LinearB
LinearB
  • Видео 115
  • Просмотров 81 717
13.3% of Your PRs Are Bot-Created – Now What? [SDLC Impact Workshop]
Bot-generated pull requests are on the rise (13.3% of all PRs are bot-created today), and they are creating a unique impact on your SDLC.
Engineering orgs who create a system for managing bot-generated Pull Requests are able to reduce their team's entire Pull Request review load by over 6%, while also making drastic improvements in their security and compliance posture.
In this 45-minute workshop, you’ll discover insights like:
54% of bot PRs are deleted without action
96.18% of all bot-created PRs are not linked to a PM tool
12.27 days is the average vulnerability time for bot-created PRs
Просмотров: 194

Видео

Software Engineering Intelligence with LinearB
Просмотров 27 тыс.3 месяца назад
Software engineering leaders create the value that drives revenue. To succeed, they have to fulfill a dual mandate: maximize operational efficiency and align their resources to business goals. Answering the dual mandate begins with LinearB's software engineering intelligence solutions. Combining software delivery insights, engineering investment visibility, and workflow automation, LinearB help...
What is Software Engineering Intelligence
Просмотров 1073 месяца назад
Dan Lines and Conor Bronsdon explains what is software engineering intelligence. Subscribe to our Newsletter ►► linearb.io/blog/#subscribeformore #engineeringleadership #trending #engineeringteams #startup #enterprise #productivity #stakeholders #planning #software #engineering #intelligenceplatform #softwareengineering #softwareengineeringintelligence
Why Software Engineering Intelligence is Important for Engineering Teams
Просмотров 153 месяца назад
Dan Lines and Conor Bronsdon share their opinion about why software engineering intelligence is important for engineering teams. Watch the video to learn more about it Subscribe to our Newsletter ►► linearb.io/blog/#subscribeformore #engineeringleadership #trending #engineeringteams #startup #enterprise #productivity #stakeholders #planning #software #engineering #intelligenceplatform #engineer...
What Makes a Great Software Engineering Intelligence Platform
Просмотров 293 месяца назад
Join Dan Lines and Conor Bronsdon in a discussion about what makes a great software engineering intelligence platform. Subscribe to our Newsletter ►► linearb.io/blog/#subscribeformore #engineeringleadership #trending #engineeringteams #startup #enterprise #productivity #stakeholders #planning #software #engineering #intelligenceplatform
Software Engineering Intelligence: Exposed & In Action
Просмотров 5433 месяца назад
In this 35-minute session, you’ll gain a comprehensive understanding of Software Engineering Intelligence (SEI) capabilities and see real-world examples of how these tools are being implemented to rapidly accelerate developer productivity. We dive deep into how engineering leaders are using SEI to take on: Developer Productivity - accelerating developer output Profitable Engineering - the data ...
How to Set Goals to Achieve Your Dual Mandate
Просмотров 325 месяцев назад
Yishai Beeri CTO at LinearB and Dan Lines, COO and co-founder at LinearB, discuss about the advantages of a bottom-up approach, which empowers teams to set their own goals and metrics tailored to their specific ways of working. This fosters autonomy, accountability, and a positive culture. You'll also discover when a top-down approach is beneficial, such as focusing on company-wide initiatives ...
The CTO Board Deck Template and How to Present Engineering Data to Your Board
Просмотров 1125 месяцев назад
The CTO Board Deck Template and How to Present Engineering Data to Your Board
Starting Your Engineering Metrics Program
Просмотров 8405 месяцев назад
Starting Your Engineering Metrics Program
Modern Practices for Goal Setting in Software Engineering
Просмотров 8836 месяцев назад
Modern Practices for Goal Setting in Software Engineering
How Syngenta Built a Robust and Transparent Career Ladder for Engineers
Просмотров 377 месяцев назад
How Syngenta Built a Robust and Transparent Career Ladder for Engineers
Improving Cycle Time by Unblocking Bottlenecks in QA and Collaboration
Просмотров 667 месяцев назад
Improving Cycle Time by Unblocking Bottlenecks in QA and Collaboration
Measuring Impact: GenAI Code
Просмотров 6008 месяцев назад
Measuring Impact: GenAI Code
DORA & LinearB present: Insights into the 2023 Accelerate State of DevOps Report
Просмотров 80011 месяцев назад
DORA & LinearB present: Insights into the 2023 Accelerate State of DevOps Report
2023 Engineering Benchmarks Report Webinar
Просмотров 854Год назад
2023 Engineering Benchmarks Report Webinar
How We Cut Our CI Pipeline In Half
Просмотров 203Год назад
How We Cut Our CI Pipeline In Half
Programming Languages: Longest vs Shortest Lifespans
Просмотров 78Год назад
Programming Languages: Longest vs Shortest Lifespans
gitStream Now Estimates How Much Time Your Team is Saving
Просмотров 221Год назад
gitStream Now Estimates How Much Time Your Team is Saving
Improve: Using Engineering Metrics to Accelerate & Report Roadmap Delivery
Просмотров 664Год назад
Improve: Using Engineering Metrics to Accelerate & Report Roadmap Delivery
Why the Best Engineering Teams Keep Their PR Size Small
Просмотров 151Год назад
Why the Best Engineering Teams Keep Their PR Size Small
Automate: Pre merge Workflow Automation for Dev Efficiency
Просмотров 515Год назад
Automate: Pre merge Workflow Automation for Dev Efficiency
The Data Behind LinearB's Compounding Efficiencies Research
Просмотров 33Год назад
The Data Behind LinearB's Compounding Efficiencies Research
Benchmark: Building an Engineering Metrics Function
Просмотров 1,6 тыс.Год назад
Benchmark: Building an Engineering Metrics Function
The Future of Ops is Platform Engineering
Просмотров 205Год назад
The Future of Ops is Platform Engineering
gitStream Worshop: How to Apply a Rule - Approving Safe Changes
Просмотров 82Год назад
gitStream Worshop: How to Apply a Rule - Approving Safe Changes
Why Syngenta Chose LinearB Over Competitors
Просмотров 160Год назад
Why Syngenta Chose LinearB Over Competitors
What is Cycle Time (aka Lead Time for Changes)?
Просмотров 199Год назад
What is Cycle Time (aka Lead Time for Changes)?
What is Deployment Frequency?
Просмотров 139Год назад
What is Deployment Frequency?
What is Mean Time to Restore (MTTR)?
Просмотров 266Год назад
What is Mean Time to Restore (MTTR)?
What Is Change Failure Rate (CFR)?
Просмотров 199Год назад
What Is Change Failure Rate (CFR)?

