internally to their ownofficial node. And then that node publishes a contract on-chain, and that on-chain contract is arepresentation of that data provider. So now there's an on-chain contract that's therepresentation of that data providers services. And that on-chain contract gets requests fromother smart contracts for data to be given to them because, once again, a blockchain cannottalk to an API. A blockchain has to have an oracle to speak with any API in the outside realworld. And so the second variant is where data providers that are more interested in kind of sellingtheir data to the blockchain ecosystem or more convinced about that, and we have many dataproviders already doing this live. We have data for sports events, weather events, marketevents, all kinds of things out in the real-world already live on production with data providersrunning their own production nodes. This variant allows you to get data essentially directly froman official node run by a data provider. It has the benefits of getting data directly from a dataprovider running their own node. It has the limitation in that the data provider now has to be ableto make sure that they are properly connected, that their APIs stay up according to the node andall these other kinds of nuances. The benefit that they get is they are connected to manydifferent chains all at once. And in reality this variant basically requires the data provider to wantto opt-in to some kind of infrastructure. It requires them to want to say that, “Hey, I want to kindof run a function in the cloud or I want to run some kind of node myself and I want to make atechnical investment in that.”What we found so far is that the majority of data providers just want to sell their data tosomebody and they want to provide that to an oracle network that just retrieves their data andsells that data successfully to a smart contract. There are some data providers that want to runtheir own node and we're working with a lot of those, but I think that's something that's going toevolve more slowly.[00:16:33] JM: You mentioned this reputation system for how data gets verified as quality. Howdoes that reputation system work? How do you vet and ensure quality data?[00:16:45] SN: So once again there's two levels. There's one level of the node operators andassuring that they're operating properly and then there's the level of the data providersresponding properly. In terms of the node operators, the way that the Chainlink system works isthat node operators are committing to certain service level commitments, right? They'rebasically, in many cases, on-chain committing to a certain degree of service. And they'recommitting to that because the on-chain activity that they do is immediately public to everybodyas soon as it happens. So I think the big nuance difference between a reputation system in the web world and areputation system in the blockchain world is that data is immediately available publicly. It isimmediately available for people to know that a node did not respond for a certain period oftime. And that lack of response is recorded on-chain immutably for everybody to analyze. Andwe actually have multiple ecosystem teams. We have multiple kind of block explorer-like thingsand marketplaces that are all able to analyze the same data about both node operators anddata providers.So basically the way that it looks is that the node operators are expected to perform to a certaindegree on-chain. Those expectations are clear. They are then able to perform, or in some casesif they're not able to perform, they are not able to stay on that oracle network. And then the dataproviders themselves, for the ones that run their own nodes, it becomes pretty clear what theirresponses, are and if their responses are often wrong, then you know once again that dataprovider and their node might not be used in an aggregation. They might not be applied to thataggregation.In the cases where a node operator gets data from a data source, a lot of that data is actuallymore internal to the oracle network and that data is something that's in the process of gettingpublished on chain. So there is a certain amount of insight that node operators have about theresponsiveness of different data providers and different data sources. At this point the reputationsystem extends to node operators and to the node operators that are data sources. It willcontinue and is already being extended to cover data provi...

Aug 11, 2021 • 10min
Scaling Blockchains [Vitalik Buterin]
Source: https://www.youtube.com/watch?v=XW0QZmtbjvsTranscript[00:00:00] swyx: Part two of my cryptocurrency exploration is on scaling blockchains. And I think if metallic is probably the best and most articulate person to talk about this. [00:00:09] Vitalik Buterin: There's two major paradigms for scaling blockchains. Right? As you said, we are one and layer two. And layer one, basically means, make the blockchain itself, like it capable of, uh, processing more transactions by having some mechanism by which you can do that. Despite the fact that there's a limit to the capacity of each participants in the blockchain. [00:00:29] And then what you're two says, while we're going to keep the blockchain as. But we're going to create clever protocols that sit on top of the blockchain that still use the blockchain. And it's still kind of inherit things like the security guarantees of a blockchain, but at the same time, a lot of things that are done off chain. [00:00:45] And so you get more scalability that way. Um, so. In Ethereum, the most popular paradigm for layer two is roll-ups and the most popular paradigm for layer one is charting. [00:00:54] Lex Fridman: So one way to achieve layer one scaling is to increase the block size, hence the block size wars quote unquote, and a, you