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586 followers
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Jeff M. shared this📢 We're hiring at Atlassian for someone to come and work with us as we scale out our DX infrastructure! https://lnkd.in/gPct3SKd
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Jeff M. shared thisI decided to put Claude Code agent teams to work exploring fringe scientific theories. If you've seen the movie Oppenheimer, I'm feeling like General Groves (Matt Damon) right now. Feels like I've tapped into what Dario Amodei is calling a "country of geniuses in a datacenter". I want to know what the shape of the electron is. I want to see some pretty pictures, and put my gaming GPU to good use. Gonna crack a beer and keep cracking the universe. My team: a Nobel Prize winner for the physics, a mathematician for the proofs, and a coder who will mass-parallelize the search for truth. https://lnkd.in/g9JmySpuGitHub - jeffmoss/electron-topology: An experiment with Claude agent teamsGitHub - jeffmoss/electron-topology: An experiment with Claude agent teams
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Jeff M. reposted thisJeff M. reposted thisToday we’re announcing DX Annual, our flagship conference for developer productivity leaders. Since DX’s founding, customers have asked us for a venue to learn from each other and study what the best companies are doing. With AI transforming the SDLC at an unprecedented rate, the need for a gathering like this is more important than ever. The inaugural DX Annual will be held on April 16th in San Francisco, bringing together a curated group of ~400 senior engineering leaders from companies like Pinterest, Nationwide, Dropbox, Netflix, and Dell. If you’re a leader focused on developer productivity and AI transformation, I’d love to see you there. Request an invite: https://dxannual.com
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Jeff M. reposted thisJeff M. reposted thisAI is changing how every company builds software. But engineering leaders are struggling with the question: "Is AI truly helping our teams deliver better software, faster?" We're excited to announce our definitive agreement to acquire DX, the leader in developer intelligence, to help deliver answers. By combining our expertise in teamwork with DX's engineering intelligence, we're empowering every team to thrive in the AI era. DX helps over 350 enterprises, including Pfizer, Pinterest, and Xero, measure, benchmark, and improve developer experience and productivity. Together with Rovo Dev, Compass, Bitbucket, and Jira, DX will give our 300,000+ customers the clarity and confidence to: ⚡ Invest in the right places 🔍 Understand developer experience in real time 📊 Prove the impact of AI Welcome to the team, DX! Read more: https://go.atlss.in/8tgq9k
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Jeff M. reposted thisJeff M. reposted thisAnnouncing: Plaid Layer Layer increases end-to-end sign up rates by 10 - 25%. In a world where 1-2% gains are considered a big win. Here’s how we give you the Internet’s fastest, highest converting financial onboarding experience: 1. 📱 You send us your user's phone number when they're signing up for your service. From that, Plaid tells you whether that user is in the Plaid network 2. ⚡ In-network users are given the choice to sign up instantly with Plaid. Layer authenticates the user, and then presents them everything from their name and date of birth to their SSN and their most relevant previously linked bank account 3. 🌐 Your user hits "Share" and instantly permissions their full identity so you can KYC them. This also links a bank account in one tap (for supported institutions) This is a *massive* improvement in user onboarding. It's an 87% reduction in end to end financial onboarding time - KYC to account linking. And it works, today, for tens of millions of users who are already in our network. Some of my favorite key features: 🔑 Next-level user authentication, powered by direct-to-carrier SIM authentication, our ML models for thwarting bad actors, Passkeys for seamless login, and our network of trusted devices 📊 You can make sure that only users who have *exactly the data you need* on file go through this experience. Everyone else uses your existing signup flow. 🎉 We only charge you when users successfully share their information and link an account with you. Our incentives are 100% aligned with yours. 🧠 We called it Layer because it's a layer that sits on top of your sign up flow that only appears when it benefits you and your users It's available starting today. Link in the comments.
