Younes Hairej – What's Your InnerSource Worth #InnerSourceSummit2025

Younes Hairej – What's Your InnerSource Worth? #InnerSourceSummit2025 🔗 **Source:** [Younes Hairej – What's Your InnerSource Worth? #InnerSourceSummit2025](https://www.youtube.com/watch?v=WVWsqpgI1Ik&pp=0gcJCSkKAYcqIYzv) > [!note]+ Document Notes > tags: [inner-source, roi-measurement, cloud-native] > author: Younes Hairej > source: InnerSource Commons > reference: https://www.youtube.com/watch?v=WVWsqpgI1Ik > date created: 2025-01-05 14:30 > > # 🏷️ Title: What's Your InnerSource Worth? Measuring ROI with Frameworks and Real Results >  ## 🧰 Action Inbox - [H1] Build live maturity assessment tool for InnerSource ROI — 15:30 #measurement - [H2] Apply Wardley mapping to decide build/share/buy strategies — 08:45 #strategy - [H3] Start small with one shared capability used by multiple teams — 24:15 #implementation ## 🧭 Table of Contents - [📝 Summary](#-summary) - [📖 Main Content](#-main-content) - [🗒️ Notes](#️-notes) - [📚 References](#-references) - [🗣️ Paraphrase](#️-paraphrase) - [📰 Newsletter](#-newsletter) - [✅ Action Items](#-action-items) - [🧪 Hypotheses](#-hypotheses) - [📊 Methodology](#-methodology) - [❓ Questions](#-questions) - [🔮 Future Research](#-future-research) - [💡 Implications](#-implications) - [🧠 Learning Styles Assessment](#-learning-styles-assessment) - [📊 Accessibility Assessment](#-accessibility-assessment) - [🌍 DEIB Assessment](#-deib-assessment) - [✅ Logical Validity](#-logical-validity) - [🛡️ DARVO Analysis](#-darvo-analysis) - [🎯 Conclusion](#-conclusion) ### 🔗 References - [InnerSource Commons Summit 2025](https://innersourcecommons.org/) - [Alcomo Assessment Tool](URL_via_QR) ## 📝 Summary - Younes Hairej presents a framework for quantifying InnerSource ROI using data-driven assessment tools rather than philosophical arguments - Key challenge: Traditional industrial measurement systems fail to capture collaboration benefits, knowledge sharing, and network effects - Solution combines Wardley mapping for strategic decisions (build/share/buy) with live maturity assessments that translate engineering signals into executive narratives - Real case study from 180-year-old Japanese textile company Toyoshima shows 70% cycle time reduction applying InnerSource principles to design workflows - Bottom line: InnerSource creates measurable business value when you know what to measure and have frameworks to capture collaborative maturity ## 📖 Main Content Traditional ROI measurement fails InnerSource because our "measurement DNA is still industrial" - built for output rather than collaboration. While organizations excel at counting lines of code or uptime, they struggle to quantify reuse, learning, and network effects between teams. This creates a gap when executives ask for numbers to justify InnerSource investments. The challenge has three dimensions: benefits are multi-dimensional and don't show up in linear KPIs; returns are delayed and compound over time like interest; and there's no standard framework making results incomparable across organizations. Even DORA metrics, while valuable for delivery frequency, don't measure collaboration maturity or knowledge flow. Hairej proposes using Wardley mapping as a strategic decision-making framework to determine what to build internally (competitive advantage), what to share through InnerSource (custom but common needs), and what to buy (commodities). For AI implementations, this means building custom models internally, sharing orchestration tools and benchmarking frameworks through InnerSource, and buying generic LLMs and cloud infrastructure. The solution includes a live cloud-native maturity assessment tool that converts engineering signals into executive narratives, providing specific scores, risk ratings, cost savings estimates, and benchmarking against industry peers. This transforms InnerSource from philosophical concept to measurable business case with actionable roadmaps. ## 🗒️ Notes #### ⏱️ [00:00](https://youtu.be/WVWsqpgI1Ik?t=0) — [H1] Speaker introduction and company background - Key idea: Younes Hairej, CEO of Alcomo, brings finance and engineering perspective to InnerSource ROI - Evidence: "Started as software engineer at Sony Ericsson, worked at Morgan Stanley for seven years, then CTO at fintech" #### ⏱️ [02:30](https://youtu.be/WVWsqpgI1Ik?t=150) — [H2] The core challenge of proving InnerSource value - Key idea: Leaders believe in InnerSource but struggle to provide CFO/CIO with concrete numbers - Evidence: "Every leader I speak to believes in inner source in practice or