Комментарии

  • @MarcoSeegloc
    @MarcoSeegloc 7 дней назад

    I'm working on People's credit files. Is there a bot to automatically put these PRS on the files instead of manually putting them in

  • @topsy_kreds
    @topsy_kreds 2 месяца назад

    Thank you, it was very interesting

  • @johnnyz9368
    @johnnyz9368 5 месяцев назад

    Promo-SM 😄

  • @briancolfer415
    @briancolfer415 6 месяцев назад

    How to determine if a particular release produced a failure can be ambiguous. It may be a latent feature or a defect that is not noticed for weeks.

  • @briancolfer415
    @briancolfer415 6 месяцев назад

    The recommendateion for complete and thorough code reviews is both very specific if describing the Formal Inspection Process or very ambiguous.

  • @bernhardkrickl5197
    @bernhardkrickl5197 6 месяцев назад

    Guess what? At some point to further reduce PR size and get deeper reviews in a short time, you just switch to pair programming and push to mainline.

  • @briancolfer415
    @briancolfer415 6 месяцев назад

    Lower MTTR is correlated with more work on features and less Yak shaving and bugfixes.

  • @mosescarayol5316
    @mosescarayol5316 7 месяцев назад

    Thank you for this video. A Junior software engineer

    • @LinearBInc
      @LinearBInc 6 месяцев назад

      So glad you found it helpful!

  • @antonprokhorov6185
    @antonprokhorov6185 7 месяцев назад

    I once heard an interesting point while interviewing Principal Engineer - big PRs for sure might bring troubles and to be very complex to review. But very small PRs are also a signal - in particular scenario from that Engineer - it was actually a sign of some level of toxicity within the team, where they were so constantly throwing review comments that weren't actually helping to make the code better, that irritated devs started doing very atomic PRs thinking "ok now you bastard won't tell me a single word, finally"