actually tweeted something about. [00:01:06] Uh, people are saying that Vitalik changed his mind about in, he, he went from being a S [00:01:13] Vitalik Buterin: small. I went from being big to small. Is it big to small? [00:01:16] Lex Fridman: And, uh, but you said I've been a medium blocker all along. So maybe you can also comment on, on work, on the very basic aspect before we even get to sharding of where you stand. [00:01:27] Block [00:01:28] Vitalik Buterin: size debate. Sure. So the way that I think about the trade-off, as I think about it as a trade-off between making it easy to write to the blockchain and making it easy to read the blockchain. Right. So when I say read, I just mean, you know, have a node and actually verify it and make sure that it's correct. [00:01:43] And all of those things. And then by right. I mean, send transactions. So I think for decentralization, it's, it's important for both of these tasks to be accessible. And I think that they're like about equally important, right? If you have a. Too expensive to read, then everyone will just trust a few people to read for them. [00:01:59] And then those people can change the rules without anyone else's permission. But if on the other hand it becomes really expensive to write. Then everyone will move on to like basically second layer systems that are incredibly similar. And that takes away from, you know, decentralization and self sovereignty as well. [00:02:18] So this has been my viewpoints, like pretty much the whole time, right? It's like, you know, you need this balance and going in one direction or the other direction is very unhealthy in the Bitcoin case. Um, basically what happens was that Bitcoin originally. Like at the very beginning, it didn't really have a block size. [00:02:33] It just had an accidental block size of 32 Meg or oxides limit of 32 megabytes because that just happens to be the limit of the peer-to-peer messages. Um, but then I didn't even know that part. Yeah. But then, um, so Toshi back in 2010 was worried that even 32 megabyte blocks would be too hard to process. [00:02:51] So he, uh, put the limit down to one megabyte and, you know, I think the. You mean sneaked in there? Yeah. Just like made an update to the Bitcoin software that made blocks bigger than one. I think it's a million bytes invalid. And I think the impression that most people had at the time is that, you know, this is just a temporary safety measure and overtime, you know, as we become more confident in the software, that limit would be like raised some, uh, somewhat. [00:03:21] Um, but. That then when the actual usage of the blockchain started going up, and then it started going up first to 100 kilobytes per block, then to two 50 kilobytes per block, then to 500 kilobytes per block. Now let me know there started a kind of coming out of the woodworks, this opinion that like, no, that limit should just not be increased. [00:03:42] And, and, you know, then there are all of these attempts at compromising, right? Um, No first, there was like a proposal for 20 megabyte blocks. Then there was the two for eight proposal, which is, um, a bit ironic because the 2 48 proposals started off being like a small block negotiating position. But then when the big law people came back and said like, Hey, why aren't we aren't we going to do this? [00:04:05] They're like, oh no, no, no, we don't want them. We don't want the block size increases anymore. Uh, so, you know, there were these two different positions, right? The small blockers, I think they valued one megabyte blocks for two reasons. One is that they just like really, really believe in the importance of being able to read the Chan. [00:04:22] But two is that a lot of them really believe in maintaining this norm of never hard forking. Right? So the difference between a hard fork and a soft fork is basically that Ian, a soft fork, um, blocks that were. Any block that's valid under the new rules that were still valid under the old rules. So if you have a client that verifies according to the old rules, then you'll still be able to accept the chain that follows the new rules. [00:04:48] Whereas with a hard fork, like you have to update your code in order to stay on the chain. Uh, huh? They have this belief that it'll soft forks are kind of either less coercive than hard forks, which by the way, I completely disagree with, um, I actually think soft forks are more coercive because like basically they force everyone who disagrees to sort of go along by default. Rollups [00:05:11] Vitalik Buterin: So this might be a good time to talk about roll-ups. What [00:05:13] Lex Fridman: are roll-ups? Okay. Now we're moving into layer [00:05:16] Vitalik Buterin: two ideas. So the idea behind a roll up is basically that. So instead of. Just publishing transactions directly on chain and having everyone, you know, do all of the checking of those transactions. Um, what you do is you create a system where users send to their transactions to some central party called an aggregator. [00:05:44] And like, well, theoretically, you could have a system where like the aggregator, so which is arounds or where anyone can be an aggregator. So, you know, it's still like permission to us to send things. Um, then what the aggregator does is. Strip out all of the transaction data that like is not relevant to helping people update the state. [00:06:03] So when I say the state, this is like, this is a very important, it's kind of technical term from blockchains. I mean like account balances, code, um, like things that are. Memory internal memory of smart contracts. So like basically everything, the blockchain actually has to keep track of it. Right. So ju you're just still put in, um, you take it, oh, these transactions strip out all the data. ...