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Jeff M. shared thisJeff M. shared thisHuge update this week for Cognito Flow! Introducing Flow Network Explorer: A sophisticated new way to help you understand the graph of potentially fraudulent users and shut them down proactively. Flow is always trying to block fraudulent verification attempts, and one of the most powerful tools we use involves understanding the velocities of various characteristics of users signing up for your platform. Today we use Device IDs and IP address and plan to expand it more over time. Learn more (and read about this week's other product updates) here: https://lnkd.in/gTqDaJSz #kyc #amlcompliance #fraudprevention #identityfraud
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Jeff M. shared thisPeople are saying Flow is the Stripe of identity verification, very well-built inside and out. The integration couldn't be any simpler. Have a look!Jeff M. shared thisIntroducing Flow, our biggest product launch yet. Flow is a drop-in, complete ID verification system that works globally 🌎 . https://lnkd.in/gZatBwE It now only takes businesses 20 minutes to integrate a sophisticated + beautiful ID verification experience. - 📇 PII verification in 36 countries - 🛂 Passports/ID card/DL verification globally - 💖 High conversion and localized UX - 🔒 Built-in anti-fraud indicators - ⚡️ No code, real-time editor It really feels like ✨ magic ✨ and we can't wait for you to try it! Interested in trying the beta? Sign up for a sandbox account here: https://lnkd.in/gnPqthA and shoot us an email at support@cognitohq.com to get it enabled on your account
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Jeff M. shared thisWe're doing exciting work at Fountain! We have a few engineering positions available, if you're interested in working on a rapidly scaling web app reach out to me directly!Jeff M. shared thisThrilled to share that Fountain has released a new analytics suite to empower business leaders to gain a better understanding of the candidate journey and make data-driven decisions. I couldn't be more proud of the work our team is doing! http://ow.ly/u6qL50DqqC5 #ATS #highvolumehiring #recruiting
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Jeff M. shared thisJeff M. shared thisFlow Kana’s technology team is growing rapidly and immediately hiring several product management, UX design and software engineering roles (backend, front end and full stack). See roles here: https://lnkd.in/g85gju6 We’re building the premier cannabis brand and supply chain backbone of California, the fifth largest economy in the world. If you’d like to solve new and refreshing problems in supply chain, marketplaces, agriculture, compliance, and farmer experiences, we have about ten or so jobs you might like to check out. This is not an ordinary software job. Rather, it's an exciting journey of important causes, beautiful places and with very special people. Please take a peek or share with friends. (The image below is from a recent technology team offsite.)
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Jeff M. liked thisKeith's proposal here is quite interesting, and definitely deserves more attention. Perhaps it's insufficiently glamorous, but hopefully some smart engineers can contribute their brain power to exploring this innovation (or we could just continue to let AI hornswogglements and the dopamine-driven social media influence bamboozlements suck up all the available oxygen 😎).Jeff M. liked thisLos Angeles has a 30-million-ton problem. Every year, LA County produces enough waste to fill a skyscraper. Despite "Zero Waste" goals, we are running out of landfill space and struggling with rising illegal dumping. Meanwhile, California is adding 13 GW of intermittent solar by covering aqueducts. We have the waste, and soon, we’ll have the excess power. What we’re missing is a way to bridge the two. The Proposal: Trash-to-Syngas Seasonal Storage I am proposing a grid-coupled energy storage pathway that transforms municipal waste into syngas and liquid fuels. This isn't just disposal—it’s a way to store seasonal solar energy. How it works: Inspired by 1800s "town gas" methods, this process vaporizes trash in steam over a pool of melted slag heated by induction coils. The Scale: Vaporizing all of LA’s trash (approx. 4,000 tons/hr) would require ~6.5 GW. The Storage: Unlike batteries, syngas can be stored in depleted oil or gas fields for seasonal use. The Output: The resulting syngas can be converted into sustainable aviation fuel (SAF). There is enough carbon in LA’s trash to potentially supply LAX’s entire fuel demand. Why this beats Incineration or Landfills: Zero Methane: Unlike landfills, there is no organic decay releasing GHGs. Cleaner Output: Unlike incineration, it’s easier to capture chlorine and fluorine from a syngas stream than from massive volumes of stack exhaust. Water Neutral: The process utilizes the moisture already present in "wet" trash. This is a long-term, massive-scale infrastructure project. It requires a significant growth in solar, but it solves two of our greatest challenges: waste management and long-duration energy storage. Is it time we stop looking at trash as a liability and start seeing it as a battery? #Sustainability #CleanTech #RenewableEnergy #LosAngeles #Engineering #CircularEconomy