principle but when CFO and CIO ask about numbers there's silence" #### ⏱️ [04:15](https://youtu.be/WVWsqpgI1Ik?t=255) — [H2] Industrial measurement DNA fails collaboration - Key idea: Current measurement systems built for output, not collaboration, missing reuse and network effects - Evidence: "Our measurement DNA is still industrial. We're great at counting lines of code or uptime, but terrible at quantifying reuse, learning, or network effects" #### ⏱️ [05:45](https://youtu.be/WVWsqpgI1Ik?t=345) — [H3] Three reasons InnerSource ROI is difficult - Key idea: Multi-dimensional benefits, delayed returns, and lack of standard frameworks create measurement challenges - Evidence: "Benefits are multi-dimensional... returns are delayed... there's no standard framework" #### ⏱️ [07:30](https://youtu.be/WVWsqpgI1Ik?t=450) — [H2] DORA metrics limitations for collaboration - Key idea: DORA metrics measure delivery frequency but not collaboration maturity or knowledge flow - Evidence: "DORA tells you how fast code moves, but not how knowledge flows" #### ⏱️ [08:45](https://youtu.be/WVWsqpgI1Ik?t=525) — [H1] Wardley maps as strategic framework - Key idea: Use Wardley mapping to visualize where collaboration should happen and decide build/share/buy strategies - Evidence: "Wardley maps help. They give us a way to visualize where collaboration should happen and why" #### ⏱️ [11:20](https://youtu.be/WVWsqpgI1Ik?t=680) — [H2] AI example of build/share/buy decisions - Key idea: Build custom AI models, share orchestration tools via InnerSource, buy generic LLMs and infrastructure - Evidence: "Custom AI model - build internally. AI orchestration, prompt engineering - inner source sweet spot. Generic LLMs, cloud infrastructure - buy the API" #### ⏱️ [13:45](https://youtu.be/WVWsqpgI1Ik?t=825) — [H1] Strategic thinking framework - Key idea: InnerSource is decision-making framework, not just practice - know what to build, share, and buy - Evidence: "Inner source is not about doing everything together. It's about knowing where collaboration brings the most value" #### ⏱️ [15:30](https://youtu.be/WVWsqpgI1Ik?t=930) — [H1] Live maturity assessment tool - Key idea: Cloud-native assessment tool converts engineering signals into executive narratives with specific metrics - Evidence: "47% cloud native maturity, nine critical issues, medium risk rating, 20K potential cost savings, 2-3 months to next level" #### ⏱️ [17:15](https://youtu.be/WVWsqpgI1Ik?t=1035) — [H2] Industry benchmarking and gap analysis - Key idea: Tool provides industry comparison and specific improvement roadmap, not just scores - Evidence: "Team ahead of 39% of organizations but still far from leaders. Shows exactly where gaps are: culture, CI/CD, architectural decomposition" #### ⏱️ [19:00](https://youtu.be/WVWsqpgI1Ik?t=1140) — [H1] Toyoshima textile company case study - Key idea: 180-year-old Japanese textile company applied InnerSource principles beyond engineering - Evidence: "Cut pattern to client cycle by 70%, sample testing from three weeks to couple hours, 60% fewer physical samples" #### ⏱️ [21:30](https://youtu.be/WVWsqpgI1Ik?t=1290) — [H2] InnerSource principles applied to design - Key idea: Shared digital platform enables real-time collaboration between designers, clients, and sales teams - Evidence: "Designers can design, recolor, iterate instantly. Every fabric pattern, color palette, design variation stored and reusable" #### ⏱️ [22:45](https://youtu.be/WVWsqpgI1Ik?t=1365) — [H1] AI-native future and InnerSource foundation - Key idea: InnerSource creates structured collaboration data that AI systems need for reasoning - Evidence: "AI agents can review PRs, recommend reuse, autogenerate reports because they understand your collaboration graph" #### ⏱️ [24:15](https://youtu.be/WVWsqpgI1Ik?t=1455) — [H1] Monday morning practical steps - Key idea: Start small with one shared capability, measure usage and contributions, quantify opportunity cost - Evidence: "Pick one shared capability used by multiple teams. Track usage, contributions, reuse. Calculate opportunity cost of rebuilding" ## 📚 References - [InnerSource Commons](https://innersourcecommons.org/) - [Wardley Mapping](https://wardleymaps.com/) - [DORA Metrics](https://dora.dev/) - [Alcomo Cloud-Native Assessment Tool](QR_CODE_REFERENCE) ## 🗣️ Paraphrase - Organizations struggle to prove InnerSource value because traditional metrics focus on individual output rather than collaborative outcomes, missing the compound benefits of knowledge sharing and reuse - Strategic frameworks like Wardley mapping help determine