11 Ways to Play the AI Shift in Software Work

AI is basically the world's most confident junior developer. 🙃 🤖 It has an answer for everything. 🤖 It happily works at 3 AM. 🤖 It is completely wrong 25% of the time, with absolute certainty. But you can’t build enterprise-grade software on confidence alone. With the tech market shifting, outsourcing is no longer a race to the bottom on price. It is a race to the top for senior human engineers who know when not to listen to the AI. We help tech companies scale by injecting pre-vetted, high-performing developers into their workflows to anchor their product roadmaps. If you are looking to scale your engineering velocity without sacrificing code reliability, let’s exchange a few ideas. #SoftwareEngineering #ITOutsourcing #VietnamTech

𝗔𝗜 𝗠𝗮𝗱𝗲 𝗖𝗼𝗱𝗲 𝗙𝗿𝗲𝗲. 𝗦𝗼 𝗪𝗵𝘆 𝗔𝗿𝗲 𝘁𝗵𝗲 𝗚𝗶𝗮𝗻𝘁𝘀 𝗦𝘁𝗶𝗹𝗹 𝗪𝗶𝗻𝗻𝗶𝗻𝗴? Everyone says AI lets solo developers beat big companies. Others say big companies will just absorb everything. Both views are wrong. I analyzed four major 2025 developer datasets from Google Cloud, Stack Overflow, GitHub, and JetBrains. Here is what the data actually shows. AI dropped the cost of writing code to near zero. It did not lower the cost of trust, support, or distribution. These factors make up 80% of a software business. The middle is disappearing. Small, VC-funded startups building simple features are losing. They get crushed by solo devs building for free and giants who bundle features for free. The real winners are the extremes: Solo founders and massive giants. Key findings from the 2025 data: - AI is an amplifier, not an equalizer. It makes good teams better and bad teams worse. - Adoption is universal. 80% to 90% of developers use AI. - Trust is dropping. 66% of developers find AI solutions frustrating because they are almost right but not quite. - Speed is a trap. One study found experienced developers were 19% slower with AI, even though they felt 20% faster. How solo founders can win: 1. Focus on independence. AI helps those with low coordination costs. A solo dev has zero organizational drag. 2. Master your architecture. AI helps you create unmaintainable mess fast. Use modular, boring architecture to avoid platform risk. 3. Localize. Giants ignore local payments, local laws, and local languages. This is your wedge. 4. Build a relationship moat. If your only defense is a feature, a giant will copy it next quarter. Build trust instead. The builder base is moving global. The next decade of founders will come from India, Brazil, and Indonesia, not just California. AI made building nearly free. The real contest is now about taste, trust, and focus. These do not come in an API. Source: https://lnkd.in/g2rryDgG Optional learning community: https://t.me/GyaanSetuAi

The tech industry is evolving faster than most of us are prepared for. Frameworks that were industry standards two years ago are now being reconsidered. Skills that felt secure last year are being automated today. Solutions that once took entire teams months to build are being replaced in a matter of weeks. This pace used to feel overwhelming. Now I see it differently. The professionals thriving in this industry are not necessarily the ones with the deepest knowledge of any single tool. They are the ones who have made adaptability their greatest strength. They do not attach their identity to a language or a framework. They attach it to problem-solving. History keeps proving this. Technologies change. The fundamentals do not. Those who understood the underlying principles of software development never struggled when the tools shifted. Those who only knew the tools did. The industry does not reward the people who know the most. It rewards the people who learn the fastest. Artificial intelligence is not replacing developers. It is raising the standard of what a developer needs to be. Writing code is no longer enough. Today, the real value lies in systems thinking, engineering judgment, and the ability to solve complex problems that no tool can navigate on its own. The bar is rising. And that is not a threat. It is an opportunity for everyone willing to keep growing. Stay curious. Stay adaptable. Keep building. The industry will keep moving forward. The only question worth asking is whether you are moving with it. #SoftwareDevelopment #TechIndustry #WebDevelopment #AI #FutureOfTech #SoftwareEngineering #CareerGrowth #LearningInPublic #DeveloperMindset