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Jeff M. liked thisJeff M. liked thisAfter 4 years at Workera, I've moved on. I learned what I came to learn, and it's time for the next inflection point. I couldn't be more proud of what we built and look forward to seeing what the Workera team does next. --- Workera is an AI skills verification platform for enterprises. Over those years, I served as Head of Product and then Director of Product Marketing. Huge thank you to Kian Katanforoosh, Tim DaRosa, and Falen Milton ⚡️ for taking a chance on me and for the mid run pivot. Here's what we shipped: 1) Launch the Rocket: the moonshot that set the stage for what came next. 2) The vision of measuring any skill and breaking capabilities down to their smallest unit. That became Compose: assessments for any skill, based on a company's own docs and goals. 3) Category narrative and positioning that delivered a verification data layer enterprises adopted: ServiceNow, SoftBank, Medtronic, Booz Allen Hamilton The approach: → Structured experimentation: we shipped, measured, and adjusted. → Trust-first AI, validated iteration. → Same pattern at scale: Behavior change through validated iteration, similar approach that pushed growth and adoption at DataCamp and Pluralsight. One moment I'm especially proud of: we helped a Fortune 500 tech company roll out Elo, our AI Skills Agent, to their entire employee population. Most skills tools get 18% participation. We proved enterprises would trust AI for verification when you gave them controlled rollouts and measurable outcomes. All while more than doubling ARR and maintaining enterprise trust. I left knowing we’d built something that would outlast me. --- Our whole industry is at an inflection point, but the opportunity I care about is more specific than AI. I want to build for the moments in life that feel the most out of control. Health. Learning. Financial stress. The places where fear is the default and good technology can actually return power to the person. What I've learned, at Pluralsight, at Workera, and honestly from a community project I've been running on the side, is that activation is the easy part. The hard part is getting people to keep showing up for something difficult because it means something to them. That's the problem I keep gravitating toward. Behavior change that sticks because it's tied to identity, not just utility. If you're building in that space and you know you're at an inflection point but aren't sure how to solve it, I'm looking for my next VP Product, Head of Product, or CPO role. I'd love to talk. #openToWork #AI #ProductManagement #VPProduct
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Jeff M. liked thisJeff M. liked thisICYMI: Fintech infrastructure company Plaid revealed on Thursday that it has completed a new fundraise to provide liquidity to employees at a valuation of $8B. That valuation is up 31% from the $6.1B the San Francisco-based company was valued at in April 2025 when it completed a separate tender offer. At its peak in 2021, Plaid was valued at $13.4B.Fintech Plaid Completes Tender Offer At $8B ValuationFintech Plaid Completes Tender Offer At $8B Valuation
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Jeff M. liked thisExcited to be part of the Data Foundation + AI team that launched Plaid’s first foundation model for financial data. This is just the beginning of the cutting edge models we’re building to improve transaction understanding at scale. Huge thanks to the team: Han Yu, Ozgur Can Seckin, Melody Zhao, Kevin Supakkul, Wen Yao, Raghu Chetlapalli, Zachary Keller Bhaskar DuttJeff M. liked thisFor most people, money is still harder than it should be. If AI is going to matter in finance, it has to make financial products genuinely more helpful, secure, and responsive to real life. I’ve spent the last decade building large-scale data networks, and I’m convinced the next chapter of financial services won’t just be about access to data, it will be about understanding it. Open finance unlocked secure, permissioned connectivity. That foundation enabled a generation of innovation. Now AI is ushering in the next wave of innovation. Intelligent finance means systems that understand context, adapt in real time, and continuously improve. It means stopping fraud without adding unnecessary friction. It means making better decisions across payments, credit, and identity, with the accuracy and trust this industry demands. It also requires infrastructure that is purpose-built and understands how money moves. At Plaid, we’re building intelligence models that learn from patterns across our network and compounds with scale. As part of that work, we’ve developed our first transaction foundation model for finance to deepen how financial activity is understood across products. I believe this shift from open finance to intelligent finance will define the next decade. I wrote more about how we’re approaching it here: https://lnkd.in/gV35NPbyWhy intelligent finance needs purpose-built AI infrastructure | PlaidWhy intelligent finance needs purpose-built AI infrastructure | Plaid
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Jeff M. liked thisI’m excited to share a significant step forward for Plaid: the launch of our first foundation model purpose-built for financial data. Understanding financial transactions at scale is more complex than it seems, yet getting it right underpins countless decisions and products. To address this, we moved beyond brittle rules and built a model that learns a richer representation of financial activity directly from de-identified transaction data across the Plaid network. We’re already seeing meaningful improvements in transaction understanding and merchant identity resolution, strengthening the accuracy and resilience of the systems built on top of it. This work reflects the kind of AI we believe in: practical, high-precision systems designed to operate reliably within critical financial infrastructure. I’m incredibly proud of the team that brought this vision to life. We’re hiring on this team, along with other AI and data roles across Plaid. If you’re excited about building foundational AI systems in finance, I’d love to connect. Also check out current