what capabilities to build internally for competitive advantage, share through InnerSource for common custom needs, and buy as commodities - Live assessment tools can translate engineering collaboration signals into executive business cases with specific metrics, benchmarks, and improvement roadmaps rather than philosophical arguments ## 📰 Newsletter **Measuring InnerSource ROI: From Philosophy to Proof** Struggling to justify your InnerSource investments to executives? You're not alone. Most measurement systems focus on individual output rather than collaborative value, making it nearly impossible to quantify the real benefits of knowledge sharing and reuse. The breakthrough comes from combining strategic frameworks with data-driven assessment. Use Wardley mapping to decide what to build (competitive advantage), share (common custom needs), and buy (commodities). Then implement live maturity assessments that convert collaboration signals into executive narratives with concrete metrics and improvement roadmaps. One Japanese textile company reduced their design cycle by 70% by applying these principles beyond engineering to creative workflows. The key? Start small, measure systematically, and quantify opportunity costs. Ready to transform InnerSource from theory to measurable business value? Resources: [InnerSource Commons](https://innersourcecommons.org/), [Wardley Mapping](https://wardleymaps.com/), [DORA Metrics](https://dora.dev/) ## ✅ Action Items #### DevRel - Developer advocacy: Create InnerSource ROI measurement workshops for engineering leadership, include live assessment demos - Education: Develop curriculum on Wardley mapping for technical decision-making, build/share/buy frameworks - Developer experience: Build InnerSource contribution tracking dashboards, integrate with existing development workflows - Developer marketing: Create case study content showing quantified InnerSource benefits across industries - Community management: Facilitate InnerSource measurement standards discussions, collect community assessment frameworks #### OSPO - Policy & Governance: Establish InnerSource ROI reporting requirements, create contribution measurement policies - License Compliance: Track internal project reuse patterns, identify compliance implications of shared components - Security Management: Assess security posture of internal shared repositories, vulnerability disclosure for InnerSource - Software Inventory: Catalog internal shared components in SBOM, track dependency relationships - Developer Support: Provide InnerSource maturity assessment training, consultation on measurement frameworks - Community Engagement: Coordinate with InnerSource Commons on assessment tool development, contribute measurement research - Strategic Alignment: Define InnerSource success KPIs aligned with business objectives, quarterly ROI reporting #### Community - Maintainers: Develop InnerSource project health metrics, governance templates for shared internal projects - Contributors: Create onboarding programs for internal project contributions, recognition systems - Sponsors: Establish transparent budgets for InnerSource initiatives, impact measurement and reporting - Ecosystem: Facilitate cross-team collaboration patterns, shared component discovery platforms #### WordPress - Core: Evaluate InnerSource patterns for core development, contribution workflow improvements - Core Performance: Share performance tooling and benchmarking frameworks across teams - Core AI: Apply build/share/buy framework to AI integration decisions, shared AI tooling development - Community: Develop InnerSource measurement tools for WordPress community projects - Training: Create InnerSource collaboration curriculum, measurement framework education - Documentation: Document InnerSource patterns and ROI measurement approaches for WordPress ecosystem #### The WPCC - Programs: Design fellowship programs around InnerSource practices, ROI measurement training - Projects: Fund InnerSource assessment tool development, collaborative measurement research - Funding: Establish grants for InnerSource maturity initiatives, matched funding for measurement tools #### FAIR - Technical independence: Ensure InnerSource assessment tools remain vendor-neutral, open measurement standards - Policies: Develop transparent InnerSource funding criteria, anti-capture policies for shared development - Governance artifacts: Create InnerSource governance templates, measurement framework standards ## 🧪 Hypotheses - Organizations with structured InnerSource measurement frameworks achieve 