I delivered this talk at The Australian National University earlier this year and will be talking to people in Darwin next week. 𝐖𝐡𝐞𝐧 𝐀𝐈 𝐜𝐚𝐧 𝐰𝐫𝐢𝐭𝐞 𝐜𝐨𝐝𝐞 𝐢𝐧 𝐬𝐞𝐜𝐨𝐧𝐝𝐬, 𝐰𝐡𝐚𝐭 𝐢𝐬 𝐥𝐞𝐟𝐭 𝐟𝐨𝐫 𝐭𝐡𝐞 𝐡𝐮𝐦𝐚𝐧 𝐝𝐞𝐯𝐞𝐥𝐨𝐩𝐞𝐫?   Title: "𝐓𝐡𝐞 𝐇𝐮𝐦𝐚𝐧 𝐀𝐏𝐈: 𝐖𝐡𝐲 𝐘𝐨𝐮𝐫 𝐃𝐞𝐠𝐫𝐞𝐞 𝐌𝐚𝐭𝐭𝐞𝐫𝐬 𝐚𝐬 𝐌𝐮𝐜𝐡 𝐚𝐬 𝐘𝐨𝐮𝐫 𝐈𝐃𝐄" It’s a question that a lot (may be all) of students and early-career devs should be asking right now: Will there still be a place for me tomorrow?   The answer is an absolute yes. AI can generate code, but it can’t understand human frustration, build trust, or care about the community. Your professional development isn't just about syntax, it's about learning how to think structurally, question deeply, and navigate uncertainty.   🎟️ 𝐒𝐚𝐯𝐞 𝐲𝐨𝐮𝐫 𝐬𝐞𝐚𝐭 𝐡𝐞𝐫𝐞: https://shorturl.at/LuNzI 📅 𝐖𝐡𝐞𝐧: 9 July, 2026 (Thursday)  🕠 𝐓𝐢𝐦𝐞: 5:30 PM - 7:30 PM  📍 𝐖𝐡𝐞𝐧: Oaks Hotel, Darwin City, Level 1  (Please take the lift and head to Level 1) Here is what we are getting into:   𝐁𝐫𝐢𝐝𝐠𝐢𝐧𝐠 𝐭𝐡𝐞 𝐠𝐚𝐩: Turning abstract tech problems into human solutions. 𝐇𝐨𝐰 𝐫𝐞𝐚𝐥 𝐭𝐞𝐚𝐦𝐬 𝐰𝐨𝐫𝐤: Moving past theory to how people actually communicate, disagree, and build trust. 𝐅𝐢𝐧𝐝𝐢𝐧𝐠 𝐲𝐨𝐮𝐫 𝐧𝐞𝐭𝐰𝐨𝐫𝐤: Why a local community builds the resilience and belonging you need as tech shifts. Core-X GDG Darwin (Google Developer Groups)

93% of developers now use AI. Delivery moved 10%. The gap isn't a rounding error. It's the whole story of 2026. Adoption hit 92.6%. Roughly 27% of production code is AI-generated. And organizational throughput has barely crawled past 10%. Look closer and it gets worse. A field experiment across 4,867 developers, run by MIT, Princeton, Wharton and Microsoft, found the senior engineers, the ones above median tenure, got no significant gain at all. METR ran a controlled study on experienced open-source devs working in their own repos. Measured result: 19% slower with AI. Self-reported feeling: about 20% faster. They felt fast while shipping slow. Nobody notices that from the inside. Meanwhile the vanity metrics scream success. 21% more tasks closed. 98% more PRs merged. Then bugs climb, review queues back up, rework piles on, and DORA change-failure rate moves the wrong way. So the code gets written faster and the system gets fixed slower. The person paying that tax is the senior who reviews, integrates, and stabilizes the flood. The bottleneck already moved. It left writing code. It now lives in reviewing it. If you measure your team on individual output right now, you are measuring the one number that stopped meaning anything. Two questions, pick your honest answer. Is your senior team faster or slower since AI landed? And what is your review queue actually doing? #AI #SoftwareEngineering #EngineeringLeadership #DeveloperProductivity #AICoding

Every AI doomer on this app owes software engineers an apology. For two years straight, the loudest voices in tech said engineering was the first job AI would kill. News outlets said it. VCs and founders said it. Half of LinkedIn and X had some version of it. They were wrong. I run a company that places engineers at AI labs, hyperscalers, and startups from seed to Series A. We've done 500+ placements. We grew 8x last year and we're still growing month over month. If AI was replacing engineers, our business would be dying. Instead it's the opposite. AI increased the total amount of software that needs to be built. Every company now wants to ship AI products and the infrastructure to support them. That means more engineers, not fewer. What changed is the bar. Companies stopped hiring engineers to write boilerplate. They want people who can direct AI, ship fast, and own outcomes end to end. So yes, some engineers are getting squeezed out. The ones who can't adapt and still treat coding like data entry are losing to engineers who think in systems and use AI as a multiplier. Every company I talk to is fighting over that second group. The demand went up and the standards went up. The doom predictions were just wrong. If you're an engineer reading headlines about being replaced, close the tab and go build something. What are you actually seeing in your hiring right now?