Aug 10, 2021 • 12min
Ethereum 2.0 [Danny Ryan]
Source: https://www.listennotes.com/podcasts/epicenter-learn/danny-ryan-ethereum-dNF42A7tuiR/ NotesEth 2Beacon chain went live in Dec 20204.5m eth locked Each validator 32 ethValidator job: randomness generation, finality, validator level transactions (attestations, deposits, onboarding)The MergeEth1 has an application layer and a thin consensus layer (PoW)Post merge - beacon chain will drive applications going forwardEth2 keeps everything about Eth1 clients and swaps out the consensusWhy not fork?difficulty bombapplications atop Eth are much more substantial nowTranscript [00:00:00] swyx: This week, we're diving into Ethereum and other cryptocurrencies. Don't worry, this isn't about to become a cryptocurrency podcasts, but I still think it's a pretty interesting topic. And there's a lot of interesting research that is not just price hype, but actually serious innovation in terms of distributed systems and crypto economics. [00:00:19] And I've been storing up a bunch of podcasts related to that, that I figured I would get through it now in one block. [00:00:25] So today I wanted to feature this conversation on the epicenter podcast with Denny Ryan, Danny is from the foundation and works on Eve too. And he explains what these two is what the merge is going to be like as well as what the incentives are for the community to stick together rather than have hard fork like they did last time with Eth classic. [00:00:43] Danny Ryan: Eth2 is a series of major consensus upgrades for Ethereum aimed to make the protocol more secure, more sustainable, and more scalable. And at the core of that is the move from proof of work consensus to a proof of stake consensus. [00:01:00] So instead of securing the network with mining hardware and energy consumption, securing the network with the tokens itself the ether. And so at the core of that is the bootstrapping and the creation of this new consensus mechanism. And what as you mentioned, is live today is what we call phase zero. [00:01:18] And that went live in December of 2020. And that was really the bootstrapping of this new proof of stake consensus mechanism. That is called the beacon chain. So in December tons of Ethereum community members and different institutions put a bunch of ether as capital and collateral into what we call the deposit contract and kickstarted this new consensus mechanism called the beacon chain. [00:01:42] The beacon chain exists in parallel to the current theater network. So in parallel to the proof of work network, which is still securing all of the assets and applications and contracts and accounts today. So we have on the one hand and the proof of work network chugging along and on the other hand, this new consensus mechanism called the beacon chain existing in parallel to this building and securing it. [00:02:07] I think today there's something like 4.5 million ether locked and secured in this chain. I don't know what that's worth today. It depends on the minute and the hour. This thing exists, this thing finalizes itself, this thing builds itself. But ultimately what it does is it just builds and secures itself. [00:02:26] And this is by design. This is an iterative path to get rid of the proof of work and to move Ethereum to this new consensus mechanism, obviously it, there may not as used by tons of people secure as tons of value. And there's a lot at stake in this operation. But what we've done is built it in parallel vetted it in production dozens, tons of tests live. [00:02:49] And now what we're working on is actually the deprecation of the proof of work consensus mechanism in favor for the slide proof of stake consensus mechanism. So that's where we're at today. There is a proof of stake, consensus mechanism, bootstrapped live securing tons of value, but really just securing itself in isolate. [00:03:07] Martin Köppelmann: Then let's deep dive into what it exactly does. So, right now it comes to consensus on what? [00:03:13] Danny Ryan: It comes to consensus on itself and it's by itself. What I mean is the proof of stake, consensus mechanism and all of the little gadgets and things in it. So it has a validator set. Each validator is worth approximately 32 eith. [00:03:26] So there's something like 140,000 validator entities in this consensus. Each one of them has like its own little state. It has its balance. It has duties. It has like a job at any given time. It has randomness generation. It has information about finalities. So which portions of the chain are finalized and will never be reverted. [00:03:47] And it has a lot of just various accounting between finality and kind of the head of the chain. So there's a number of operations related to the functionality of this chain. And those operations are what we call validator level transactions. So system level trends. And really what it does is there's a core operation called attestations where validators are constantly signaling what they see as the head of the chain and what they see as their local state of the world. [00:04:14] And they use these messages to come to consensus with each other and ultimately drive this core like system layer of the chain. There's some other operations related to validate or activity like deposits, onboarding, new validators exits leaving the validator set, and a couple of other things. [00:04:30] So really it's like this, it's a proof of stake system and there's a lot of different accounting, different little operations going on and it builds and it comes to consensus on itself. So The Merge[00:04:39] Friederike Ernst: maybe let's talk about the merge for a little bit. There would be the merge and the merge with merge each one into the beacon chain. So how exactly does it happen? When is it going to happen? I imagine either one in east who have separate states, how is that handled? How do you make them congruent? [00:04:55] Danny Ryan: So let's think about what Eth1 is. Eth1 is, and this is a construction for each. One's a lot of things, and there's a lot of different ways to think about it. [00:05:04] But for the purposes of the merge, we can think about it in two layers, we have this application layer or this execution layer where all of the users hang out. It's where all the applications are. It's where the user layer state is. It's where transactions are being processed. Right. It's really like what I, as an end user care about, I care about, you know, my unit swap trades and that kind of stuff. [00:05:27] And then you have this thin purple work consensus module that's driving. It's really like providing the services, providing the quality the it's riding the service to this execution layer. It's the cradle for blocks. It's providing guarantees about reorgs and different things like that. [00:05:42] And what we have is really these two layers. We have the preferred consensus layer providing the application layer to services and to users. And then what we've bootstrapped in production today is the beacon chain, which is a proof of state...

Aug 8, 2021 • 41min
[Weekend Drop] What We Know We Don't Know — Hillel Wayne
An exploration of Empirical Software Engineering. We know far less than we care to admit, and the stuff we do know is boring but definitely worth investing in.See talk slides, referenced papers, and video: https://hillelwayne.com/talks/what-we-know-we-dont-know/