  • @Denzelzeldi
    @Denzelzeldi 8 месяцев назад

    06:59 A lot of organizations are being very fixated on speed and just looking at speed right like coding time cycle time all of those things and it definitely needs to be balanced with with quality indicators. For example developers might actually write more tests with the time that they're saving which increases the the code coverage but would then also dampen the impact on speed. 07:28 You might you might even get slower [using GenAI in development] if developers get more removed from the code because they didn't write it all, so their debugging time might get longer as at the same time there's risks to quality. There's there's lots been written about the quality risks of [GenAI] coding assistance. 07:55 It is important to not overdo it. I've seen one organization that very strongly looked at adoption and [had] very high expectations from the leadership about the lift that this is going to give in terms of speed so putting very high expectations on developers to use these tools to become a lot faster and putting a lot of pressure. Adoption should be neutrally monitored, like are people actually using it because it's useful and not put on an expectation beforehand of how much lift it's going to get them... obviously if you're if you stated the goal everyone should be using this then you probably pushing people in the in the wrong way 08:58 When measuring benefits it's also important not to have a fixed [goal] like this has to be 30% or more [saving]. The industry doesn't know yet actually what the benefits are how they look at in numbers and how they balance with risks. 21:45 As we're using coding assistance and potentially get higher coding throughput to create more code per time unit, if we look at our software delivery process then we have this one part of our process of our system where we're increasing the throughput. If some people are maybe like familiar with systems thinking, what will happen if we just increase throughput in one of you know one of the parts of our system? We'll get bottlenecks. In a lot of organizations code review or pull request review is already one of the bottlenecks, so what will happen if you create more code? 22:38 At thoughtworks were're big fans of pair programming as a tool to improve team collaboration and also team flow right and you know this could actually be like one of the things to also alleviate this this bottleneck, to have pairs that work with the coding assistant. Almost like a trio programming. 23:08 GitHub calls co-pilot your "AI pair programmer" which which annoys me a lot I have to say, you know because pair programming is about is a team practice to make the team better. 27:49 We are in a hype cycle right now at the peak of inflated expectations and the higher that peak is the bigger the hangover will be and the more people are going to say quickly oh my expectations were so high they were disappointed. So I think the key here is to adjust our expectations because this is definitely going to be useful in my opinion and going to be here to stay and we just have to figure out how to properly use it so that it. 29:01 I can also confirm I haven't seen anything really impressive there yet in that area so often when I would ask a coding assistant for example how can I improve this code or something, it gives me like, you could can add error handling, you know like very like generic kinds of things almost like a checklist of like a a newbie code reviewer. There's definitely still potential maybe it also can still get better. 43:27 I've been coding for more than 20 years at this point and even today you just go on the internet and you copy and paste things when you don't know yet what to do and you stitch them together and you just want to get it to work once. So I think in a way we've we've all been doing this right, there's just a tool now that can potentially make us even faster at doing that and that might make the problem worse. But I also have faith that maybe we will all adapt to this and we will still put our hands on the hot stove and get burned and then learn from that. So those cycles will still be the same so I'm trying to be not too cynical about it.

  • @krumbergify
    @krumbergify 10 месяцев назад

    Really good presentation and Q/A. I read the report(s) but this gives much more flesh on the bones. To be honest I thought that DevOps was just another bussword but after learning more I really like what it represents. It aligns very well with all my experiences as a developer.

  • @LucianoBargmann-d5v
    @LucianoBargmann-d5v 10 месяцев назад

    How do I access these reports?

  • @DevInterrupted
    @DevInterrupted 11 месяцев назад

    Killer event!

  • @harriottgaige5871
    @harriottgaige5871 Год назад

    💃 *Promo sm*

  • @bching2002
    @bching2002 Год назад

    I really like this video, it not just helps me to under DORA metrics but also how to implement it.

  • @agatasobasikem8578
    @agatasobasikem8578 Год назад

    Great summary! Thank you that was exactly what I was looking for.

  • @kroy1570
    @kroy1570 Год назад

    sorry not even understanding the post above. can you dumb it down so a Program Manager can understand?

  • @paul4ashraf
    @paul4ashraf Год назад

    Thank you for this! Sorry I missed the webinar

  • @Tristan-mr3pk
    @Tristan-mr3pk Год назад

    To me the value of DORA comes when paired with the capability model and the 24 capabilities from Accelerate. Without that context I think DORA looses its meaning.

  • @aliasuser958
    @aliasuser958 Год назад

    Lots of really good nuggets here!

  • @celestinaliebrecht4679
    @celestinaliebrecht4679 2 года назад

    promosm

  • @alphonsokirk8340
    @alphonsokirk8340 2 года назад

    𝔭𝔯𝔬𝔪𝔬𝔰𝔪 😜