openings at https://plaid.com/careers/Jeff M. liked thisFor most people, money is still harder than it should be. If AI is going to matter in finance, it has to make financial products genuinely more helpful, secure, and responsive to real life. I’ve spent the last decade building large-scale data networks, and I’m convinced the next chapter of financial services won’t just be about access to data, it will be about understanding it. Open finance unlocked secure, permissioned connectivity. That foundation enabled a generation of innovation. Now AI is ushering in the next wave of innovation. Intelligent finance means systems that understand context, adapt in real time, and continuously improve. It means stopping fraud without adding unnecessary friction. It means making better decisions across payments, credit, and identity, with the accuracy and trust this industry demands. It also requires infrastructure that is purpose-built and understands how money moves. At Plaid, we’re building intelligence models that learn from patterns across our network and compounds with scale. As part of that work, we’ve developed our first transaction foundation model for finance to deepen how financial activity is understood across products. I believe this shift from open finance to intelligent finance will define the next decade. I wrote more about how we’re approaching it here: https://lnkd.in/gV35NPbyWhy intelligent finance needs purpose-built AI infrastructure | PlaidWhy intelligent finance needs purpose-built AI infrastructure | Plaid
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Projects
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Toastd
- Present
See projectA port of toastr library to the dart language. Toastr is a jquery plugin to display android-style toasts in web apps.
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ActiveResource Pagination
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See projectA ruby gem library providing pagination support for ActiveResource models.
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Roofray
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See project"Basically it’s a solar clearinghouse that uses Google satellite data and info from the National Renewable Energy Labs to help users make good decisions about what sort of system to buy."
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Nalini Belaramani, PhD
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Senior engineering leader with 10+ years of experience leading large distributed teams (up to 80+ persons) in a broad range of areas. Proven track record for scaling teams, carrying out turnarounds and team turndowns. Skilled in driving strategy and impact through strong execution and inclusive team culture. <br><br>Experience in Regulatory Compliance, Trust & Safety, Android, Corp Eng, Cloud, Data Analytics Infrastructure<br><br><br>Core Competencies:<br>* Strategic Leadership: Defining and executing strategic initiatives in complex environments. Architecting robust solutions utilizing both 1st and 3rd party technologies.<br>* Organizational Development: Building and transforming high-performing distributed engineering teams, including experience with team growth, turnarounds, and transitions.<br>* Effective Communication: Fostering collaboration and influencing stakeholders across multiple teams, external partners, and OEMs.<br>* People Development: Empowering and mentoring engineers and managers, creating a culture of growth and innovation.
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Mike Dyer
Wits Innovation Lab • 1K followers
DDD is the gold standard for complex domains. Everybody agrees. Evans was right. Vernon was right. The methodology works. But nobody wants to say the quiet part out loud. It was designed for teams. Knowledge crunching? That's two or more people in a room wrestling with ambiguity. Event storming? You need a wall, sticky notes, and a room full of people who disagree productively. Context mapping? That's a negotiation between teams. Every foundational practice in DDD assumes you're not alone. So what happens when you are? I'll tell you what happens. You adopt the tactical patterns without the strategic discipline. You define aggregates without doing bounded context analysis. You emit domain events without modeling policies or sagas. You build what looks like DDD from the outside but is really CRUD with fancier names. That's not a criticism. I've done it. You've probably done it. It's the rational response to a methodology that hands you the vocabulary but locks the practice behind a door marked "requires team." Here's the thing though — the patterns aren't the hard part. The books cover those. The conference talks cover those. What the books can't cover is the thing that happens when a senior practitioner points at your model and says "that boundary is wrong, and here's why." That transfers through osmosis. Through rooms. Through years of sitting next to people who've internalized things they can't articulate. If you don't have the room, whole layers of the methodology become invisible. Not wrong. Invisible. I wrote about why this matters and what it means for the thousands of architects building serious systems alone. https://lnkd.in/gNW7r-sn #DomainDrivenDesign #SoftwareArchitecture #DDD #SoloBuilder #AI
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Matt Watson
Full Scale • 78K followers
Engineers should constantly ask why, push back on bad ideas, and suggest alternatives. Some of our clients find it jarring at first. "Why is my developer questioning requirements?" Because that's what great engineers do. They think. They challenge. They improve. Unless, you want silent compliance and mediocre products 🤔
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Felipe S.