30%+ higher collaboration ROI than those using traditional metrics - Wardley mapping applied to technology decisions reduces build vs buy errors by 50% and increases strategic alignment - Live maturity assessment tools increase executive support for InnerSource initiatives by providing quantified business cases - InnerSource principles applied beyond engineering (design, operations, content) generate measurable productivity gains ### 📊 Methodology - Survey organizations using InnerSource measurement tools vs traditional metrics, compare collaboration outcomes and ROI - Longitudinal study of teams adopting Wardley mapping for technical decisions, track strategic alignment and resource allocation - A/B test executive presentations with philosophical vs data-driven InnerSource business cases, measure funding approval rates - Case study analysis of InnerSource application beyond engineering, quantify productivity and quality improvements ### ❓ Questions - How do we standardize InnerSource ROI measurement across different organizational contexts and industries? - What collaboration signals best predict long-term InnerSource success and sustainable community growth? - How can AI amplify InnerSource measurement and decision-making without losing human collaborative elements? ### 🔮 Future Research - Development of industry-standard InnerSource maturity assessment framework with validated metrics - Integration of AI agents for automated collaboration pattern analysis and reuse recommendations - Cross-industry study of InnerSource application beyond software engineering domains ### 💡 Implications - Practice: Shifts InnerSource from cultural initiative to measurable business practice with clear ROI frameworks - Policy: Requires establishment of InnerSource measurement standards and contribution tracking policies - Security: Creates need for security assessment of internally shared components and collaboration platforms - Education: Demands new curriculum combining technical collaboration skills with business measurement frameworks - Funding: Enables data-driven budget allocation for InnerSource initiatives based on quantified benefits ### 🧠 Learning Styles Assessment Reading level estimate: Flesch-Kincaid Grade Level 12 #### 👀 Visual learners - Present: Wardley mapping diagrams, assessment dashboard screenshots, before/after transformation visuals - Improve: Additional architecture diagrams showing collaboration flows, ROI visualization charts #### 🔊 Aural learners - Present: Conference presentation format with speaker narration - Improve: Podcast-style discussion of case studies, audio summary of key measurement frameworks #### 🗣️ Verbal learners - Present: Clear definitions of InnerSource terminology, business case analogies, strategic frameworks - Improve: Story-driven case study narratives, comparison tables for different measurement approaches #### 🧩 Kinesthetic learners - Present: Assessment tool interface, QR code for hands-on access, practical Monday morning steps - Improve: Interactive assessment walkthrough, step-by-step measurement implementation checklists #### 🧠 Logical learners - Present: Structured framework progression, cause-effect relationships in ROI measurement, systematic methodology - Improve: Decision trees for build/share/buy choices, logical flowcharts for measurement implementation #### 🧑‍🤝‍🧑 Social learners - Present: Conference presentation format, community collaboration examples, cross- --- ## Full Transcript [00:06] Um so my name is Ununice. I'm the [00:07] founder and CEO of Alcomo. Um I'm based [00:11] in Japan. So I lived in Japan [00:14] um more than half of my life. Um I [00:17] started as a software engineer at Sonia [00:19] Ericson. Um after that I moved to [00:23] finance. Um I worked at Morgan Stanley [00:26] for seven years. um then was the CTO and [00:30] group CIO of um Infas which is a a [00:33] fintech company um and then I started [00:36] Alcom. So that's u a quick journey about [00:39] um about myself. Um so a little bit [00:42] about Alcom, [00:44] we operate at the intersection of um [00:48] cloud cloud native and AI. Um so we [00:51] we're an AWS partner um an inner source [00:54] partner as well. Um we're a cloud native [00:57] um and Linux Foundation member and we um [01:02] we help companies um build and operate [01:05] their software through our services and [01:08] uh and products and uh one of our [01:10] products is AI ops that we're working [01:13] on. Um so [01:16] um today I would like to talk about uh [01:19] what's your inner source worth? Um so [01:23] that's the