AI is not killing developers. It is killing the entry point into the profession. The path used to be simple. Junior learned on small tasks. Mid-level got bruised on medium ones. Senior knew why everything broke because they broke it themselves. Today juniors do not write code. They prompt. They do not understand why it works. But it works. For now. Here is the question I cannot stop thinking about. What happens in 10 years when today's seniors retire? Who will audit the AI if the next generation never wrote code by hand? Who will catch the query that kills production if nobody ever spent 3 hours staring at EXPLAIN ANALYZE? We are not losing jobs. We are losing the mechanism that reproduces expertise. And that is far more dangerous. Is this panic or a real industry problem? Tell me what you think. #SoftwareDevelopment #AIinDev #TechFuture #Laravel #SeniorDeveloper

AI isn't replacing developers. It's creating two very different kinds of developers. And the gap between them seems to be growing every month. ━━━━━━━━━━━━━━━ 🚀 TIER 1 — The Accelerated • Uses AI as a productivity multiplier, not a replacement for thinking. • Knows when to trust AI output—and when to challenge it. • Spends more time on architecture, problem-solving, code review, and product decisions than repetitive implementation. • Learns faster because AI helps remove repetitive work. ━━━━━━━━━━━━━━━ ⏸️ TIER 2 — The Resisting • Avoids AI because of skepticism, habit, or fear of becoming dependent on it. • Still relies almost entirely on manual coding for everyday tasks. • Competes on typing speed and syntax knowledge instead of higher-level decision-making. • Risks falling behind as AI-assisted workflows become more common. ━━━━━━━━━━━━━━━ Here's the part many people won't like. Today, both groups can absolutely have good jobs. Both groups can build great software. But as AI becomes a standard part of engineering workflows, developers who know how to work with AI are likely to have an advantage in speed, adaptability, and the kinds of problems they can take on. ━━━━━━━━━━━━━━━ The biggest barrier isn't learning AI. It's changing how you think about your role. If you believe your value comes from writing every line of code yourself, AI feels like a threat. If you believe your value comes from solving problems, making sound technical decisions, and building reliable systems... AI becomes another tool. ━━━━━━━━━━━━━━━ The craft was never typing code. The craft is understanding systems. Designing solutions. Making trade-offs. Reviewing what matters. That's still your job. AI just helps you spend more time doing it. ━━━━━━━━━━━━━━━ So here's my question: Which tier do you think you're in today? And if you're trying to move toward Tier 1, what's the biggest challenge holding you back? #AITools #FrontendDevelopment #TechCareer #SoftwareEngineering #DeveloperProductivity #FutureOfWork #CareerGrowth Google for Developers Aitools

Until about 6 months ago I was using AI to complete the functions and validate my decisions. Productivity increase was at least 3x, was able to get 80 percent accurate results from prompt one. Then Claude Code happened, within a few hours I was able to fully build a functional MVP that is connected to a real database. The craft that was honed over 15+ years looked pale and my future as a developer looked even more so. I was left scrambling for a job as the company that hired me for the last 5 years also had similar ideas. Then I got to work with a team of exciting young engineers who is as AI-native as it can get. I started to feel how my parents must have felt learning a smart phone, neverthless the curiousity kept me motivated. Slowly I started to see the cracks in the AI native developers, the juniors are now more productive than ever, their speed is in fact hurting the seniors who are maintaining the products. POCs and MVPs are great, but enterprise grade products where every line is scrutinized this new approach is also making senior devs work harder than ever. That is not just the troublesome part, there is no roadmap for training future senior developers. AI is going to stay in one form or another, we need to define boundaries and work towards a sustainable path. Do share your experience and thoughts on the same.

Slightly uncomfortable truth: A lot of organisations seem to be acting as though AI is simultaneously unreliable and ready to replace entire teams. Both can't be true. I use AI tools every day. When they operate in familiar territory they can be incredibly useful. When they wander into unfamiliar territory they can become confidently inventive. The awkward part is we're now seeing two conversations happening at once. One group believes AI has solved software development. The other group spends half their day checking what AI just produced. Meanwhile junior developers are being asked for experience they can't gain because the work they would normally learn from is increasingly being automated. The whole industry feels like it's trying to skip a chapter and hoping nobody notices. I'm genuinely interested where people think this settles in five years.