TrueDial • 3K followers
Funny watching big companies dunk on “vibe coded startups” like they just exposed something. “You can’t build stable systems like that.” “Won’t scale.” “Not production-ready.” No shit. That’s not what it’s for. You’re evaluating it like it’s supposed to replace your 200-engineer stack. Meanwhile, a 3-person team is using it to: test ideas in days get real user feedback iterate 10x faster than your roadmap allows Of course it looks messy to you. Your entire worldview is: stability process risk mitigation quarterly planning Their world is: speed learning what outcome takes less resistance to success Vibe coding isn’t trying to compete with enterprise systems. It’s a velocity engine. A test bench. A way to punch way above your weight *before* you earn the right to build it “properly.” So when a big company trashes a vibe-coded product for not being stable… it just shows they don’t understand the game being played. You’re optimizing for perfection. They’re optimizing for truth. And truth shows up faster than your next sprint cycle.
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Justin Gordon
ShakaCode • 5K followers
Any best guesses on how long until Claude Code can: 1. Fire up the browser (without needing the MCP configuration) to evaluate changes 2. Fully leverage the Chrome Dev Tools 3. Use the Ruby debugger I’m finding Claude Code is creating fixes that would have been too tedious or painful. The gap right now is testing and debugging.
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CM Pravda
Architectural Consultant and… • 5K followers
Todays WORKFLOW TIP: “Parallelization” using sub-workflows to expiditer Ai Tasks which lag when done linearly, can be improved w/ “DIVIDE & CONQUER” strategy to makes applications snappy. ( not to be used for all workflows ) Factor in requests for API calls as well. EXAMPLE: Perplexity ( for research 🧐 tasks ) allows only ~50 requests per minute (RPM) =~ 0.83 requests per second (RPS) EXAMPLE: Openai GPT4o allows only 500 RPM ~ 8.33 RPS ( that’s a 10x increase to certain tasks, So we can add loop + wait functionality for batching sub-workflows )
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Edward Kreiman
We Are Agentic • 5K followers
If you're leading post-acquisition delivery and timelines are slipping while engineers quietly churn - this is the part no playbook prepares you for. The code was clean. The infra played nice. The teams were stuck. It's not tech debt. It's not tooling. It's not your roadmap. It's culture. Not the fluffy kind. The deep, invisible defaults - how teams think, prioritise, and act when things get hard. I've led 7 tech integrations, and here's what I've learned the hard way: Clean architecture won't save you... But aligning on these 8 cultural levers before you write a line of code will. 1. Value Hierarchy What wins when tradeoffs hit- velocity, stability, dev experience, or uptime? Tip: Build a tradeoff matrix. When priorities clash silently, resentment grows loudly. 2. Decision Velocity Are choices made in 2 days or 2 weeks? Tip: Codify a 48h SLA. Momentum dies in async purgatory. 3. Risk Tolerance What happens when things break—do teams freeze up or push ahead blindly? Tip: Define "safe to fail" by environment. Speed without guardrails ≠ agility. 4. Trust Defaults Can engineers ship solo, or must they get approval? Tip: Align on autonomy thresholds. Confusion here creates slowdowns and surprises. 5. Feedback Norms Slack thread or status deck? Blunt or buffered? Tip: Co-create a feedback contract. Psychological safety isn't a given under pressure. 6. Technical Ownership Who owns what post-Day 1? Tip: Map systems and names. Ambiguity kills accountability. 7. Architecture Philosophy OSS-first or enterprise-preferred? Tip: Surface tooling biases early or risks future deadlocks over tech "religion." 8. Talent Signalling What does "good engineering" mean here? Tip: Align your definition. Otherwise, you'll hire (and reward) the wrong behaviours. Since aligning these levers: • Delivery overruns dropped 68% • Engineer retention rose to 91% • $3-5M preserved per integration Want the Cultural Alignment Scorecard? Comment "ALIGN" or DM me, and I'll send it over. Or forward this to your Head of Engineering. Let's fix what's stalling your integration before you write another line of code.