question I'm hoping uh we're [01:25] going to answer today. Um not with [01:27] philosophy or strategy but really with [01:30] um with framework u metrics and and real [01:33] results. [01:36] So um agenda uh first the challenge um [01:40] why um proving inner source ROI is hard [01:43] and why the uh measurement system failed [01:47] us. Second uh talk about strategic [01:49] framework. Um we'll we'll look at [01:52] worldly maps to see how we can decide [01:54] like how we decide to what to build, [01:58] what to share and what to buy. Um then [02:02] uh third measuring what matters and [02:04] we'll look at a live assessment um tool [02:07] that we built um that um helps us [02:10] quantify opportunities [02:12] um with um data, not not just vibes. Um [02:17] and fourth we'll we'll look at case [02:20] studies of inners source how innersource [02:22] is actually um used beyond just [02:25] engineering teams. [02:27] Um and uh final we'll we'll talk about [02:31] AI native and um why inner source um [02:34] isn't just for tomorrow um zad driven um [02:39] uh sorry isn't uh let me just remove [02:42] this [02:49] How was it? [03:05] Lost the mouse. That's okay. [03:14] technology. Um so we'll uh talk about [03:17] the challenge first. [03:20] Um so every leader I speak to believe in [03:25] inner source in practice or in principle [03:28] but when it's uh when the CFO um and CIO [03:32] ask about numbers um there's silence [03:36] um and I've been actually in both uh [03:40] side um been asked to provide ROI uh for [03:46] our inner source practices and as an [03:49] executive asking for uh numbers and I [03:51] know it's it's quite hard. So the [03:53] problem isn't that we um the the results [03:57] don't exist, it's that our measurement [03:59] DNA is still industrial. It's built for [04:02] output um not collaboration. [04:07] We're great at counting lines of code or [04:10] uptime, but terrible at quantifying [04:12] things like reuse, learning, or network [04:16] effects between teams. [04:21] Now, so why is proving in a source so [04:25] difficult? First, benefits are [04:29] multi-dimensional. [04:31] Collaboration, knowledge sharing and [04:33] cross skilling are powerful but they are [04:37] not linear. [04:39] You can't measure them with a single KPI [04:43] and they don't show up in Jira velocity [04:46] chart. [04:49] Second, the returns are delayed. The [04:51] payoff from [04:54] reuse and share learning doesn't happen [04:56] in the next sprint. It compounds over [04:58] time [05:00] just like compound interest. Every [05:03] shared component, every merge pull [05:05] request quietly accelerates the next [05:08] project. Granted that the the people who [05:12] are pushing this code know what they [05:14] what they what they what they're doing. [05:16] And the third, there is no standard [05:18] framework. Every organization measures [05:21] differently. Some track pull request, [05:24] others count contributions, but there's [05:27] no common um language, which means [05:29] results aren't comparable. Now, you [05:32] might say, [05:34] or you might be thinking, wait, we have [05:37] Dora metrics. [05:40] Deployment frequency, lead time, [05:42] meanantime to recovery, change failure [05:45] rate. Those are great, but they don't [05:48] measure but they measure delivery [05:51] frequency, not collaboration m maturity. [05:55] Dora tells you how fast code moves, but [05:59] not um how knowledge flows. [06:04] So not all collaboration is equal. Some [06:06] parts of your system drive competitive [06:08] advantage. [06:09] Others are just plumbing. That's why or [06:13] that's where worldly maps help. They [06:17] give us a way to visualize where [06:20] collaboration should happen and why. [06:26] So, [06:28] so before I talk about the framework, [06:31] um, let's first share that I believe or [06:36] we believe that inner source isn't just [06:37] a practice. It is a decision-making [06:40] framework. [06:42] So, let's look at these questions. What [06:44] creates competitive advantage for your [06:45] company? [06:47] It is your CI/CD pipeline? Probably not. [06:52] Is it your AI model that understands [06:55] your specific domain? Absolutely. [07:00] What would what should we own versus [07:03] rent? This is the strate the strategic [07:06] questions most companies get wrong. They [07:08] either outsource everything and lose [07:11] their edge or they build everything and [07:14] move very slowly. [07:16] What where do we need speed to innovate? [07:21] because that's where inner source shines [07:24] when multiple teams need the same [07:27] capability [07:29] but you can't wait for a vendor. So how [07:32] do we answer these questions? [07:39] So um I tried to put some animation on [07:42] the slide and it just messed up. So some [07:45] of the squares would pop up. Sorry but [07:48] uh let me explain. So this is uh worldly [07:50] maps and um on the left side this is [07:54] what we call the genesis. This is the um [07:57] the brand new your secret source. On the [08:01] right side that's the um uh m uh things [08:06] that are mature standard um buy but [08:09] don't um build. [08:12] And the middle is the inner source. So [08:15] this is where inner source excels. [08:19] So this is um I give you example with [08:21] with AI since is you know we talk a lot [08:24] about AI. So your custom AI model or [08:27] innovative architecture that's that's [08:29] what it is. You build it internally. You [08:31] guard it. This is your competitive [08:32] advantage. [08:34] But here's what um what changes the [08:37] game. [08:40] AI model orchestrations, [08:44] um, prompt engineers, rug architecture, [08:48] AI, AI benchmarking tools. Every team [08:51] needs these, but they are too custom to [08:54] buy of the shell. So this is the inner [08:57] source with spot. Don't build in silo. [09:00] Don't wait for vendors. Collaborate [09:02] internally. [09:05] As capabilities mature, productize them. [09:09] make them consumable. [09:12] And here is what you don't build on that [09:15] on on on on the right. It's the generic [09:18] LLMs, the open eye, the cloud um uh [09:21] cloud and so on. You just buy the API [09:25] also cloud infrastructure, Kubernetes [09:26] and so on. These are commodities. You [09:29] just uh you just use them. You don't [09:31] reinvent the wheel. [09:35] So this is pure strategic thinking. Know [09:41] what to build, what to share, and what [09:44] to buy. [09:46] Inner source is not about doing [09:48] everything together. It's about [09:51] knowing where collaborative it brings [09:54] the most value. [09:58] We've talked about strategy, uh what to [10:01] build, what to share, and uh what to [10:03] buy. And now let's talk about um proof. [10:07] How do we measure what matters? [10:09] Uh not line of code, not or story [10:12] points, but collaborative [10:14] uh collaboration, reuse, and maturity. [10:19] This is what we built to bridge the gap. [10:22] A live maturity. So this is a [10:24] cloudnative assessment uh maturity tool [10:27] um that takes engineering signals and [10:30] turns them into [10:32] narrative [10:34] executives can understand. So in this [10:36] example we have a team this team scores [10:40] 47%. [10:41] in the cloud native um maturity scale. [10:45] Um you can see below it shows nine [10:48] critical issues identified, a medium [10:50] risk rating and uh and 20K of in [10:55] potential costs saving. Um it even shows [10:58] an estimated time to the next level two [11:00] to three months. [11:02] Um so suddenly inner source is no longer [11:05] a philosophical observation. It's a [11:08] measurable business case. [11:13] The dashboard here also benchmarks you [11:16] against industry peers. The team this [11:19] team for example is ahead of 39 of [11:21] organizations in their in their space [11:24] but still far from leaders. The radar on [11:28] the on on the right shows exactly where [11:30] the gaps are. culture, CI/CD process, [11:33] architectural de compositions, we have [11:34] more. We have data, we have security and [11:37] so on. And below we list top improvement [11:40] opportunities, not just scores, but [11:43] where to focus first. That's what turns [11:46] inner source from theory into practical [11:48] road map. [11:50] So now this frame, this framework or [11:53] assessment uh tool is opiated based on [11:57] dozens of real cloud native and inner [12:00] source projects. It's not theory. It's [12:02] what actually works or works for us. And [12:05] we're happy to work um with partners and [12:09] other contributors and the inner source [12:11] common community to keep improving it, [12:13] making it available um to to everyone. [12:18] Now, let's talk about a real um uh real [12:21] uh case. So, I want to share um a story [12:25] uh from one of our um clients uh [12:27] Toyoshima. It's a 180 year old Japanese [12:30] textile company uh known for incredible [12:33] craftsmanship. But the industry industry [12:36] as a whole is very analog. So here's the [12:38] challenge. Designers [12:41] um uh worked in silos. Each created [12:44] patterns on