Toni Klopfenstein

The Meta layoffs hit pretty close to home. A lot of friends and former colleagues got let go on Monday. I understand that companies grow, and then need to scale back. But to explicitly call out low performers makes me upset. It seems like it's their way of handing out scarlet letters for the job search. I really wish the wording was more along the lines of reducing operational expenses, rather than cutting low performers. Here's why- I grew a lot as an engineer and a person while I was there. But what I never shared publicly is I had to interview 3-4 times after getting rejected over and over. I ultimately joined as a contractor, quickly converted to FTE after proving myself, and got promoted the first PSC cycle, only a couple months after I was hired. In all my PSCs, I consistently got 'greatly exceeds' and 'exceeds'. The company was smaller, and I had opportunities to shine. Towards the end of my tenure, the hardware group was a lot larger and I was struggling to find ways to make impact. My scope had narrowed, I got my first 'meets all', which was gutting, and opportunities to move up had shrunk, and then I left. The point being is that their interview process is gruelling! They only hire the top performers. And when a company grows so quickly, sometimes those top performers have less work and opportunity to make impact. They're not 'low performers'. So to any prospective employer, recruiter, or manager reading this, please don't disregard anyone from Meta. The vast majority of folks I worked with there were all rockstars, and I'd hate to see anyone get pushed to the bottom of the pile because they were affected in 'this layoff.'

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Signal Seekers. You, as a Technical Program Manager, are signal seekers. There is a TON of noise when you're leading a large initiative or program. One of your jobs is to discern noise from signals. These signals are the things you need to address before they throw everything off course. You know...the squeaky wheels. Those are the signals. How do you find them? You pick up on these signals through building great relationships with people involved, facilitating regular avenues to talk, creating an environment of safe discussion, and driving a culture of healthy accountability. Signal Seeking is a core skills of a high-impact TPM.

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I genuinely think we as an industry are shooting ourselves in the foot by not investing in the next generation of software engineers. I see far too many companies only hiring Senior Engineers, often not to solve hard problems just because they want to have senior engineers just in case they run into hard problems. but the seniors aren't getting the chance to grow by mentoring more junior engineers, and they are often stuck doing grunt work that kills their motivation. Compound this with the "We won't hire anyone else, we'll just rely on AI to speed things up." attitude and we're generating a lot of crap code that no one understands, and the people who can maintain it are going to eventually age out of the market without there being anyone to pick up the mantle. I see a lot of graduates struggling to find roles on r/CSCareerQuestionsUK on Reddit, Inc. and it really makes me sad. SOURCE: https://lnkd.in/e_v375PQ

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I didn't learn one important aspect of the principal engineer role until I left my first job with that title. Three different intermediate devs privately told me something along the lines of "I stayed here because you seemed to have faith in the company." My presence in a principal role isn't just about what I can do for the company or what it can do for me. It is a vote of confidence in both the company and in its leadership. Just by being employed I am implicitly telling other employees, "How they treat you here is fine. This is a good company."

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"What slows you down?" It's a simple question, but one that reveals so much about what our engineers experience every day. When I posed this to our Engineering org, the answers surprised me. And they led us to create something different from the typical "Developer Experience" team you see at most tech companies. We call ours Developer Amplification (DevAmp) and their purpose is to amplify our engineers and their impact, not just make them more productive. So, what makes DevAmp at Duolingo unique? 📈 Customers, not colleagues  DevAmp operates almost like a B2B startup where engineers are our customers - focusing on product sense, user testing, and metrics-driven decision making, all applied to internal tools. ⚡ From chore work to genius work  Currently engineers spend roughly 20% on high-leverage work and 80% on low-leverage tasks. Our goal is to make that 80:20 in favor of the creative, innovative work only humans can do. 🔧 No more library updates  We're automating the tasks nobody wants to do - like upgrading libraries across dozens of microservices (who actually enjoys that?). 🎯 Why this matters  In the age of AI, we're preparing for engineers to ship 2-10x faster. The goal isn't to do less with more. It's to do more with more. We're already seeing promising results in several areas: - Streamlining code reviews with AI assistance - Automating tedious library updates across microservices - Accelerating test creation and documentation - Automating app release testing The purpose of DevAmp is to make building software not only easy, but genuinely fun. And I think we’re off to a great start. #Duolingo #engineering

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My latest blog post: Using AI to promote divergent thinking A possible explanation for why we observe such a discrepancy between the productivity gains from AI tools of seasoned senior software engineers versus their less-experienced counterparts: Inexperienced problem solvers have a tendency to get stuck when using AI tools to solve complex problems because they bias towards convergent thinking: narrowing possibilities and looking for a specific solution which fits within their preconceptions. Experienced problem solvers who have adopted AI tools tend to use it to augment a scientific process, which includes building mental models, formulating hypotheses, and performing experiments. In this process, they use AI to accelerate divergent thinking: exploration and discovery of possibilities. (Blog post link in the first comment)

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In distributed systems, reliability isn’t just about retries and durability, it’s about knowing who owns recovery. My latest post, based on the Coordinated Progress model I posted previously, explores how reliable triggers create responsibility boundaries and how those boundaries shape resilience, observability, and complexity. https://lnkd.in/diCmywnS

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I’ve interviewed a lot of junior engineers over the years. Some had impressive portfolios. Others had none. But the ones who stuck with me? They had one thing in common: they kept showing up - even when it was frustrating. If you're teaching yourself how to code, trying to land that first job, or pushing through imposter syndrome - remember, the dev who stays in the game long enough usually finds their break. I’ve hired people with bootcamp backgrounds, self-taught paths, and resumes full of question marks. I can teach someone how to code. I can’t teach them how to keep going when it’s hard.

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Throughout my 20+ year career in software, integration work was often relegated to the "lower decks" of engineering. Armies of talented engineers designed, updated, and maintained the crucial components that make systems actually work together. Yet despite the complexity of their roles, they were frequently overlooked by those building "core algorithms." Now, with the rise of agentic AI, integration work is stepping into the spotlight. If you're an experienced integration engineer, I believe you're positioned to benefit significantly in the near to mid-term. Why? Because successful integrations demand exceptional attention to detail and the engineering rigor to be both forward-thinking and backwards-compatible. These skills are now more valuable than ever. But let's be realistic: integration work won't be immune to automation in the long run. Today's opportunity is to shape the methodology and standards that will define successful integrations going forward.

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Someone recently asked me what separates a Senior Engineer from a Staff Engineer, and these were the first things that came to mind: Staff engineers think and operate beyond their immediate area. They connect the dots across teams, influence product direction, and help shape the technical roadmap even without formal authority. They define what problems are worth solving. They spot high-ROI opportunities, sense technical risk early, and challenge unnecessary complexity with calm conviction. They go beyond mentorship. Instead of just guiding individuals, they build systems: libraries, patterns, and team rituals that raise the baseline for everyone. They land more impact through leverage and influence. They invest in discussions and documentation that turn good ideas into shared direction and real progress. And they communicate exceptionally well, keeping the right people informed, aligned, and inspired. What did I miss?

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