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Juliette Stephens
Nathan Clare Consultants • 2K followers
Six months of decisions that never got made. Here's what that actually cost. The plan was ready. The team was ready. Four exec forums. No outcome. Just “let’s review next quarter.” While everyone waited:: • $300K burned on idle contractors • A critical platform fell out of support • Senior engineers disengaged And still, progress was expected. Indecision is still a decision. It just hides the cost. What changed things wasn’t alignment. It was ownership. “We’re starting Monday unless someone stops it by Friday.” That single shift forced clarity. Delay was no longer invisible. Where is delay costing more that deciding right now? Most leaders don’t see the cost until it’s too late.
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Brandon Levey
Ichi • 3K followers
I was showing Ichi to about 120 building department staff when something interesting happened... During my webinar with CALBO last week I was demonstrating how we pull code sections and jurisdiction-specific requirements. Standard demo stuff. But these folks didn't only care about the speed (though yeah, turning 30-minute code searches into seconds is nice). They want to know, how can they trust it. This is where being able to show them the exact source of information matters. Makes total sense when you think about it. These are the people who carry the liability when something goes wrong. They're not going to trust some AI that spits out answers without showing its work. That's why we built Ichi to be completely transparent. The plan reviewers and inspectors I talked to after were genuinely relieved. Someone finally built tech that respects how they actually need to work. If you want to see what transparent AI for building departments actually looks like, I'll share the full demo link in the comments.
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Saurabh Anand
Emergent Labs • 10K followers
Developers weren’t just builders. They were gatekeepers. If you couldn’t code, you didn’t create. You waited. On engineering bandwidth. On roadmaps. On someone else’s priorities. Syntax was the wall. Know where the semicolon went? You shipped. Didn’t? You stood outside. That divide shaped more than workflows. It shaped status. Developers got the leverage. The scarcity gave them the power to decide what shipped and when. Everyone else adapted around them. It wasn’t about being smarter. It was about access — and access wasn’t evenly distributed. Some people were in the right rooms early, tripped into syntax, and built from there. Others never got the chance. That was the difference. But syntax was only the first kind of alpha. The second was quieter. Harder to see. More enduring. System knowledge. Knowing which database could survive Black Friday traffic. When to debounce vs. throttle. How to shard writes across regions. Not just writing code — architecting it. That’s the tacit layer. Built from war stories. Outages. Scaling pain. Years in the trenches. It’s still here. And it still matters. For now. I remember the first time I tried to shortcut it. I’d tell Claude what I wanted. It would spit out code. I’d paste it. It would break. I’d send back the error. It would try again. Loop by loop, something shifted. Reddit called it “copy-paste monkey.” They saw a hack. I saw a door opening. People who’d been locked out started building demos. Then products. Then real companies. The wall between “technical” and “non-technical” was never about intelligence. It was about translation. And now, translation is free. What matters now isn’t syntax. It’s clarity. How well you can think. Break things down. Iterate. That’s what the agent understands. And that’s what it rewards. The syntax advantage is gone. Developer privilege is flattening. System knowledge is next. Today, the agent can’t always choose the perfect database. But if you tell it the trade-offs, it will. If you give it context, it will architect with precision. That tacit edge still holds. But only for now. Soon, even that will be embedded. And leverage will shift again — to anyone who can think clearly enough to guide the machine. That shift isn’t coming. It’s here. And it’s not going away.
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Divansh Gupta
Confidential • 5K followers
I often ask, “Why did you design it this way?” The strongest candidates don’t jump to tools — they explain the trade-offs. Example: “We used EMR for this pipeline because Glue jobs were hitting concurrency limits, and we needed better tuning control.” That one line shows experience, ownership, and context awareness. #DataEngineering #InterviewTips
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Shan Hanif
Genflow • 48K followers
A team member messaged me after a 4-hour call fixing dev issues. "I can't believe you were on that call." We have 100+ people at Genflow. I run a $100M agency. And I was right there debugging code with the team. It hit me how wrong most people get leadership. Everyone thinks being CEO means strategy sessions and vision boards. Wrong. Being CEO means being the captain who's still on the field. You show people how it's done by doing it alongside them. Not above them. The idea that you'll build a business and just work on "high-level stuff" while everyone else executes? That's not how you scale. You scale by staying close to the work. Understanding the actual problems. Building alongside your team. After 9 years of doing this, I've learned: The best CEOs aren't in corner offices. They're in the trenches when things break. They know the product inside out. They can still do the work if needed. Your team doesn't follow titles. They follow leaders who roll up their sleeves. What kind of leader are you trying to be?