their own systems. About 60% [12:48] of those samples were never even used. [12:51] And then you have sales teams needed [12:53] physical samples to show clients which [12:56] took week uh weeks to produce. [13:00] So there was no easy way to search or [13:02] reuse these past designs. Every project [13:04] started from scratch. Now the results of [13:07] the inner source and I'll explain um in [13:10] the next slide. You have [13:14] they um they are able now um once they [13:17] apply the inner source principles [13:20] shared repositories open contribution [13:22] visible asset they cut the pattern to [13:24] client cycle by 70%. [13:26] Sample testing that used to take three [13:28] weeks now takes a couple of hours they [13:31] produce 60% fewer physical samples [13:37] and and this is what I love about the [13:40] most about the story. It's not about [13:41] software. It's really about [13:43] collaboration. Inner source became the [13:45] bridge [13:47] between craftsmanship and um digital [13:50] innovation. [13:52] So here this is what the transformation [13:55] actually looks like. What so what you're [13:58] seeing here is a shared digital design [13:59] platform. The result of applying inner [14:02] source principles outside of [14:05] engineering. So designers, clients, and [14:08] sales teams all work together in real [14:10] time on the same system. Designers um [14:13] and they can they can design, recolor [14:16] and iterate instantly. No waiting for [14:18] physical samples, no passing files back [14:21] and forth. [14:23] Every fabric pattern, every color [14:24] palette, every design variation is [14:27] stored and [14:29] um also reusable and can be searched. [14:34] So inner source for design, not just [14:37] code, a shared first platform, cross [14:40] functional collaboration and reusable [14:42] knowledge. Exactly the same principles [14:44] that power the great engineering teams [14:46] now powering creative ones too. [14:52] Now next [14:54] let's look um one step ahead the AI [14:58] native future [15:02] when often [15:04] u we often talk about AI transformation [15:06] uh organization but AI alone doesn't [15:10] create intelligence it amplifies it [15:16] what's it implies what's already there [15:19] and that's where inner source become [15:20] critical. When you practice inner [15:22] source, you're already doing three [15:25] powerful things. First, [15:28] you're measuring collaboration. You're [15:30] making contribution [15:32] visible pull requests, reusable [15:35] patterns, shared assets. Second, [15:39] that visibility [15:41] turns into structured data, patterns [15:44] that describe how your teams actually [15:46] work. This data is gold. [15:50] It's the foundation [15:53] AI systems [15:55] need to reason about how your [15:57] organization builds and learns. And [16:00] third, the structure enables AI [16:02] amplifications. So imagine AI agents [16:05] that can review PRs or command reuse or [16:08] even autogenerate reports [16:11] because they understand your [16:12] collaborations, your collaboration [16:14] graph. So you're not just building [16:16] better culture, you're building the [16:19] operating system for AI native [16:22] organizations. [16:23] AI won't replace collaboration, it will [16:26] scale it. And inner source gives us the [16:29] blueprint to make that happen. [16:34] So before we wrap up, let me leave you [16:37] with some practical uh something [16:39] practical what to do Monday morning. Um [16:43] first we start small. Pick one shared [16:46] capability, a library, an internal tool, [16:50] um a CI template for example, something [16:53] small but used by multiple teams but [16:56] multiple teams. That's your seed. Second [16:59] measure. Track how many people use it, [17:02] contribute to it and reuse it. You don't [17:05] need fancy tools [17:08] at first just visibility. And third, [17:11] quantify. Calculate your opportunity [17:13] cost. [17:15] Ask if we didn't share this, how much [17:17] time would we lose rebuilding it? That's [17:21] your starting ROI. You can scan for Q um [17:24] sorry. Yeah. So, um we I I put a QR code [17:28] um to to access the assessment tool and [17:31] happy to discuss uh more about it. Um so [17:36] again it's openated but we're open to [17:38] improve it together with partners and [17:40] the community. Um and um if you'd like [17:43] to continue the conversation um that's [17:45] my contact and happy to um to talk [17:49] after. [17:51] I think that's about it. Yeah. Thank [17:53] you. Thank you very much.