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Marc Gasser
Pedalix • 8K followers
Agents are the new apps. And they just went multiplayer. The software engineering landscape is undergoing a seismic shift. Google just dropped Firebase Studio. And it might just replace half the AI builder startups out there. You’ve probably seen tools like Lovable, bolt.new, Vercel's v0, or Cursor. They let you build AI-powered apps without writing much code. Describe what you want — boom — they create UIs, workflows, and automation for you. It’s fast. It’s smart. It’s changing how software is built. Now imagine that… backed by Google. What is Firebase Studio? Firebase Studio is Google’s new end-to-end app builder for AI-first products. It combines: ✅ UI generation ✅ Agent workflows (like AgentSpace) ✅ Firebase backend (auth, storage, hosting, etc.) ✅ Google’s best Gemini models AgentSpace is like a command center for AI agents. It lets you create multistep workflows, connect APIs, and manage how agents behave. Great for product teams prototyping internal tools, automations, or AI assistants. But it’s still pretty early-stage. Right now, Firebase Studio and A2A (Agent-to-Agent) are two separate moves from Google — but they are strategically aligned, and integration is very likely coming. You need to manage agents, instructions, tools, and sometimes code. Why this matters for product managers? → The barrier to building software is decreasing. → With Firebase Studio, a product manager can do what used to take a team. The AI agent is becoming the new app. Not just chat. Agents that do stuff: send emails, fetch data, run logic. Google wants to standardise agents across platforms. Their new Agent-to-Agent protocol (A2A) means your agents could soon talk to each other — across apps, tools, maybe even companies. Enter MCP: The USB-C for AI Anthropic’s Model Context Protocol (MCP) is an open standard that enables developers to build secure, two-way connections between their data sources and AI-powered tools. MCP is a standardised protocol designed to streamline the way AI models communicate with external systems, eliminating the need for custom integrations. With so many advancements happening rapidly, it’s challenging to keep up and navigate them within the realities of development. Yet, it has never been more exciting to be in the software engineering space. #AI #FirebaseStudio #ProductManagement #Innovation #TechTrends #MCP #A2A
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Daniel Kempe
Quuu • 3K followers
The way we build software is about to fundamentally shift, and most teams aren't ready for it. I'm watching something fascinating happen right now. Software development agents are moving from "nice to have" to "embedded in your actual workflow." Not in some separate tool you have to context-switch into. We're talking agents that live in your IDE, your Slack, your CI/CD pipeline, your project manager. Everywhere you already work. Here's what gets me: this isn't about replacing developers. It's about removing friction. When you spot a refactor that needs doing, you don't context-switch and spend an hour on it. You delegate it right there and keep shipping. When an incident hits at 2am, your team doesn't start from zero. The agent is already in the war room with them. The real competitive advantage isn't going to teams with the fanciest AI. It's going to teams that integrate this into their actual development rhythm without disrupting it. The ones who treat agents as part of their workflow, not a parallel process. For founders building technical products right now, this is worth paying attention to. Your development velocity just became a core business metric in ways it wasn't before. What's your biggest bottleneck in your current development process? The thing that takes time but doesn't actually require your creative problem-solving? That's probably your first candidate for this kind of delegation.
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Patrick How
Howrecruit • 14K followers
You don’t need 10x engineers. You need cracked ones. (No, it doesn't mean broken as I initially thought 🤣) Had a great call last week with a founder and their on-site team about a critical engineering hire. They didn’t want someone “good.” They wanted someone cracked. At first, I literally had no idea what they were talking about (Thank you posthog 🦔.) Turns out it means engineers who demonstrate: Extreme ownership - they run towards problems and pull the team with them Enthusiasm for the craft - the kind that lifts the room even on rough days Care for quality and velocity - they think in systems, not just sprint tickets. They multiply the impact of those around them. This mindset can turn an “almost” project into one that gets deployed on time and shifts the needle for the business. At StreamYard, I saw it up close. The hires that changed everything weren’t just strong coders. We just didn't call it "cracked" at the time lol. They were energy givers (no energy vampires in startups 🧛) Engineers who took the mission personally. Engineers who others wanted to follow. Quick tip Don’t just ask: Can they do the work? Ask: Will they bring clarity, momentum and belief? That’s what cracked really means. If you're hiring now or have hired engineers in the past, how do you assess this? If you'd like to give a cracked engineer a shout-out, tag them in the comments for some props! Everyone loves a bit of positive recognition.....
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Sudhanshu Sharma
Learn With Psudo • 981 followers
This one might hurt a little. 👀 I’m being honest. 🫡 I’ve worked in teams that said, “We’ll add tests later.” Later never came. —————- ❌No TDD Feature starts fast. PR looks big and impressive. Everyone claps. Then… One small change breaks three modules. QA finds regression. Hotfix goes out. Another thing breaks. Now the same feature costs 3x the effort. Speed at the start. Stress at the end. —————— ✔️With TDD Start with a failing test. Write just enough code to pass. Refactor safely. Repeat. It feels slower. It feels uncomfortable. It forces you to think. But here’s what I’ve seen: Fewer surprises. Cleaner design. Refactoring without fear. Confidence during releases. —————— TDD isn’t about loving tests. It’s about respecting the future version of yourself who will maintain this code. From my QA lens, the difference is clear: Without TDD → QA becomes a damage controller. With TDD → QA becomes a quality partner. And that shift changes everything. Agreed? Learn With Psudo #TestDrivenDevelopment #TDD #SoftwareDevelopment #QualityEngineering #ShiftLeft #AutomationTesting #Agile #DevOps #CleanCode #ContinuousIntegration #SoftwareTesting #TechLeadership
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Charles Palen
Transcending Digital LLC • 283 followers
I think the future of development won't be 2x,5x,10x but how creative and parallel can you effectively go without bad output quality. Maybe we call this being a 2p or 5p engineer. It will probably involve managing many agents and layering additional agents on those for quality, company standards, security, compliance, CI/CD. This is the current trend in a lot of the literature and hints from hot AI devs being released to the public. I see inexperienced developers complaining that these AI tools are not good. I think that's wrong. They are amazingly good. The tools enhance the common experienced design patterns of small file sizes, and limited context per file that requires a lot of discipline. This image was generated with Comfy UI using Flux Kontext Dev
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Ayyoub El Amrani
Mirage Metrics • 5K followers
Hiring engineers for hard operational problems is different. Most candidates can write clean code. Fewer can sit with a dispatcher at 7am and understand why their shift planning breaks down. Fewer still can go back to the codebase and design something that actually works in production with those constraints. What I look for at Mirage Metrics is not just skill with Python, SQL, or distributed systems. It is a willingness to go into environments that are messy, sometimes chaotic, and keep digging until the real bottleneck shows up. That can mean inventory mismatches hidden in Excel, planning rules written on a whiteboard, or API endpoints that return inconsistent data depending on who queries them. The best engineers I have worked with are the ones who do not flinch at this. They treat debugging a customs declaration pipeline with the same seriousness as debugging a memory leak. They know that solving “boring” problems in data quality or workflow mapping is what unlocks everything else. On the technical side, I test for clarity. Can someone explain the trade-offs between running a model via an API versus hosting it on GPUs without getting lost in jargon. Can they design a schema validator that will still make sense six months later when requirements change. Can they write glue code that is robust, not fragile. On the personal side, I look for stamina. These projects are rarely about building a shiny feature in isolation. They require iteration with operators, late-night debugging of OCR failures, and the patience to integrate into legacy systems that were never designed for AI. If you want to work on AI for logistics, manufacturing, or mining, the question is not only whether you can code. It is whether you can hold your ground in the real world, in front of the people whose work depends on your system. That is the bar.
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Jarod Stewart
WRAPS • 934 followers
Colorado just introduced SB 26-051, and as a developer based here, I need to talk about how fundamentally misguided this is. The bill requires operating system providers to build an "age signal" API into device setup, then mandates that every app developer call that API when their app is downloaded and launched. The age data? It comes from a parent or account holder self-reporting a birth date during account setup. Let me get this straight: the state of Colorado wants to legislate a real-time API contract between OS providers and every application developer — enforced by fines up to $7,500 per minor per violation — and the entire system is backstopped by... a parent typing in a date? Here's what this actually does: It creates a state-mandated surveillance pipe from OS to app. It shifts compliance burden onto independent developers who now must integrate a government-required API or face penalties. It does absolutely nothing to stop a 14-year-old from entering "1990" at setup. And it gives Colorado legislators the ability to say they "did something" about child safety online. If you actually care about protecting kids online, this isn't it. This is compliance theater dressed up as child safety legislation. The kids who need protection aren't going to be protected by a self-attestation date field. The developers who build thoughtful, safe products are going to be buried in compliance overhead. We can do better than mandating API contracts by statute. https://lnkd.in/gmedNMKx
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